WO2018106496A1 - Catheters, systems, and related methods for mapping, minimizing, and treating cardiac fibrillation - Google Patents

Catheters, systems, and related methods for mapping, minimizing, and treating cardiac fibrillation Download PDF

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Publication number
WO2018106496A1
WO2018106496A1 PCT/US2017/063747 US2017063747W WO2018106496A1 WO 2018106496 A1 WO2018106496 A1 WO 2018106496A1 US 2017063747 W US2017063747 W US 2017063747W WO 2018106496 A1 WO2018106496 A1 WO 2018106496A1
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Prior art keywords
tissue
electrode
ablation
electrodes
electrogram
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PCT/US2017/063747
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English (en)
French (fr)
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Peter S. SPECTOR
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University Of Vermont
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Priority claimed from US15/369,483 external-priority patent/US10912476B2/en
Application filed by University Of Vermont filed Critical University Of Vermont
Priority to AU2017370535A priority Critical patent/AU2017370535B2/en
Priority to EP17879048.1A priority patent/EP3547910A4/de
Priority to CA3045988A priority patent/CA3045988A1/en
Publication of WO2018106496A1 publication Critical patent/WO2018106496A1/en
Priority to IL267047A priority patent/IL267047B2/en

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B18/04—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/25—Bioelectric electrodes therefor
    • A61B5/279—Bioelectric electrodes therefor specially adapted for particular uses
    • A61B5/28—Bioelectric electrodes therefor specially adapted for particular uses for electrocardiography [ECG]
    • A61B5/283—Invasive
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/361—Detecting fibrillation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6846—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be brought in contact with an internal body part, i.e. invasive
    • A61B5/6847—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be brought in contact with an internal body part, i.e. invasive mounted on an invasive device
    • A61B5/6852—Catheters
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B18/02—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by cooling, e.g. cryogenic techniques
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B17/00—Surgical instruments, devices or methods, e.g. tourniquets
    • A61B2017/00017—Electrical control of surgical instruments
    • A61B2017/00022—Sensing or detecting at the treatment site
    • A61B2017/00039—Electric or electromagnetic phenomena other than conductivity, e.g. capacity, inductivity, Hall effect
    • A61B2017/00044—Sensing electrocardiography, i.e. ECG
    • A61B2017/00048—Spectral analysis
    • A61B2017/00053—Mapping
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00315—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body for treatment of particular body parts
    • A61B2018/00345—Vascular system
    • A61B2018/00351—Heart
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00571—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body for achieving a particular surgical effect
    • A61B2018/00577—Ablation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00636—Sensing and controlling the application of energy
    • A61B2018/00642—Sensing and controlling the application of energy with feedback, i.e. closed loop control
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00636—Sensing and controlling the application of energy
    • A61B2018/00696—Controlled or regulated parameters
    • A61B2018/00702—Power or energy
    • A61B2018/00708—Power or energy switching the power on or off
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00636—Sensing and controlling the application of energy
    • A61B2018/00773—Sensed parameters
    • A61B2018/00839—Bioelectrical parameters, e.g. ECG, EEG
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00636—Sensing and controlling the application of energy
    • A61B2018/00898—Alarms or notifications created in response to an abnormal condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00636—Sensing and controlling the application of energy
    • A61B2018/00904—Automatic detection of target tissue

Definitions

  • the present disclosure relates generally to methods and systems for detecting and treating cardiac fibrillation. More specifically, the present disclosure relates to physiologic, particularly electrophysiologic, methods and systems for preventing, treating, and at least minimizing if not terminating cardiac fibrillation by mapping cardiac fibrillation and optimizing the placement of ablation lesions and methods and systems for detecting contact between a tissue and an electrode.
  • Atrial fibrillation which accounts for almost one-third of all admissions to a hospital for a cardiac rhythm disturbance, is an uncontrolled twitching or quivering of muscle fibers (fibrils) resulting in an irregular and often rapid heart arrhythmia associated with increased mortality and risk of stroke and heart failure.
  • muscle fibers muscle fibers
  • Radio Frequency Ablation Two Systematic Literature Reviews and Meta-analyses, 2(4) Circ. Arrhythmia Electrophysiol. 349-61 (2009).
  • Atrial fibrillation may be paroxysmal or chronic, and the causes of atrial fibrillation episodes are varied and often unclear; however, atrial fibrillation manifests as a loss of electrical coordination in the top chambers of the heart. When fibrillation occurs in the lower chambers of the heart, it is called ventricular fibrillation. During ventricular fibrillation, blood is not pumped from the heart, and sudden cardiac death may result.
  • Atrial Flutter and Supraventricular Tachycardia 104(5) Am. J. Cardiol. 61 ⁇ , 674 (2009).
  • ablation is to alter atrial and/or ventricular physiology and, particularly, electrophysiology such that the chamber no longer supports fibrillation; it is insufficient to simply terminate a single episode.
  • ablation lesions have the potential to cause additional harm to the patient (e.g., complications including steam pops and cardiac perforation, thrombus formation, pulmonary vein stenosis, and atrio-esophageal fistula) and to increase the patient's likelihood of developing abnormal heart rhythms (by introducing new abnormal electrical circuits that lead to further episodes of fibrillation).
  • cardiac fibrillation patients would benefit from new methods and systems for the preventing, treating, and at least minimizing if not terminating cardiac fibrillation in the underlying "substrate" (i.e., the tissue on which abnormal electrical circuits of reentry are formed) responsible for the initiation and perpetuation of cardiac fibrillation.
  • substrate i.e., the tissue on which abnormal electrical circuits of reentry are formed
  • These methods and systems would help clinicians minimize or prevent further episodes and increase the success rate of non-invasive ablation treatments in cardiac fibrillation patients.
  • There remains a need for patient-specific, map-guided ablation strategies that would minimize the total amount of ablation required to achieve the desired clinical benefit by identifying ablation targets and optimizing the most efficient means of eliminating the targets.
  • Electrodes When electrodes are placed transvenously into the heart, the operator has no direct visualization of the electrode or the heart. Therefore, a method is required to identify when the electrode is in contact with the heart.
  • a method is required to identify when the electrode is in contact with the heart.
  • Some of these methods require medical imaging technology of various types. For example, they may require intracardiac ultrasound, MRI, 3D localization systems or force detectors. Each of these requires additional systems and equipment above and beyond the catheter, electrode and amplifier. Because of the additional imaging technology required in these systems, the systems and methods disclosed herein, which can identify electrode tissue contact and electrode orthogonality using electrogram analysis alone, has the advantage of decreased complexity and reduced cost.
  • the SmartTouch catheter from Biosense Webster uses an electromagnetic signal to identify the position of the tip electrode relative to the end of the catheter, this information along with knowledge of the force required to deform the tip electrode allow calculation of the force and direction of electrode tissue contact.
  • St Jude medical employs a system that measures the resistance of a circuit from a radiofrequency generator through a catheter, through the body and back through a dispersive grounding patch to the generator. The impedance of the tissue is higher than the blood and increased impedance is used to determine electrode tissue contact.
  • the present invention recognizes that identification of local tissue activation frequency can identify circuit cores in atrial fibrillation. See, e.g., Benson, B.
  • One of the most important parameters that influence spatial resolution is the height of the recording electrode above the heart surface. See e.g., Stinnett-Donnelly, J. M., et al., Effects of Electrode Size and Spacing on the Resolution of Intracardiac Electrograms, 23(2) Coron. Artery Dis., 126-132 (2102).
  • electrode height due to the impact of electrode height on spatial resolution it is useful to be able to identify electrode tissue contact.
  • determination of electrode tissue contact is important for frequency mapping during atrial fibrillation.
  • the present disclosure includes both computational and in vivo studies that illustrate that electrogram frequency varies with electrode height. The accuracy with which electrogram frequency measurements identify tissue frequency is maximal with electrode tissue contact.
  • the electrode configuration with the highest spatial resolution is a bipolar recording between two electrodes where one electrode is in contact with the tissue while the second electrode is directly above the first (orthogonal to) the tissue surface.
  • Thompson, N. C, et al. Improved Spatial Resolution and Electrogram Wave Direction Independent with the Use of an Orthogonal Electrode Configuration, Journal of Clinical Monitoring and Computing, in press (2013).
  • This "orthogonal close unipolar" configuration allows maximal spatial resolution and records electrograms whose amplitude is independent of wave direction. When recording tissue activation frequency this direction independence is important because during atrial fibrillation ("AF"), waves travel in random directions and if some waves are "unseen” then the electrogram frequency will be less than the actual tissue frequency.
  • AF atrial fibrillation
  • the methods and systems of the present invention are predicated on the recognition and modeling of the actual physiologic and, particularly, electrophysiologic principles underlying fibrillation.
  • the prior ablation art fails to recognize the importance of and provide methods and systems for gauging a patient's fibrillogenicity, e.g., how conducive the atria are to supporting atrial fibrillation and how much ablation is required for successful treatment, detecting and mapping fibrillation, optimizing the distribution of ablation lesions for both effectiveness and efficiency, and guiding ablation based on quantitative feedback methods and systems.
  • These methods and systems of the embodiments of the present invention are directed, therefore, to defining successful strategies, procedures, and clinical outcomes that are tailored for each patient with cardiac fibrillation.
  • catheter optimized for mapping cardiac fibrillation in a patient including an array of at least one stacked electrode pair, each electrode pair including a first electrode and a second electrode, wherein each electrode pair is configured to be orthogonal to a surface of a cardiac tissue substrate, wherein each first electrode is in contact with the surface to record a first signal, and wherein each second electrode is separated from the first electrode by a distance which enables the second electrode to record a second signal, wherein the catheter is configured to obtain one or more measurements from at least a first signal and a second signal in response to electrical activity in the cardiac tissue substrate indicative of a number of electrical circuit cores and distribution of the electrical circuit cores for a duration across the cardiac tissue substrate in the patient's heart.
  • catheter optimized for assessing efficacy of an ablation procedure in a patient comprising: an array of at least one stacked electrode pair, each electrode pair including a first electrode and a second electrode, wherein each electrode pair is configured to be orthogonal to a surface of a cardiac tissue substrate, wherein each first electrode is in contact with the surface to record a first signal, and wherein each second electrode is separated from the first electrode by a distance which enables the second electrode to record a second signal, wherein the catheter is configured to obtain one or more measurements from at least a first signal and a second signal in response to electrical activity in the cardiac tissue substrate indicative of a number of electrical circuit cores and distribution of the electrical circuit cores for a duration across the cardiac tissue substrate in the patient's heart.
  • a method for identifying electrode tissue contact comprising positioning a catheter including an array of at least a first electrode and a second electrode affixed to the catheter and having a known inter-electrode spacing in the vicinity of a cardiac tissue substrate; measuring a first rate of change in electrogram amplitude (dV/dt) from the first electrode; measuring a second rate of change in electrogram amplitude (dV/dt) from the second electrode; calculating a difference between the first rate of change in electrogram amplitude and the second rate of change in electrogram amplitude to obtain a delta dV/dt value; and correlating the delta dV/dt value to whether the first electrode is in contact with the cardiac tissue substrate.
  • FIGS. 1 A-1C illustrate the relationship between the source-sink ratio and wave curvature according to some embodiments of the present invention
  • FIGS. 2A-2B illustrate reentry circuits using a topological perspective of the tissue substrate, in accordance with embodiments of the present invention
  • FIGS. 3A-3B illustrate how the minimum path of a curling wavefront is limited by tissue excitation wavelength, in accordance with embodiments of the present invention
  • FIGS. 4A-4F illustrate rotor termination resulting from circuit transection via core collision with a tissue boundary according to some embodiments of the present invention
  • FIGS. 5A-5C illustrates the rotor ablation requirement of a linear lesion from the rotor core to the tissue edge, in accordance with some embodiments of the present invention
  • FIGS. 6A-6C are simulated patterns of cardiac tissue activity produced by a computational model, in accordance with embodiments of the present invention.
  • FIGS. 7A-7C illustrate surface topology and reentry, in accordance with embodiments of the present invention.
  • FIG. 8 illustrates the impact of boundary-length-to-surface-area ratio on the duration of multi-wavelet reentry according to some embodiments of the present invention
  • FIGS. 9A-9D illustrate how ablation lines increase the boundary-length-to-surface- area ratio and decrease the duration of multi-wavelet reentry, in accordance with
  • FIGS. 10A-10B illustrate the circuit density maps, particularly FIG. 10A illustrates homogenous tissue without a short wavelength patch, and FIG. 10B illustrates heterogeneous tissue with a wavelength patch, in accordance with embodiments of the present invention
  • FIG. 11 illustrates graphically ablation lesion characteristics and fitness of tissue with homogeneous circuit density, in accordance with embodiments of the present invention
  • FIGS. 12A-12B illustrate graphically the relationship of ablation density versus circuit density, in accordance with embodiments of the present invention.
  • FIG. 13 is a system component block diagram, in accordance with embodiments of the present invention.
  • FIG. 14 is a plot of simultaneous measurements of the atrial fibrillatory cycle length from surface ECG/EKG and the left and right atrial appendages according to some embodiments of the present invention;
  • FIGS. 15A-15D illustrate graphically atrial fibrillation cycle length (AFCL) correlation, particularly, FIG. 15A illustrates relationship between mean sureface
  • FIG. 15B illustrates relationship between surgace ECG AFCL from 10 CL and AFCL using time frequency analysis
  • FIG. 15C illustrates the relationship between surface ECG AFCL from 10 CL and the LAA CL
  • FIG. 15D illustrates the relationship between ECG AFCL from 10 CL and RAA CL in accordance with embodiments of the present invention
  • FIGS. 16A-16C are Bland- Altman plots illustrating the relationship between the RAA cycle length and the cycle lengths from time frequency analysis and surface ECG/EKG, in accordance with embodiments of the present invention.
  • FIG. 17 is a plot of the receiver-operator characteristic curve for the surface
  • FIGS. 18A-18B are plots of Kaplan-Meier curve analyses of the incidence of recurrent arrhythmia following ablation procedure, in accordance with embodiments of the present invention.
  • FIGS. 19A-19F illustrate temporal, spatial, and spatiotemporal variation of tissue excitation, in accordance with embodiments of the present invention
  • FIG. 20 illustrates electrode geometry, spacing, and position, in accordance with embodiments of the present invention
  • FIG. 21A is a graph illustrating fractionation as a function of temporal variation by the number of deflections versus stimulus cycle length, in accordance with embodiments of the present invention.
  • FIG. 2 IB is a series of virtual unipolar electrograms from tissue excited at decreasing cycle lengths, in accordance with embodiments of the present invention.
  • FIG. 22A is a graph of the number of deflections in unipolar recordings as a function of spatiotemporal variation and electrode resolution, in accordance with embodiments of the present invention.
  • FIG. 22B is a series of virtual unipolar electrograms from tissue excited with increasing spatiotemporal variation, in accordance with embodiments of the present invention.
  • FIGS. 23 A- 23B are fluoroscopic images of a catheter in the coronary sinus, in accordance with embodiments of the present invention.
  • FIG. 23C is a set of electrograms simultaneously recorded during sinus rhythm and atrial fibrillation with varying inter-electrode spacing, in accordance with embodiments of the present invention.
  • FIG. 24 is a schematic of a dipole current source located at ⁇ ⁇ /2 about the origin and a bipolar pair of electrodes of diameter d and height 1 separated by ⁇ and located at height zo along the y-axis, in accordance with embodiments of the present invention
  • FIGS. 25A-25B are graphical plots where FIG. 25A illustrates a comparison of predicted potential recorded by a unipolar electrode as a function of lateral distance from a dipole current source (solid line) and the potential measured experimentally in a saline bath (filled circles) and FIG. 25B illustrates a corresponding plot for bipolar recording, in accordance with embodiments of the resent invention;
  • FIGS. 26A-26B are graphical plots where FIG. 26A illustrates the potential due to a dipole current source recorded by a unipolar electrode as a function of lateral distance from the source, showing how resolution is quantified in terms of peak width at half maximum height and FIG. 26B illustrates the corresponding plot for a bipolar electrode, in accordance with embodiments of the present invention
  • FIGS. 27A-27B are graphical plots of simulates bipolar electrograms, in accordance with embodiments of the present invention.
  • FIGS. 28A-28C graphically illustrate the resolution of a unipolar electrode recording of a dipole current source as assessed in terms of Cmin and W1/2, In accordance with embodiments of the present invention.
  • FIGS. 29A-29D are graphical plots illustrating resolution of a bipolar electrode recording of a dipole current source, as assessed in terms of Cmin and W1/2, in accordance with embodiments of the present invention;
  • FIG. 30 is a process flowchart for identifying an optimal spatial resolution for local tissue with spatiotemporal variation, in accordance with embodiments of the present invention.
  • FIGS. 31 A-3 IB illustrate a catheter with a contact bipolar electrode configuration, in accordance with embodiments of the present invention
  • FIG. 32 illustrates the orientation of electrodes relative to an electric dipole, in accordance with embodiments of the present invention
  • FIG. 33 illustrates the orientation of electrodes relative to near and far field charges, in accordance with embodiments of the present invention
  • FIG. 34 graphically illustrates near fields spatial electrograms from a model, in accordance with embodiments of the present invention.
  • FIG. 35 graphically illustrates far field spatial electrograms from a model, in accordance with embodiments of the present invention.
  • FIG. 36 illustrates graphically electrical potential recordings at a single electrode, in a model, in accordance with embodiments of the present invention
  • FIG. 37 graphically illustrates membrane voltage underneath a single electrode, in a model, in accordance with embodiments of the present invention.
  • FIGS. 38A-38B illustrate a catheter with an orthogonal, close, unipolar (“OCU”) electrode configuration, in accordance with embodiments of the present invention
  • FIG. 39 illustrates the difference between a first catheter with an inter-electrode axis orthogonal to a tissue surface and a second catheter with an inter-electrode axis that is not orthogonal to the tissue surface, in accordance with embodiments of the present invention
  • FIG. 40 illustrates an example of improved spatial resolution obtained by use of an OCU electrode configuration, in accordance with embodiments of the present invention
  • FIGS. 41 A-41C illustrates the edge extension and windowing process applied to an exemplary transformation between the tissue membrane current density field and the potential field at height, in accordance with embodiments of the present invention
  • FIGS. 42A-42D illustrate examples of deconvolution, in accordance with
  • FIGS. 43 A-43L illustrate maps of membrane current density, in accordance with embodiments of the present invention.
  • FIGS. 44A-44B illustrate graphically mean square residual for the observed and deconvolved signals relative to the true signal for the two activation pattern shown in FIGS. 43 A-43L, in accordance with embodiments of the present invention
  • FIGS. 45A-45L illustrate true current density, observed signal, and deconvolved signal using different array electrodes, in accordance with embodiments of the present invention
  • FIGS. 46A-46B graphically illustrate the mean square residual for the observes and deconvolved signals relative to the true signal for the two activation patterns shown in FIGS. 45 A-45L, in accordance with embodiments of the present invention
  • FIGS. 47A-47I illustrate effects of electrode height on the resolution of a rotor showing the true current density, the observed signal, and the deconvolved signal at different heights, in accordance with embodiments of the present invention
  • FIGS. 48A-48D graphically illustrate mean square residual for the observed and deconvolved signals relative to the true signal for the activation pattern shown in FIGS. 47A- 471;
  • FIGS. 49 and 50 illustrate two-dimensional multi-electrode arrays, in accordance with embodiments of the present invention.
  • FIG. 51 A is a process flowchart for improving spatial resolution using deconvolution, in accordance with embodiments of the present invention.
  • FIG. 5 IB illustrates an exemplary window, in accordance with embodiments of the present invention
  • FIGS. 52A-52B illustrate a catheter with an OCU electrode configuration for identifying an optimal spatial resolution for local tissue with spatiotemporal variation, in accordance with embodiments of the present invention
  • FIGS. 53 and 54 illustrate different views of a catheter configured for both mapping and treating cardiac fibrillation according to some embodiments of the present invention
  • FIG. 55 is a process flowchart for assessing fibrillogenicity in a patient according to some embodiments of the present invention.
  • FIGS. 56A-56C illustrate the relationship between electrogram recordings and a resulting electrogram frequency map of a tissue substrate, in accordance with embodiments of the present invention
  • FIG. 57 illustrates the impact of selecting a threshold frequency to define the size and number of high circuit core density regions across a tissue substrate, in accordance with embodiments of the present invention
  • FIG. 58 illustrates a hierarchical tree-like structure provided by a genetic algorithm for optimizing lesion placement, in accordance with embodiments of the present invention
  • FIG. 59 is a process flowchart for applying a genetic algorithm for optimizing lesion placement to a map indicating circuit core density and distribution, in accordance with embodiments of the present invention.
  • FIG. 60 is a process flowchart for assessing fibrillogenicity in a patient, in accordance with embodiments of the present invention.
  • FIG. 61 is a process flowchart for treating cardiac fibrillation in a patient using iterative feedback, in accordance with embodiments of the present invention.
  • FIG. 62 is a system diagram, in accordance with embodiments of the present invention.
  • FIGS. 63 A-63B are a computer axial tomography scans of a human heart, in accordance with embodiments of the present invention.
  • FIGS. 64-65 are two views of a three-dimensional plot of the time to termination of induced episodes of multi-wavelet reentry as a function of total ablation length and circuit density overlap according to some aspects of the present invention;
  • FIGS. 66-67 are two views of a three-dimensional plot of the percent inducibility (z- axis) as a function of total ablation length (x-axis) and circuit density overlap (y-axis) in accordance with some aspects of the present invention
  • FIGS. 68, 69A-69B, and 70 illustrate catheter designs of alternative embodiments in accordance with some embodiments of the present invention.
  • FIGS. 71 A-71B illustrate a catheter with four electrodes at different rotational positions relative to a tissue substrate, in accordance with embodiments of the present invention
  • FIG. 72 illustrates the effect of catheter rotation and elevation on the accuracy with which bipolar electrogram frequency correlated with the activation frequency of the tissue immediately beneath the catheter;
  • FIGS. 73 A-73D illustrate the effect of catheter rotation on the correlation between bipolar electrogram frequency and the activation frequency of the tissue immediately beneath the catheter;
  • FIG. 74 illustrates map accuracy with and without correcting for electrode height
  • FIG. 75 illustrates the correlation between tissue and electrogram frequency during atrial fibrillation using electrodes with various heights and degrees of rotation
  • FIG. 76 shows is a close up on one activation, and shows electrograms as a function of height above the tissue
  • FIG. 77 shows a first derivative of electrograms as a function of height above the tissue
  • FIG. 78 shows dV/dt as a function of height above the tissue
  • FIG. 79 shows the delta dV/dt as a function of height above the tissue
  • FIG. 80 shows the difference in average maximal negative amplitude of the first derivative of electrograms from two orthogonal electrodes (delta dV/dt) versus the height of the electrodes above the tissue and rotation of the electrode pair relative to the tissue surface;
  • FIG. 81 shows examples of the first derivative of unipolar electrograms recorded from electrodes at various heights above a tissue during atrial fibrillation
  • FIG. 82 shows an example of the first derivative of a unipolar electrogram recorded during atrial fibrillation
  • FIG. 83 shows a plot of the first derivative of a unipolar electrogram (dv/dt) recorded during atrial fibrillation versus electrode height above the tissue surface;
  • FIG. 84 shows a plot of the difference in average maximal negative amplitude of the first derivative of electrograms from two orthogonal electrodes (delta dV/dt) versus the height of the electrodes above the tissue;
  • FIG. 85 is a process flowchart for identifying a threshold value, in accordance one embodiment of the present invention.
  • FIG. 86 is a process flowchart for identifying a threshold value, in accordance one embodiment of the present invention.
  • FIG. 87 is a process flowchart for identifying electrode tissue contact, in accordance one embodiment of the present invention
  • Embodiments of the present invention include new methods and systems for preventing, treating, and at least minimizing if not terminating cardiac fibrillation in the substrate responsible for initiation and perpetuation of fibrillation and for optimized treatments of that substrate, which are predicated on the recognition and modeling of the actual physiological information, including the electrophysiologic principles, underlying fibrillation, and detecting contact between a tissue and an electrode. These methods and systems make it possible for a clinician to develop and implement patient-specific, tailored fibrillation treatment, minimization, and prevention strategies. More specifically,
  • embodiments of the present invention allow a clinician to minimize or prevent further episodes and increase the success rate of ablation in fibrillation patients by preventing "reentry,” which perpetuates fibrillation as described in greater detail below.
  • new methods and systems for guiding treatment of fibrillation using quantitative feedback and determining when sufficient treatment has been provided are disclosed according to some embodiments of the present invention. Also disclosed are new catheter systems and methods for determining patient- specific and location-specific tissue spatiotemporal variations, mapping the density and distribution of circuit cores, and/or assessing the efficacy of a treatment procedure and detecting contact between a tissue and an electrode.
  • Cardiac fibrillation particularly atrial fibrillation, is a progressive disorder, wherein a heart's electrical properties become increasingly conducive to supporting fibrillation; hence episodes, once initiated, are progressively less likely to spontaneously terminate.
  • the outer wall of the human heart is composed of three layers.
  • the outer layer is the epicardium, or visceral pericardium because it is also the inner wall of the pericardium.
  • the middle layer is the myocardium, which is composed of cardiac muscle that contracts.
  • the inner layer is the endocardium, which is in contact with the blood that the heart pumps.
  • the endocardium merges with the endothelium of blood vessels and also covers heart valves.
  • the human heart has four chambers, two superior atria and two inferior ventricles.
  • the pathway of blood through the human heart consists of a pulmonary circuit and a systemic circuit.
  • Deoxygenated blood flows through the heart in one direction, entering through the superior vena cava into the right atrium. From the right atrium, blood is pumped through the tricuspid valve into the right ventricle before being pumped through the pulmonary valve to the pulmonary arteries into the lungs. Oxygenated blood returns from the lungs through the pulmonary veins to the left atrium. From the left atrium, blood is pumped through the mitral valve into the left ventricle before being pumped through the aortic valve to the aorta.
  • the study of clinical electrophysiology is essentially comprised of examining how electrical excitation develops and spreads through the millions of cells that constitute the heart.
  • Human cardiac tissue constitutes a complex non-linear dynamic system. Given the enormous number of cells in a human heart, this system is capable of generating a staggeringly large number of possible ways that the heart can behave, that is, potential activation patterns as excitation propagates through the tissue.
  • Rhythms vary across a spectrum, from the organized and orderly behavior of sinus rhythm, with large coherent waves traversing across all cells and then extinguishing, to pathologic behaviors during which activation propagates in continuous loops, perpetually re-exciting the cardiac tissue (via reentry) in structurally defined circuits like the complex, dynamic and disorganized behavior of cardiac fibrillation.
  • a basic understanding of the principles of propagation may be applied to predict how cardiac tissue will behave under varied circumstances and in response to various manipulations.
  • a cell becomes excited when the voltage of its membrane rises above the activation threshold of its depolarizing currents (i.e., the sodium current (INa+) and calcium current (ICa++)).
  • the net trans-membrane current must be sufficient to discharge the membrane capacitance.
  • the cell membrane separates charges across the space between its inner and outer surfaces, resulting in a voltage gradient. The size of the voltage gradient is determined by the number of charges and the distance by which they are separated.
  • the membrane capacity to hold charges on its surface is determined by the surface area of a cell membrane and its thickness (i.e., the distance by which it separates charges).
  • the force required to keep these charges from wandering away from a cell surface is generated by the electrical attraction to opposite charges on the other side of the membrane. The thinner the membrane, the closer the charges are to each other and the larger force they can exert to resist wandering off (i.e. the distance across the faces of a capacitor is inversely proportional to its capacitance).
  • Cardiac cell membranes can simultaneously accommodate inward and outward currents (via separate ion channel s/exchangers/pumps). Membrane depolarization is determined not by inward current alone, but rather by net inward current. If both inward and outward currents exist, the amount of depolarization (or repolarization) is determined by the balance of these currents. In their resting state, the majority of open channels in typical atrial and ventricular cells are potassium (K+) channels. This is why the resting membrane potential is nearly equal to the "reversal potential" for K+. As current enters a cell (e.g., via gap junctions from a neighboring cell), its membrane will begin to depolarize. This depolarization reduces the force preventing K+ from traveling down its concentration gradient. K+ flows out of the cell once this concentration gradient force exceeds the voltage gradient counter-force so that the outside of the cell is less positive than the inside of the cell.
  • Propagation refers not simply to cell excitation but specifically to excitation that results from depolarizing current spreading from one cell to its neighbors. Electrical propagation may be described in terms of a source of depolarizing current and a sink of tissue that is to be depolarized. A source of current from excited cells flows into a sink of unexcited cells and provides a current to depolarize the unexcited cells to activation threshold.
  • a source is analogous to a bucket filled with electrical current
  • a sink is analogous to a separate bucket into which the source current is "poured.”
  • the sink bucket When the "level" of source current in the sink bucket reaches a threshold for activation, the sink bucket is excited and fills completely with current from its own ion channels. The sink bucket itself then becomes part of the source current.
  • the net depolarizing current is the inward/upward current as limited by the "leak” current or outward/downward current, which is analogous to a leak in the bottom of the sink bucket.
  • the safety factor is the amount by which source current may be reduced while maintaining successful propagation.
  • the increased capacitance of multiple sink cells connected via gap junctions is analogous to two or more sink buckets connected at their bases by tubes.
  • the intercellular resistance of the tubes influences the distribution of current poured into the first sink-bucket.
  • the majority of the current poured into the first bucket will contribute to raising the voltage level of that bucket, with only a small trickle of current flowing into the second bucket.
  • the rate of voltage change in the first and second buckets progressively equalizes. With sufficiently low intercellular resistance, the sink effectively doubles in size (and the amount of depolarization of each membrane is reduced by half).
  • the source-sink ratio is determined by the number of source cells and the number of sink cells to which they are connected. If the source amplitude is held constant while sink size is increased, the source-sink ratio is reduced. For example, when multiple sink cells are connected via gap junctions, source current is effectively diluted, reducing the source sink ratio. Outward currents competing with the source current also increase the sink size. As the source-sink ratio decreases, the rate of propagation (i.e., conduction velocity) also decreases because it takes longer for each cell to reach activation threshold.
  • a sufficiently low source-sink ratio i.e., a source-sink mismatch
  • the safety factor may diminish to less than zero, excitation may fail, and propagation may cease.
  • the physical arrangement of cells in a tissue influences this balance.
  • a structurally determined source-sink mismatch occurs when propagation proceeds from a narrower bundle of fibers to a broader band of tissue.
  • the narrower bundle of fibers provides a smaller source than the sink of the broader band of tissue to which it is connected.
  • the source-sink ratio is asymmetric.
  • this tissue structure may result in a uni-directional conduction block and is a potential mechanism for concealed accessory pathways, as described further below.
  • wavefront also influence the source-sink ratio.
  • source and sink are not balanced in a curved wavefront.
  • the source is smaller than the sink; therefore, convex wave-fronts conduct current more slowly than flat or concave wave-fronts.
  • the rate and reliability of excitation is proportional to wavefront curvature: as curvature increases, conduction velocity decreases until critical threshold resulting in propagation failure. This is the basis of fibrillation.
  • FIGS. 1 A-1C illustrate the relationship between the source-sink ratio and wave curvature according to some aspects of the current invention.
  • a flat wavefront maintain a balance between source 10 and sink 12
  • a convex wavefront have a smaller source 10 and a larger sink 12.
  • FIG. 1C illustrates a spiral wavefront with a curved leading edge, in which the curvature is progressively greater towards the spiral center.
  • the spiral wavefront in FIG. 1C has less curvature but faster conduction at location 14 than at location 16, where the wavefront has less curvature but faster conduction than at location 18.
  • the source is too small to excite the adjacent sink and, due to the source-sink mismatch, propagation fails, resulting in a core of unexcited and/or unexcitable tissue around which rotation occurs.
  • reentry While several mechanisms may contribute to cardiac fibrillation, by far the most conspicuous culprit in fibrillation is reentry.
  • the fundamental characteristic of reentry is that ongoing electrical activity results from continuous propagation, as opposed to repeated de novo focal impulse formation.
  • the general concept of reentry is straight-forward: waves of activation propagate in a closed loop returning to re-excite the cells within the reentry circuit. Because of the heart's refractory properties, a wave of excitation cannot simply reverse directions; reentry requires separate paths for conduction away from and back towards each site in the circuit.
  • circuit formation can be quite varied and in some cases quite complex.
  • a circuit is structurally defined in that physically separated conduction paths link to form a closed loop (resulting in, e.g., atrial flutter).
  • Circuits can also be composed of paths that are separated due to functional cell-cell dissociation (e.g., rotors, to be described further below).
  • reentry requires: (1) a closed loop of excitable tissue; (2) a conduction block around the circuit in one direction with successful conduction in the opposite direction; and (3) a conduction time around the circuit that is longer than the refractory period of any component of the circuit.
  • a region of tissue substrate may be described as a finite two- dimensional sheet of excitable cells. The edges of the sheet form a boundary, resulting in a bounded plane. If a wave of excitation traverses the plane, it will extinguish at its edges. However, if a disconnected region of unexcited and/or unexcitable cells within the plane, a closed loop may exist with the potential to support reentry provided the other criteria for reentry are met.
  • FIGS. 2A-2B illustrate reentry circuits using a topological perspective of the tissue substrate in accordance with some aspects of the present invention.
  • an uninterrupted, bounded plane of tissue substrate cannot support reentry.
  • the addition of a inner, disconnected region of unexcited and/or unexcitable cells 20 transforms the tissue substrate into an interrupted, bounded plane and a potential circuit for reentry.
  • topological approach One benefit of a topological approach is the generalizability with which it applies to the full range of possible circuits for reentry. Despite a myriad of potential constituents, all reentrant circuits may be modelled as interrupted, bounded planes. Another benefit of a topologic approach is the unification it confers on all treatments for reentry: circuit transection by any means results in termination. Topologically, all circuit transections constitute transformation back to an uninterrupted, bounded plane.
  • Reentry may be prevented in two ways: (1) increasing the tissue excitation
  • the embodiments of the present disclosure provides methods and systems for effectively and efficiently preventing reentry by the latter method of physically interrupting the circuits and, consequently, reducing the ability of a heart to perpetuate fibrillation.
  • a reentrant circuit may be transected physically, as with catheter ablation, or functionally, as with antiarrhythmic medications (which may, e.g., reduce tissue excitability and/or extend the refractory period). Either way, a circuit transection results when a continuous line of unexcited and/or unexcitable cells is created from a tissue edge to an inner boundary, and the interrupted, bounded plane is transformed into an uninterrupted, bounded plane.
  • FIGS. 3 A-3B illustrate circuit transection due to refractory prolongation.
  • FIG. 3 A if the trailing edge of refractory tissue 32 is extended in the direction of the arrow to meet the leading edge of excitation 30, such that the entire leading edge encounters unexcitable tissue ("head meets tail") then, in FIG. 3B, the propagation ends where the unexcitable tissue begins 36 and a line of conduction block 38 transects the circuit from inner to outer boundary.
  • Complex Reentrant Circuits Rotors and Multi-Wavelet Reentry
  • the self-perpetuating reentry properties of fibrillation are in part the result of cyclone-like rotating spiral waves of tissue excitation ("rotors").
  • a rotor is an example of a functional reentrant circuit that is created when source-sink relationships at the end of an electrical wave create a core of unexcited and/or unexcitable tissue (i.e., a rotor core) around which rotation occurs.
  • Activation waves propagate radially from the rotor core, producing a spiral wave that appears as rotation due to the radial propagation with progressive phase shift.
  • Rotors can occur even in homogeneous and fully excitable tissue in which, based on the timing and distribution of excitation, groups of cells in separate phases of refractoriness create separate paths which link to form a circuit.
  • the simplest rotors have spatially-fixed cores, whereas more complex rotors have cores that are more diffuse and meander throughout the tissue.
  • rotors encountering spatially-varying levels of refractoriness divide to form distinct daughter waves, resulting in multi-wavelet reentry.
  • wave curvature influences source-sink balance.
  • a rotor has a curved leading edge, in which curvature is progressively greater towards its spiral center of rotation. As curvature increases, conduction velocity decreases. At the spiral center the curvature is large enough to reduce the safety factor to less than zero, and propagation fails due to source-sink mismatch, creating a core of unexcited and/or unexcitable tissue (i.e., a sink) around which rotation occurs.
  • the wavelength at the inner most part of a rotor is shorter than the path length around the sink, its unexcited and/or unexcitable core is circular and/or a point. If the wavelength is longer than the path length, then the rotor may move laterally along its own refractory tail until it encounters excitable tissue at which point it can turn, thus producing an elongated core. If conduction velocity around its core is uniform, a rotor will remain fixed in space. Alternatively, if conduction velocity is greater in one part of rotation than another, the a rotor and its core will meander along the tissue substrate.
  • reentry may comprise multiple meandering and dividing spiral waves, some with wave lifespans lasting for less than a single rotation. Terminating and Preventing Reentrant Rhythms
  • the mechanism of reentry provides insight into the strategies that will result in its termination: If reentry requires closed circuits then prevention, minimization, and/or termination requires transection of these circuits. Transection can be achieved in several different ways. In the case of fixed anatomic circuits, the circuit simply be physically transected with, for example, a linear ablation lesion.
  • Another approach to transection is to prolong the tissue activation wavelength by increasing refractory period sufficiently that wavelength exceeds path-length (i.e., "head meets tail"), and the circuit is transected by a line of functional block. Increasing conduction velocity sufficiently would ultimately have the same effect but is not practical
  • antiarrhythmic agents are limited by the degree to which they decrease conduction velocity.
  • the antiarrhythmic approach to treating multi-wavelet reentry in atrial fibrillation may include: decreasing excitation (thereby increasing the minimum sustainable curvature, increasing core size, meander and core collision probability) or increasing action potential duration and thereby wavelength (again increasing the probability of core
  • FIGS. 4A-4F illustrate rotor termination resulting from circuit transection via core collision with a tissue boundary according to some aspects of the present invention.
  • the rotor core 40 moves closer to the tissue edge with each rotation 1-4, shown in FIGS. 4A-4D respectively.
  • FIG. 4E Upon collision of the core 40 with the tissue edge, as shown in FIG. 4E, the circuit is transected and reentry is terminated as shown in FIG. 4F.
  • Atrial remodeling promotes fibrillation by decreasing the boundary-length-to-surface-area ratio (chamber dilation (surface area) is greater than annular dilation (boundary length)) and by decreasing wavelength (conduction velocity is decreased and action potential duration is decreased).
  • the boundary- length-to-surface-area ratio can be increased by adding linear ablation lesions.
  • an ablation line In order to transect a rotor circuit, an ablation line must extend from the tissue edge to the rotor core. Focal ablation at the center of a rotor simply converts the functional block at its core into structural block; ablation transforms spiral wave reentry into fixed anatomic reentry.
  • FIGS. 5A-5C illustrates the rotor ablation requirement of a linear lesion from the rotor core to the tissue edge in accordance with some aspects of the present invention.
  • focal ablation 50 at a rotor core converts a functional circuit (i.e., spiral wave) into a structural circuit but does not eliminate reentry.
  • FIG. 5B illustrates how reentry continues if a linear lesion does not extend to the rotor core 52 (similar to a cavo-tricuspid isthmus ablation line that fails to extend all the way to the Eustachian ridge).
  • an ablation line 54 from the rotor core to the tissue edge transects the reentry circuit. Instead of circulating around its core the wave end travels along the ablation line 54 and ultimately terminates at the tissue edge.
  • Reentrant electrical rhythms persist by repeatedly looping back to re-excite or activate tissue in a cycle of perpetual propagation rather than by periodic de novo impulse formation. Due to its refractory properties, cardiac tissue activation cannot simply reverse directions. Instead, reentry rhythms or circuits require separate paths for departure from and return to each site, analogous to an electrical circuit. [0145] The components of these reentrant circuits can vary, the anatomic and physiologic constituents falling along a continuum from lower to higher spatiotemporal complexity.
  • circuits are composed of permanent anatomically-defined structures such as a region of scar tissue; however, circuit components may also be functional (i.e., resulting from emergent physiologic changes) and therefore transient, such as occurs when electrical dissociation between adjacent fibers allows formation of separate conduction paths.
  • FIGS 6A-6C illustrates these concepts using simulated patterns of cardiac tissue activity produced by a computational model.
  • the reentrant circuits illustrated in FIGS. 6A- 6C are of increasing complexity.
  • FIG. 6A illustrates spiral waves of a simple reentrant circuit around a structural inner-boundary region of non-conducting tissue 60 (i.e., a simple rotor with a spatially-fixed core of, e.g., scar tissue).
  • FIG. 6B illustrates spiral waves of a more complex reentrant circuit 62 that is free to travel the tissue (i.e., a rotor with a functionally- formed core).
  • Spiral waves are an example of functional reentrant substrate created when source-sink relationships at the spiral center create a core of unexcited and/or unexcitable tissue around which rotation occurs. This can occur even in homogeneous and fully excitable tissue in which, based on the timing and distribution of excitation, groups of cells in separate phases of refractoriness create the separate paths which link to form a circuit.
  • the simplest spiral-waves have spatially fixed cores as in FIG. 6A, whereas more complex examples have cores that meander throughout the tissue as in FIG. 6B.
  • spiral-waves encountering spatially varying refractoriness can divide to form distinct daughterwaves, resulting in multi-wavelet reentry.
  • FIG. 6C illustrates multi- wavelet reentry with, for example, daughterwaves 64, 66, and 68 (i.e., multiple rotors dividing to form daughter waves).
  • a rotor terminates when: (1) the rotor core (i.e., the center of the wave's rotation) collides with an electrical boundary in the atria, which physically interrupts the circuit of reentry; or (2) the tissue excitation wavelength is increased beyond the length of the circuit of reentry, thus physiologically interrupting the circuit of reentry (i.e., the circuit "interrupts itself as the leading edge of tissue excitation collides with the trailing edge of refractory tissue).
  • FIGS. 3 A and 3B illustrate how the minimum path of a rotor is limited by tissue excitation wavelength in accordance with some aspects of the present invention. In FIG.
  • the leading edge 401 of the tissue excitation wave does not overlap the trailing edge 402 of refractory tissue so the reentrant circuit is not interrupted.
  • the wavelength of the tissue excitation wave exceeds the length of the circuit of reentry: the leading edge 403 of the tissue excitation wave meets the trailing edge 404 of refractory tissue.
  • the cardiac tissue substrate for example, the left atrium
  • the cardiac tissue substrate may be viewed as a bounded and interrupted plane, which is capable of forming a reentrant circuit.
  • the annulus forms the edge or "outer" boundary of the plane, while the pulmonary veins form holes or discontinuities interrupting the plane.
  • a discontinuity is any place within the tissue across which current does not flow.
  • a discontinuity may be structural and/or functional.
  • tissue refractory properties or source-sink mismatch
  • a structurally uninterrupted plane may nonetheless be capable of forming a reentrant circuit around a functional inner discontinuity, such as a physiologic conduction block.
  • a heart may be described based upon its physical topology (defined by the geometrical structure of the tissue) and based upon its functional topology (defined by the physiologically possible paths of tissue activation).
  • topologically two surfaces are considered homomorphic (i.e., the same) if one surface can be transformed into the other surface by stretching, but not by cutting or pasting. All bounded surfaces with an inner-discontinuity may be considered homomorphic and functionally identical. Likewise, all bounded surfaces with an inner discontinuity may be considered homomorphic and functionally identical. From this perspective, a bounded surface with no inner discontinuity and a bounded surface with a discontinuity that is connected to a boundary (i.e., a tissue edge) are the same despite being of different shapes because one surface can be merely stretched to become the other surface.
  • a boundary i.e., a tissue edge
  • a structurally uninterrupted plane may nonetheless be capable of forming a circuit (around an inner-discontinuity to physiological conduction block).
  • Reentry requires a complete electrical circuit; disruption causes propagation to cease. If its circuit is disrupted, reentry is terminated, whether by prolongation of the tissue excitation wavelength beyond the circuit length or by physical interruption. As such, termination of fibrillation requires "breaking" each reentrant circuit.
  • tissue substrate from a bounded and interrupted plane (capable of reentry) to a bounded but uninterrupted plane.
  • a bounded but uninterrupted plane is functionally identical to a bounded plane in which the interruption is connected to the boundary.
  • the tissue substrate may become functionally identical to a bounded but uninterrupted surface and less or no longer capable of supporting reentry.
  • the tissue substrate may become functionally identical to a bounded but interrupted surface and less or no longer capable of supporting reentry.
  • FIGS. 7A-7C illustrate surface topology and reentry in accordance with some aspects of the present invention. More specifically, FIG. 7A illustrates a single wave 70 in an uninterrupted plane 72 with an outer boundary; FIG. 7B illustrates an interrupted place with a disconnected inner-boundary 74; and FIG. 7C illustrates a plane several time-steps after an ablation lesion 76 has connected the inner-boundary (e.g., the wave tip) to the tissue edge, thus eliminating the inner boundary.
  • the inner-boundary e.g., the wave tip
  • Cells were arranged in a two-dimensional grid, each cell connected to its four neighbours (up, down, left, and right) via electrically resistive pathways. Each cell had an intrinsic current trajectory (Im— equivalent to net transmembrane current) that followed a prescribed profile when the cell became excited. Excitation was elicited either when the current arriving from the four neighbouring cells accumulated sufficiently to raise the cell voltage (Vm— equivalent to transmembrane voltage) above a specified threshold or when the cell received sufficient external stimulation (pacing). Once excited, a cell remained refractory (i.e. non-excitable) until Vm repolarized to the excitation threshold. The duration of a cell's refractory period was thus determined by the duration of its action potential.
  • Im intrinsic current trajectory
  • Vm equivalent to transmembrane voltage
  • This computational model did not include all the known biophysical details of individual cardiac cells. Nevertheless, it did incorporate the key behavioural features of individual cells that are required to reproduce realistic global conduction behaviour. This behaviour included source-sink relationships with wave curvature-dependent conduction velocity and safety factor, and the potential for excitable but unexcited cells to exist at the core of a spiral-wave.
  • the computational model thus combined the computational expediency of cellular automata with the realism of much more complicated models that include processes at the level of the ion channel.
  • each voltage map was converted into a phase map by performing a Hilbert transform to generate an orthogonal phase-shifted signal from the original signal at each coordinate of the tissue space-time plot (x, y, t). From the original and phase-shifted signals, the phase at each coordinate at each time-step was calculated.
  • phase singularities were identified, and phase singularity sites were considered to represent a spiral wave tip if (1) all phases surrounded the singularity in sequence (from - ⁇ to ⁇ ) and (2) the phase singularity was located at the end of a leading edge of activation.
  • Space-time plots of the phase singularities were created to delineate wave-tip trajectory.
  • the total number of spiral -wave tips (measured during each time-step over the sampling interval) divided by the space-time volume was defined as the spiral-wave- tip density. Spiral waves were initiated by rapid pacing from two sites in close proximity with an offset in the timing of impulse delivery.
  • Spiral waves were spatially stable in the setting of homogeneous tissue (all cells identical) with a shorter wavelength than circuit length.
  • action potential duration was increased (wavelength > circuit length)
  • the spiral waves began to meander.
  • Multi -wavelet reentry resulted when action potential duration was randomized across the tissue.
  • a region with higher spiral-wave density resulted when a patch of tissue with shorter mean action potential duration was created.
  • the average duration of multi-wavelet reentry increased progressively as the boundary -length-to-surface-area ratio was decreased (average duration 2.2 ⁇ 1.7 x 10 3 time-steps at a ratio of 0.26; average duration 4.0 ⁇ 2.1 ⁇ 10 6 time-steps at a ratio of 0.125; simulations at the lowest ratio were truncated at 5.0 x 10 6 time-steps; only 2 of 10 simulations terminated within this time frame).
  • FIG. 8 illustrates the impact of boundary-length-to-surface-area ratio on the duration multi-wavelet reentry according to some aspects of the present invention. Keeping tissue area fixed (at 1,600 mm 2 ) the length and height were varied such that boundary -length-to- surface-area ratio decreased from top to bottom: 0.26, 0.2125, 0.145, and 0.125, respectively.
  • FIGS. 9A-9C illustrate how ablation lines increase the boundary-length-to-surface-area ratio and decrease the duration of multi-wavelet reentry in accordance with some aspects of the present invention.
  • zero ablation lines produced termination of multi-wavelet reentry 90 in 2.2 ⁇ 2.9 x 10 5 time-steps; in FIG. 9B, one ablation line 92 produced
  • FIG. 9C two ablation lines 94 and 96 produced termination of multi-wavelet reentry in 1.6 ⁇ 2.5 x 10 3 time-steps; in FIG. 9D, three ablation lines produced termination of multi-wavelet reentry in 575 ⁇ 67 time-steps.
  • the framework also helps to shed light on some controversial aspects of atrial fibrillation ablation. For example, there are numerous reports of improved outcome with addition (or sole use) of focal ablation that targets complex fractionated atrial electrograms. On the basis of the findings in this study, one would predict that focal ablation would create new potential reentrant circuits (unless lesions are continued to an atrial boundary). [0171] Ultimately, it is desirable to apply this topological analysis to individual patients to prospectively identify those requiring additional ablation lesions and to design optimal ablation strategies that are patient specific. This has not been possible prior to the present invention and its embodiments.
  • this approach was expanded based on the recognition that multi-wavelet reentry terminates when rotor cores collide with a tissue outer boundary and that collision is more likely as the ratio of tissue boundary to tissue area is increased (e.g., through addition of linear ablation lesions contiguous with the tissue edge). It was further recognized that when the distribution of rotor cores is concentrated in certain regions (based upon tissue physiology and architecture), the probability of collision is greatest when ablation lines are placed in the regions with higher rotor density.
  • CMA-ES Covariance Matrix Adaptation Evolutionary Strategy
  • the characteristics of the evolving ablation lesion sets were assessed with regard to their adherence to the principles outlined by the conceptual strategy, specifically: (1) the percent of lines that are contiguous with the tissue's outer boundary; and (2) the total contiguous tissue area (i.e., the amount of tissue not electrically isolated (quarantined) by enclosing ablation lesions).
  • ablation lines were evolved under at least one of two conditions: (1) "homogeneous” simulated tissue in which circuits were uniformly distributed (i.e., the control condition); and (2) "heterogeneous” simulated tissue containing a patch of tissue with a higher concentration of circuits then the remainder of the tissue.
  • a computational model was used to generate simulated two-dimensional tissue sheets, comprised of an array of (e.g., 60 ⁇ 60) "cells.” Each cell represents a large number of myocytes. The intercellular resistance was uniform in each direction and throughout the tissue (unless otherwise stated).
  • the action potential duration (and refractory period) of each cell varied randomly throughout the tissue with a mean of 100 ⁇ 25 ms.
  • the cells properties included restitution; action potential duration was rate-dependent (varying as a function of preceding diastolic interval). In homogeneous tissue the distribution of baseline action potential duration (prior to the effects of restitution) was randomly selected producing a relatively uniform concentration of circuits across the tissue when following induction of multi-wavelet reentry was induced.
  • the action potential duration of cells within a patch of tissue (20 ⁇ 20 cells located along the middle third of the tissue border) was set to vary about a mean of 50 ⁇ 25 ms.
  • the inter-cellular resistance within this patch was increased by 140% relative to the tissue outside the patch.
  • FIGS. 10A-10B illustrate the circuit density across simulated tissue in accordance with some aspects of the invention.
  • the distribution is homogenous; however, in FIG. 10B, the distribution is heterogeneous.
  • Multi -wavelet reentry was generated using cross field stimulation. In the baseline state the duration of induced multi-wavelet reentry is assessed, if termination occurred within the 2.5 second simulation the tissue is was rejected and a new tissue generated. This process was repeated until 10 acceptable test tissues were generated.
  • Circuits were identified by first converting the space-time plots of tissue voltage to phase maps using a Hilbert transform. Phase singularities were identified as sites at which (1) all phases meet at a single point and (2) phases are arranged in sequence from - ⁇ to ⁇ . In order to eliminate false positive phase singularities (those not identifying a rotor core), the leading edge of each wave was delineated (based upon initiation of AP upstroke). Phase singularities that were not located at the end of a wave-front were eliminated.
  • Evolutionary algorithms are biologically inspired solution-space search methods. In general such algorithms involve: (1) randomly creating a population of candidate solutions; (2) assessing the fitness of these solutions relative to a fitness function or criterion; (3) selecting at least one of fittest solutions; and (4) creating a new generation of candidate solutions through some process of varying the prior generation's selected solution(s). These steps are iterated resulting in progressive optimization of the solutions' fitness.
  • CMA-ES is one of many different types of evolutionary algorithms that may be appropriate for lesion optimization. CMA-ES is designed to optimize real valued functions of real-valued vectors. For example one might seek a real -valued vector z that minimizes y in the fitness function f.
  • the fitness function may be non-differentiable, non-linear and non-convex; CMA-ES treats the function as a black box.
  • z corresponds to a set of ablation lines and /is a fitness function designed to optimize the ability of those lines to terminate and preclude multi -wavelet reentry.
  • CMA-ES works by naturally following the contours of a co-evolving estimate of the surrounding fitness landscape in seeking to improve a single current solution estimate. Rather than maintaining a fixed population size as in many evolutionary algorithms, CMA-ES starts by assuming a multivariate normal distribution around a single randomly selected solution vector m with covariance C, which is initially assumed to be a diagonal matrix (i.e., uncorrected variables in solution space) with a pre-defined global standard deviation ⁇ . It then proceeds to co-evolve improved estimates of the solution (new mean m) and an improved estimate of the covariance matrix C of the variables in surrounding solution space, as follows.
  • a population cloud of ⁇ potential solutions is generated according to the current estimate of the multivariate normal distribution described by C around the solution vector m; (2) this population is then truncated to the best ⁇ solutions, where ⁇ is typically on the order of one half ⁇ ; (3) a fitness-weighted average of the remaining ⁇ solutions becomes the new m, thus reducing the population to only one candidate solution; and (4) the covariance matrix C is updated using local fitness landscape information based on the generational change in m (a rank 1 update), the most recent ⁇ samples of the solution space in the vicinity of m (a rank ⁇ update), and the length of evolution path of successive estimates of m.
  • the encoding defines how a real vector z maps to a solution, in this case a set of six ablation lines.
  • Ablation lines are represented by a vector of 24 real numbers bounded from [-
  • the successive pairs of values are interpreted as (x, y) Cartesian coordinates.
  • Each coordinate pair defines the endpoints of a single straight ablation line, so there are six lines for each ablation set. Any cell i that falls underneath an ablation line is set to "dead" (unexcitable) and has an infinite resistance with its neighbors. All potential solutions (m and the clouds of ⁇ potential solutions created each generation) are of this form.
  • Tissue activation frequency is defined as the mean activation frequency of all the cells: FR (4) where & is the number of activations of the rth cell, Nis the total number of cells, and Jis the number of seconds the tissue is simulated (2.5).
  • the units of FR are activations per second.
  • An FR of 1 means cells on average are activated once per second.
  • F is the mean activation frequency FR of ten training tissues.
  • Two constraints are imposed on the ablation sets: (1) the total number of ablated cells cannot exceed 20% of the tissue; and (2) no more than 18% of the tissue can be quarantined. Any ablation set that violates these constraints is eliminated and replaced until an ablation set that satisfies the constraints is produced.
  • Each lesion set was assigned characteristics, including percent of lesions contiguous with an outer boundary, percent quarantine, and boundary-length-to-surface-area ratio.
  • ablation lines enclose a region of the tissue the enclosed cells become electrically isolated from the remainder of the tissue, effectively reducing the tissue area.
  • the proportion of cells isolated by ablation is defined as pQ. If a tissue were ablated with a line extending from the top center of the tissue to the bottom center then pQ would equal 0.5.
  • pA be the proportion of cells that are ablated.
  • the contiguous electrically excitable tissue area ⁇ 4 is the total number of cells N minus the ablated cells, pA, and the quarantined cells, pQ.
  • FIG. 12A is a plot of ablation density versus circuit density for tissue without a high circuit density patch, in accordance with some aspects of the present invention. In contrast, the ablation density was the same in and outside of the top middle portion of the tissue in the homogeneous tissue experiments.
  • FIG. 12B is a plot of ablation density versus circuit density for tissue with a high circuit density patch, in accordance with some aspects of the present invention. Ablation density is markedly increased in the high circuit density region.
  • ablation amounts to manipulating the structure of a complex non-linear system so as to constrain its behavior. Even if we limit allowable manipulations to the placement of ablation lines, the number of possible solutions is vast and exhaustive search is intractable.
  • Fibrillogenicity is a measure of how conducive a patient's heart is to supporting fibrillation. A fibrillogenicity assessment allows a clinician to estimate the amount of ablation (e.g., the total length of ablation lesions) that will be required to treat and minimize fibrillation in a particular patient.
  • fibrillogenicity may be considered proportional to the ratio of surface area to boundary length of the tissue substrate.
  • Fibrillogenicity also may be considered inversely proportional to the tissue excitation wavelength ⁇ :
  • tissue excitation wavelength is the distance from the leading edge of a tissue excitation wavefront to its trailing edge of unexcitable refractory tissue.
  • fibrillogenicity may be considered proportional to the number of reentrant circuits the tissue is capable of supporting per unit area.
  • an assessment of a patient's fibrillogenicity should take into account measurements (even if only indirect indications are available) of the substrate surface area (e.g., the patient's atrial surface area), the total boundary length of the substrate (e.g., the patient's atrial boundary length), and the minimum substrate area required to support one reentrant circuit.
  • the minimum substrate area required to support one reentrant circuit informs the extent of electrical derangement in the tissue.
  • the measure of the area of tissue required to support an individual rotor is the minimum circuit area.
  • the tissue substrate as a whole becomes capable of supporting more rotors, and the probability that all circuits will be interrupted simultaneously and fibrillation will terminate. Thus, fibrillogenicity increases as the minimum circuit area decreases.
  • the determinants of minimum circuit area are multifactorial and many of the factors are emergent (i.e., the result of interactions between cell physiology, tissue anatomy, and the evolving circumstances of global and local activation states). While the minimum circuit area cannot be measured directly, the minimum circuit area is related, at least in part, to the tissue excitation wavelength.
  • Tissue excitation wavelength is not a single static parameter of tissue but a product of the conduction velocity of a wave and the refractory period (i.e., the amount of time required to recover excitability following excitation) of the tissue through which the wave is traveling. Both of these factors depend upon spatiotemporal context. For example, the refractory period of cardiac tissue varies with the frequency at which a given heart cell is excited. A given heart cell is excited at frequencies that tend to range from 4 to 15 Hz, particularly 5 to 10Hz. Meanwhile, the conduction velocity of a wave is influenced by wave shape: curved waves (e.g., rotors) conduct more slowly than flat waves. Hence, tissue excitation wavelength— and thus minimum circuit area— may vary over time and across the heart, even in an individual patient.
  • Electrocardiography may be used to gather measurements indicative of tissue excitation wavelength and thus minimum circuit area by recording the electrical activity of a patient's heart at the body surface.
  • An electrocardiograms (also a "ECG/EKG”) translates the electrical deflections or changes in the electrical potential produced by the contractions of a heart into graphical waveforms.
  • the ECG/EKG may show fibrillatory waves ("F-waves"), which are small, irregular, rapid deflections.
  • the wavelength of F-waves in a patient may be considered proportional to, and thus indicative of, tissue activation wavelength and minimum circuit area.
  • these measurements correlate with a patient's fibrillogenicity and, consequently, may be incorporated into the estimation of how much ablation is needed and/or whether an ablation procedure is complete.
  • Fibrillogenicity is also modulated by the total boundary length of the tissue substrate, which, for an atrium, is the sum of the circumferences of the atrial boundaries and orifices (e.g., the superior vena cava, inferior vena cava, atrioventricular tricuspid valve,
  • reentrant circuits terminate upon complete interruption.
  • a complete interruption requires the absence of a continuous path of excitable tissue at any point in the reentrant circuit.
  • a moving circuit may cause its own interruption when its core collides with a physical boundary.
  • the core of a moving circuit may interrupt the circuit itself by meandering into a tissue boundary or orifice.
  • the probability of such a collision increases with the total length of any boundaries. Therefore, total boundary length may be considered inversely proportional to fibrillogenicity.
  • FIG. 63A-63B are computer axial tomography scans of a human heart.
  • FIG. 63 A is a right atrium with boundary/orifice 631.
  • FIG. 63B is a left atrium having three
  • boundaries/orifices 632, 633, and 634 To calculate the total boundary length of the tissue substrate, add the sum of the circumferences of the atrial boundaries and orifices shown in FIGS. 63A and 63B. The total surface area is calculated by removing the area of the boundaries/orifices from the surface area of the tissue substrate.
  • a moving circuit may have more space to meander without its core colliding with a boundary and interrupting the circuit itself.
  • the probability of a such a collision decreases with an increase in total surface area. Therefore, total surface area may be considered directly proportional to fibrillogenicity.
  • boundary- length-to-surface-area may indicate (at least in part) an amount or length of boundaries (i.e., lesions) to be added and/or an amount of surface area to be removed, such that the final boundary-length-to-surface-area ratio favors collision and termination of fibrillation.
  • the boundary lengths and surface areas of the heart may be mapped onto and measured from, for example, a cardiac magnetic resonance imaging (MRI) scan, computed tomography (CT) scan, rotational angiogram, three-dimensional ultrasound image, three- dimensional electro-anatomic map, and/or other medical representation.
  • MRI cardiac magnetic resonance imaging
  • CT computed tomography
  • rotational angiogram three-dimensional ultrasound image
  • electro-anatomic map three-dimensional electro-anatomic map
  • the one or more representations may be used to measure and/or compute boundary lengths, the surface areas, and/or boundary-length-to-surface-area ratios.
  • the boundary-length-to-surface-area ratio provides a more complete indication of the tissue fibrillogenicity and informs the extent of ablation required to reduce fibrillogenicity and minimize or prevent further fibrillation. As described below, this information-combined with the density and distribution of circuit cores-may be used to assess and even quantify fibrillogenicity in accordance with some embodiments of the present invention.
  • FIG. 13 is a system component block diagram in accordance with certain
  • the system may include an ECG/EKG subsystem 501 for collecting measurements indicative of tissue activation wavelength (and minimum circuit area) and/or an imaging subsystem 502 for acquiring or collecting measurements indicative of a tissue substrate's total boundary length, total surface area, and/or boundary-length-to-surface-area ratio.
  • the system may also include, but is not limited to, a catheter subsystem 503, a processing unit 504, a memory 505, a transceiver 506 including one or more interfaces 507, a graphical user interface ("GUI”) 508, and/or a display 509 (each described in detail below).
  • GUI graphical user interface
  • the ECG/EKG subsystem 501 may be used to measure the heart's electrical activity (e.g., F-waves) as recorded at the body surface. These measurements correlate with the fibrillogenicity and, consequently, may be incorporated into the calculus for estimation of how much ablation needs to be performed (and, as described below, whether or not an ablation procedure is complete).
  • the ECG/EKG subsystem 501 may include a separate display and/or share a display 509 with other components of the system shown in FIG. 13.
  • the ECG/EKG subsystem 501 and its components may be operated manually and/or automatically.
  • the imaging subsystem 502 may include any means by which a medical
  • representation e.g., a two-dimensional image or three-dimensional model
  • a tissue substrate is acquired and/or generated, allowing the measurement of, for example, an atrium's surface area along with the veins and valves (i.e., boundaries) that interrupt its surface.
  • Suitable imaging modalities include, but are not limited to, MRI, CT, rotational angiography, three-dimensional ultrasound, and/or three-dimensional electro-anatomic mapping. Some imaging modalities may require the injection of one or more contrast agents.
  • the imaging subsystem 502 may include a separate display and/or share a display 509 with other components of the system shown in FIG. 5. The imaging subsystem 502 and its components may be operated manually and/or automatically.
  • FIG. 14 is a plot of simultaneous measurements of the atrial fibrillatory cycle length from surface ECG/EKG and the left and right atrial appendages according to some aspects of the present invention. Seiichiro Matsuo et al., "Clinical Predictors of Termination and Clinical Outcome of Catheter Ablation for Persistent Atrial Fibrillation," 54:9 J. of Am. College of Cardiology 788-95 (2009).
  • the cycle lengths from surface ECG/EKG, left atrial appendage (“LAA”), and right atrial appendage (“RAA”) were 139 ms, 144 ms, and 145 ms, respectively. Id.
  • electrogram-based ablation was performed at sites in the left atrium showing any of the following electrogram features: continuous electrical activity, complex rapid and fractionated electrograms, and a gradient of activation (a temporal gradient of at least 70 ms between the distal and proximal bipoles on the roving distal ablation electrode, potentially representing a local circuit).
  • Linear ablation in the left atrium was performed if atrial fibrillation persisted after electrogram-based ablation.
  • a roof line was performed joining the right and left superior pulmonary veins, and if atrial fibrillation continued, a mitral isthmus line from the mitral annulus to the left inferior pulmonary vein was performed. After restoration of sinus rhythm, assessment of conduction block across the lines was performed in all patients with supplementary ablation, if necessary, to achieve block.
  • a cavotricuspid isthmus line was performed in all patients with an end point of bidirectional block.
  • the procedural end point was termination of longlasting persistent atrial fibrillation by catheter ablation, either by conversion directly to sinus rhythm or via one or more atrial tachycardias, which were subsequently mapped and ablated.
  • atrial fibrillation was not terminated by ablation, it was terminated by electrical cardioversion. After cardioversion, if necessary, supplemental radiofrequency energy was delivered to establish pulmonary vein isolation and conduction block of any linear lesion.
  • Categorical variables were analyzed using the chi-square test or Fisher exact test.
  • univariate factors presenting p ⁇ 0.1 were analyzed using logistic regression (multivariate analysis).
  • the receiver-operator characteristic curve was determined to evaluate the performance of the best independent predictor of atrial fibrillation termination by catheter ablation. The optimal cutoff point was chosen as the combination with the highest sensitivity and specificity. All tests were 2-tailed, and p ⁇ 0.05 was considered significant. Cumulative event rates (recurrence of arrhythmia) were calculated according to the Kaplan-Meier method.
  • FIG. 15A is a plot showing the relationship between mean surface ECG/EKG atrial fibrillation cycle length measurement from 10 and 30 cycle lengths. Id.
  • FIG. 15B is a plot showing the relationship between surface ECG/EKG cycle length from 10 cycle lengths and atrial fibrillation cycle length using time frequency analysis. Id.
  • the mean surface ECG/EKG cycle length from 10 cycle lengths and LAA and RAA cycle length of the total population were 150 ⁇ 19 ms, 153 ⁇ 20 ms, and 157 ⁇ 20 ms, respectively.
  • the mean surface ECG/EKG cycle length was longer in patients taking amiodarone (163 ⁇ 18 ms vs. 146 ⁇ 16 ms, p ⁇ 0.0001).
  • the mean differences between the surface ECG/EKG cycle length from 10 cycle lengths and the endocardial cycle length in the LAA and RAA were 7 ⁇ 6 ms and 8 ⁇ 8 ms, respectively.
  • FIG. 15C is a plot showing the relationship between surface ECG/EKG atrial fibrillation cycle length from 10 cycle lengths and the LAA cycle lengths.
  • FIG. 15D is a plot showing the relationship between surface ECG/EKG atrial fibrillation cycle length from 10 cycle lengths and the RAA cycle length.
  • FIGS. 16A-16C are Bland-Altman plots in accordance with some aspects of the study and the present invention. Id. The plot in FIG. 16A shows good agreement between the RAA cycle lengths versus the cycle length from time frequency analysis. Id. The plot in FIG. 16B shows good agreement between the RAA cycle lengths versus the manual measurement surface ECG/EKG cycle length from 30 cycle lengths. Id. The plot in FIG. 16C shows good agreement between the RAA cycle lengths versus the manual measurement surface
  • ECG/EKG cycle length from 10 cycle lengths. Id. [0229] Long-lasting persistent atrial fibrillation was terminated by ablation in 76 of 90 patients (84%), with a mean procedure time of 245 ⁇ 70 min. Pre-procedural clinical variables were compared in patients in whom atrial fibrillation was terminated by ablation versus in those who were not. Compared with patients in whom atrial fibrillation was not terminated, patients with atrial fibrillation termination had a significantly shorter duration of continuous atrial fibrillation (22 ⁇ 24 months vs. 60 ⁇ 44 months, p ⁇ 0.0001), a longer surface ECG/EKG cycle length (154 ⁇ 17 ms vs. 132 ⁇ 10 ms, p ⁇ 0.0001), and a smaller left atrium dimension (47 ⁇ 7 mm vs. 54 ⁇ 11 mm, p ⁇ 0.01).
  • FIG. 17 is a plot showing the receiver-operator characteristic curve for the surface ECG/EKG cycle length as a predictor of termination of long-lasting persistent atrial fibrillation in accordance with some aspects of the invention.
  • a cutoff point of 142 ms of the cycle length had a specificity of 92.9%) and a sensitivity of 69.7% in predicting procedural termination of persistent atrial fibrillation.
  • the positive and negative predictive value of the cycle length 142 ms were 98.1%) and 36.1%, respectively, for procedural termination of persistent atrial fibrillation.
  • FIGS. 18A-18B are plots of Kaplan-Meier curve analyses in accordance with some aspects of the invention.
  • the plot in FIG. 18A shows a Kaplan-Meier curve analysis of the incidence of recurrent arrhythmia after the last procedure in patients with or without the cycle length from surface ECG/EKG > 142 ms.
  • the plot in FIG. 18A shows a Kaplan- Meier curve analysis of the incidence of recurrent arrhythmia after the last procedure in patients with or without the duration of persistent atrial fibrillation > 21 months. Id.
  • the surface ECG/EKG cycle length and the duration of continuous atrial fibrillation independently predicted clinical outcome of persistent atrial fibrillation ablation (p ⁇ 0.01 and p ⁇ 0.05, respectively).
  • the surface ECG/EKG cycle length was measured using a computer- based system that allows modification of gain and sweep speed. It is sometimes difficult to assess the cycle length on the surface ECG/EKG using conventional settings, and therefore multiple settings may be used to get unequivocal fibrillatory waves on the surface ECG/EKG.
  • the study was focused on identifying clinical factors that can be assessed before ablation; however, other potential predictors for atrial fibrillation recurrence after ablation, for example, intraoperative parameters including, but not limited to, procedural termination of long-lasting persistent atrial fibrillation.
  • the surface ECG/EKG cycle length independently predicts procedural termination of persistent atrial fibrillation, and both the surface ECG/EKG cycle length and the duration of continuous atrial fibrillation are predictive of clinical outcome.
  • the measurement of the surface ECG/EKG cycle length and the duration of continuous atrial fibrillation could help with patient selection for catheter ablation of long-lasting persistent atrial fibrillation.
  • Fibrillation detection and mapping is aimed at identifying the density and distribution of reentrant circuit cores that are responsible for the perpetuation of fibrillation.
  • electrogram signal frequency may indicate tissue activation frequency (provided the electrogram recording is of adequate spatial resolution), which is indicative of circuit core density and distribution.
  • tissue activation frequency provided the electrogram recording is of adequate spatial resolution
  • electrogram frequencies informs the optimal placement of ablation lesions to treat fibrillation.
  • the goal of ablation should be the interruption of all reentrant circuits.
  • a circuit core meandering on the tissue surface is interrupted if it collides with an electrical boundary.
  • one or more ablation lesions may be created to increase the boundary- length-to-surface-area ratio and, generically, the probability of collision.
  • the one or more ablation lesions should be placed contiguous with existing tissue boundaries to prevent or at least minimize the formation of a new circuit of reentry.
  • Tissue activation frequency is the frequency of the variation of tissue current, which rises and falls as tissue is excited. Tissue activation frequency may indicate a circuit core and a surrounding area of tissue in 1-to-l conduction continuity with that circuit.
  • a surrounding area of tissue undergoes excitation whenever a heart cell at one tissue site is excited or activated (e.g., by a reentrant circuit).
  • Two tissue sites do not have 1-to-l conduction continuity if some degree of conduction block prevents an excitation from traveling from one tissue site to the other..
  • All heart cells in a reentrant circuit path must have 1-to-l conduction continuity; otherwise, the circuit will be interrupted, and the rotor extinguished.
  • a patient may develop multi-wavelet reentry (i.e., wave break and new wave formation) if 1-to-l conduction continuity does not exist across the tissue.
  • tissue activation frequency identifies surrounding tissue with 1-to-l conduction continuity in addition to the actual tissue site of the circuit core, detection and mapping of tissue activation frequencies alone may not always accurately indicate circuit core density and distribution (i.e., tissue activation frequency is overinclusive). However, even so, knowledge of tissue activation frequencies may be applied to enhance the effectiveness and efficiency of ablation treatments.
  • tissue activation frequencies may vary over time as well as across the surface of a tissue substrate. For example, rotors and the refractoriness of a tissue area may shift (due, e.g., to autonomic tone), resulting in new conduction blocks and changing tissue activation frequencies across the tissue substrate.
  • tissue activation frequencies may be higher at actual tissue sites of circuit cores than in transient 1-to-l conduction continuity areas.
  • Electrogram signal frequency is the frequency of the variation of the net electric field potential at a recording electrode, as opposed to the frequency of the variation of tissue current.
  • An electrode is an electrical conductor.
  • one or more electrodes are designed to be positioned in a patient's heart.
  • the types of electrodes used in some embodiments of the present invention may be microelectrodes and may include, but are not limited to, solid conductors, such as discs and needles.
  • the one or more electrodes are deployed in proximity to cardiac tissue using one or more catheters, which may be inserted via thoracotomy at the time of surgery, percutaneously, and/or transvenously.
  • catheters which may be inserted via thoracotomy at the time of surgery, percutaneously, and/or transvenously.
  • An electric field potential recorded by an electrode is the electric potential energy o at the electrode location.
  • the net electric field potential recorded by an electrode is the sum of electric potentials from different sources at the electrode location.
  • a complex relationship exists between the net electric field potential at a tissue site and the possible current source distributions that produced that net electric field potential. While a net electric field potential at any tissue site surrounded by multiple spatially distributed current sources can be uniquely determined, the actual current source distribution that generated the net electric field potential at a recording electrode cannot be uniquely determined.
  • the use of electrogram recordings to reconstruct tissue electrical events may not always provide an accurate prediction of circuit core density and distribution.
  • an electrogram signal frequency map of a tissue substrate that identifies changes in electrogram signal frequency may be optimized to enhance the effectiveness and efficiency of ablation treatments as described below in accordance with some embodiments of the present invention.
  • Fractionated electrograms may be used as targets for ablation in atrial and ventricular arrhythmias. Fractionation has been demonstrated to result when there is repetitive or asynchronous activation of separate groups of cells within the recording region of a mapping electrode.
  • tissue activation patterns with increasing spatiotemporal variation were generated using a computer model.
  • Virtual electograms were calculated from electrodes with decreasing resolution.
  • electrogram fractionation was quantified.
  • unipolar electrograms were recorded during atrial fibrillation in 20 patients undergoing ablation.
  • the unipolar electrograms were used to construct bipolar electrograms with increasing inter- electrode spacing and quantified fractionation.
  • fractionation varied directly with electrode length, diameter, height, and inter-electrode spacing. When resolution was held constant, fractionation increased with increasing spatiotemporal variation. In the absence of spatial variation, fractionation was independent of resolution and proportional to excitation frequency. In patients with atrial fibrillation, fractionation increased as inter-electrode spacing increased.
  • a model was developed for distinguishing the roles of spatial and temporal electric variation and electrode resolution in producing electrogram fractionation.
  • Spatial resolution affects fractionation attributable to spatiotemporal variation but not temporal variation alone.
  • Electrogram fractionation was directly proportional to spatiotemporal variation and inversely proportional to spatial resolution. Spatial resolution limits the ability to distinguish highfrequency excitation from overcounting.
  • complex fractionated atrial electrogram detection varies with spatial resolution. Electrode resolution must therefore be considered when interpreting and comparing studies of fractionation.
  • Fractionated electrograms have attracted the attention of clinical electrophysiologists in the setting of mapping reentrant rhythms (eg, ventricular and atrial tachycardia) and more recently mapping of atrial fibrillation.
  • Fractionation in these settings is felt to identify substrate relevant to the arrhythmia circuitry. Although fractionation can identify a critical isthmus in scar-based reentrant ventricular tachycardia circuits, the use of fractionated electrograms to guide atrial fibrillation ablation has had conflicting results.
  • Electrograms measure the changing potential field at the site of a recording electrode. Any pattern of tissue activation within the recording region of an electrode that results in alternation between increasing and decreasing potential will produce electrogram fractionation.
  • tissue activation patterns include meandering rotors, wave collision,
  • Activation was examined in a two-dimensional sheet of electrically excitable tissue using a computer model.
  • the surrounding potential field produced by tissue excitation was calculated.
  • the model was used to independently vary the temporal and spatiotemporal complexity of tissue excitation. By recording from virtual electrodes of varied size, configuration, and height, the impact of spatial resolution on fractionation was quantified.
  • the model was a monodomain cellular automaton, in which the cells are arranged in a two-dimensional grid with each cell connected to its four neighbors (up, down, left, and right).
  • Cell voltage changes in response to an action potential, external stimulation, or intercellular current flow.
  • the membrane voltage of a cell corresponds to its level of electrical depolarization.
  • the resting state of a cell corresponds to quiescence.
  • Action potential upstroke velocity and action potential duration are rate- and voltage-dependent.
  • Cells connect to their immediate neighbors through electrically resistive pathways.
  • the vertical and horizontal resistive constants are Rv and Rh, respectively.
  • Cells exchange current with their neighbors according to first-order kinetics, whereby the voltage of a quiescent cell (j, k) at time t is affected by that of its neighbors according to the following equation:
  • spatiotemporal complexity can be increased by increasing the number of parallel lines of scar, that is, increasing the number of separate tissue bundles through which excitation spreads.
  • FIGS. 19A-19F illustrate temporal, spatial, and spatiotemporal variation of tissue excitation in accordance with some aspects of present invention.
  • FIGS. 19A-19C illustrate tissue voltage distribution (single time step; 1010 mm).
  • FIG. 19A illustrates temporal variation, in which stimulation of the top row of cells (cycle length 150 ms) produced sequential planar waves of excitation.
  • FIG. 19B illustrates spatial variation. Although tissue is divided by multiple alternating linear scars 190 and 192, activation proceeds from top to bottom in parallel (secondary to simultaneous stimulation of the top row of cells).
  • FIG. 19C illustrates spatiotemporal variation.
  • FIGS. 19D-19F are corresponding virtual unipolar electrograms (electrode diameter 1 mm, height 0.5 mm, length 6 mm, and horizontal orientation) in accordance with aspects of the present invention. Note that even with linear scars, if activation occurs simultaneously in all bundles, the electrogram is very similar to that seen with in tissue without scars. To visualize this, compare FIGS. 19D and 19E. The contributions of each bundle to the potential field occur simultaneously and are hence superimposed in the electrogram (no fractionation).
  • the transmembrane current at a particular cell was defined as the time derivative of voltage (V), approximated as the difference in V between successive time steps: where j and k are position indices in the x and y directions.
  • FIG. 20 illustrates electrode geometry, spacing, and position according to some aspects of the study and the present invention.
  • three-dimensional cylindrical electrodes 200 with varied length 202, diameter 204, and height 206 were modeled.
  • the electrodes were modeled as hollow cylinders divided into a finite element mesh with elements evenly distributed about the circumference and along the length 202 of the electrode.
  • the number of elements varied depending on electrode geometry so no element area was 1 mm 2 .
  • the electric potential contribution from each cell was calculated at the center of each element.
  • the potential recorded by the entire unipolar electrode was then calculated as the sum of each element potential multiplied by the element area and divided by the total surface area of the electrode.
  • the bipolar electrogram was obtained simply as the difference in the potentials recorded by the two unipolar electrodes. Height 206 was measured from the tissue to the electrode's bottom edge and, for bipolar recording, inter-electrode spacing 208 was measured between edges. Electrodes were positioned over the center of the tissue (perpendicular to lines of scar— unipolar; parallel to lines of scar— bipolar recordings). Electrode spatial resolution varies inversely with electrode surface area (length and diameter), height above tissue, and inter-electrode spacing (for bipolar recordings).
  • the cellular automaton model evolved through discrete time steps; as a result, electrogram amplitude fluctuated from time step to time step.
  • the electrogram signal was therefore processed with a smoothing function to reduce this artifact.
  • the number of turning points was quantified as the number of peaks and troughs with a 10% tolerance.
  • Bipolar signals were exported for offline analysis. From these we constructed bipolar electrograms with increasing inter-electrode spacing (electrodes 1-2, 1-3, and 1-4). Bipolar signals were analyzed using standard algorithms for average interpotential interval (AIPI) and interval confidence level (ICL). The voltage window for ICL was 0.05 to 0.2 mV; the upper limit of 0.2 mV was selected as an average of values used by different groups. The amplitude of electromagnetic noise in each signal was measured in 10 patients (during sinus rhythm).
  • AIPI average interpotential interval
  • ICL interval confidence level
  • a mixed effects linear model was used for the analysis of the experimental data for studying fractionation as a function of inter-electrode spacing. Data for each catheter type and each outcome (ICL and AIPI) were analyzed separately. Subjects within a catheter type were treated as random effects, thereby inducing a compound-symmetrical correlation structure among withinsubject measurements. Measurements between subjects were independent, inter-electrode spacing and time of measurement were treated as fixed effects with time of measurement nested within subject. Analysis was done using PROC MIXED in SAS, Version 9.3.
  • FIG. 21 A is a graph illustrating fractionation as a function temporal variation by the number of deflections versus stimulus cycle length according to some aspects of the study and the present invention.
  • the underlying data corresponds to electrode length 2, 4, 6, and 8 mm (with fixed diameter 1 mm, height 0.5 mm).
  • 21B is a series of virtual unipolar electrograms from tissue excited at decreasing cycle lengths: cycle length 150 ms (top) to 75 ms (bottom), recorded with a unipolar electrode of 2 mm (left) and 8 mm (right) in length. The number of deflections is independent of electrode size.
  • Results showed the impact of electrode spatial resolution in tissue with temporal variation on fractionation. With temporal variation alone, fractionation was independent of electrode spatial resolution, as shown in FIGS. 21 A-21B, in accordance with some embodiments of the present invention.
  • the number of deflections in the unipolar electrogram was independent of electrode length, diameter, or height (15 deflections for electrode length 2, 4, 6, and 8 mm; diameter 1, 2, 3, and 4 mm; height 0.5, 1, 2, and 3 mm).
  • results showed that fractionation is a function spatiotemporal variation.
  • tissue was stimulated at a fixed cycle length of 150 ms from the upper left corner resulting in a "zig-zag" activation pattern.
  • fractionation was directly proportional to the number of linear scars (i.e., spatiotemporal complexity); the number of deflections was 19, 26, 45, and 52 for tissue with
  • FIG. 22A is a graph of number of deflections in unipolar recordings as a function of spatiotemporal variation (number of scars) and electrode resolution (length; diameter 1 mm, height 0.5 mm).
  • FIG. 22B is a series of virtual electrograms from tissue stimulated every 150 ms with increasing spatiotemporal variation (1 scar [top] to 6 scars [bottom]) recorded with a unipolar electrode (length 2 mm [left] and 8 mm [right]). The number of deflections increases with decreased electrode resolution (and the effect is more prominent as the number of scars increases).
  • Results showed the impact of electrode spatial resolution in tissue with spatiotemporal variation on fractionation.
  • the number of turning points increased in proportion to unipolar length (diameter 1 mm and height 0.5 mm) and number of linear scars.
  • the number of deflections was proportional to electrode diameter: 52, 66, 74, and 76 deflections for electrodes of 1-, 2-, 3-, and 4-mm diameter, respectively (length 6 mm and height 1 mm).
  • the number of deflections was directly proportional to electrode height: 52, 68, 76, and 84 deflections at heights of 0.5, 1, 2, and 3 mm above the tissue, respectively.
  • Fractionation also increased with increasing inter-electrode spacing: 22, 24, 32, and 33 deflections for inter-electrode spacing 1, 3, 5, and 7 mm, respectively (1-mm length and diameter, 0.5-mm height).
  • FIG. 23 A is a fluoroscopic image of 10-pole catheter 230 in the coronary sinus (electrode length 2 mm, inter-electrode spacing 2-5-2 mm). Brackets indicate inter-electrode spacings used for reconstruction of bipolar recordings.
  • FIG. 23B is afluoroscopic image of 20-pole catheter 232 (electrode length 1 mm, inter-electrode spacing 1-3-1 mm).
  • FIG. 23C is a set of simultaneous electrogram recordings during sinus rhythm and atrial fibrillation with inter-electrode spacing of 1, 5, and 7 mm. There is a minor increase in baseline noise as inter-electrode spacing increases (sinus rhythm) and increased fractionation with increased inter-electrode spacing (atrial fibrillation).
  • ICL 10-pole catheter 5.2 ⁇ 1.0, 8.7 ⁇ 1.0, and 9.5 ⁇ 1.0 for 2, 9, and 13 mm inter-electrode spacing, respectively (P ⁇ 0.001, 2 versus 9 and 2 versus 13 mm);
  • AIPI confidence level 6.8 ⁇ 1.0, 9.9 ⁇ 1.0, and 10.3 ⁇ 1.0 for 1, 5, and 7 mm inter-electrode spacing, respectively (P ⁇ 0.001, 1 versus 5 mm and 1 versus 7 mm).
  • AIPI decreased with increased inter-electrode spacing— 10-pole catheter: 207 ⁇ 19, 116 ⁇ 19, and
  • Electrogram fractionation is generally defined as low-amplitude, high-frequency deflections. As the number of sites contributing to an electrode's potential increases, the number of deflections will increase so long as these sites are excited asynchronously. When sites are excited simultaneously, their impact on the electrogram amplitude is additive but fractionation does not result.
  • Electrogram fractionation results from the interaction of 3 components: tissue temporal variation, tissue spatiotemporal variation, and electrode spatial resolution. In the absence of tissue spatiotemporal variation (ie, temporal variation alone), fractionation is independent of electrode spatial resolution. In a computer model of electrically excitable tissue with spatiotemporal variation and in patients with atrial fibrillation, fractionation increased with decreasing electrode spatial resolution. Electrograms measure the average potential field at the surface of an electrode over time. As a consequence, multiple different patterns of tissue activation can generate similar electrograms. Analysis of a single fractionated electrogram does not permit differentiation of temporal versus spatiotemporal tissue variation; therefore, one cannot distinguish highfrequency excitation from
  • Electrode spatial resolution must be considered when comparing studies of fractionation.
  • FIG. 24 is a schematic of a dipole current source located at ⁇ ⁇ /2 about the origin and a bipolar pair of electrodes of diameter d and height 1 separated by ⁇ and located at height zo along the y-axis.
  • FIG. 24 An in-vitro apparatus was created for confirming that commonly used clinical intracardiac electrodes do, in fact, record potentials as our model predicts.
  • a Plexiglas chamber was filled with 0.9% saline.
  • Two 0.3-mm wide copper wires with flat ends were fixed 0.5-mm apart (center to center) into the bath (the x-y plane shown in Fig. 24) with only their tips exposed to the bath interior.
  • Biphasic square wave impulses (2.4mV, 10-ms pulse width) were delivered to the electrodes to simulate a dipole source in the heart tissue.
  • Recording electrodes (both unipolar and bipolar) were also placed in the saline bath and positioned with a micromanipulator attached to a machined aluminum base under the bath. The electrode positions could be adjusted with a resolution of ⁇ 0.1mm over 10 cm.
  • the electrograms from the recording electrodes were sampled at 1 kHz and filtered from 0.5 to 250 Hz (available from Bard EP (Lowell, MA)). Ten recordings were taken using each electrode configuration at 10 positions along the y-axis at intervals of 0.2 mm. The entire set of recordings was repeated five times, with the order of catheter positions reversed (and electrodes polished) between runs to minimize effects due to electroplating of the cathode. Signals were exported and analyzed offline with the use of MATLAB®-based software.
  • Figures 25 A-25B are unipolar and bipolar space domain electrograms calculated with the computational model and measured in the physical in-vitro model.
  • Unipolar electrodes with tips having lengths of 1, 4, and 8mm (2.33-mm diameter) were examined, and correlation coefficients were found of 0.99, 0.99, and 0.97, respectively, between the computed and measured electrograms.
  • Bipolar recordings with inter-electrode spacings of 1, 2, 3, and 4mm (2.33-mm tip diameter) were examined, and correlation coefficients of 0.99 were found in all cases.
  • FIG. 26A is a plot of the potential due to a dipole current source recorded by a unipolar electrode as a function of lateral distance from the source, showing how resolution is quantified in terms of peak width at half maximum height W1/2.
  • FIG. 26B is the corresponding plot for a bipolar electrode.
  • ⁇ o(y,zo) was defined as the electrogram measured when the dipole sources are separated by a distance of zero (i.e. equivalent to a single dipole source)
  • OAy(y,zo) was defined as the electrogram measured when the sources are separated by some finite distance Ay.
  • the cross correlation between ⁇ o(y,zo) and OA y (y,zo) has a relatively low maximum value because the two signals are dissimilar in shape.
  • the nominal measure of resolution was selected to be the value of Ay for which the maximum in the cross correlation between ⁇ o(y,zo) and OAy(y,zo) achieves its minimum value. This is defined as Cmin.
  • FIGS. 28A-28C are plots illustrating how the two measures of spatial resolution, W1/2
  • Figs. 28A-28C Resolution of a unipolar electrode recording of a dipole current source as assessed in terms of Cmin (solid lines) and Wl/2 (dashed lines). The three plots show dependence of resolution on electrode diameter (d), length (1), and height above the tissue
  • Figure 29A-29D are corresponding plots for bipolar electrode recordings, including showing the effects of changing the distance D between the two electrodes of a bipolar pair (Fig. 1).
  • a layer of endothelial cells that adds to the distance between the active tissue and the closet approach of an electrode tip.
  • Figs. 26A-26B Resolution of a bipolar electrode recording of a dipole current source as assessed in terms of Cmin (solid lines) and Wl/2 (dashed lines). The four plots show dependence of resolution on electrode diameter (d), length (1), separation (D), and height above the tissue (zO).
  • Electrodes width, height, separation (in the case of bipolar), and distance from the tissue are increased.
  • Changes in electrode height had the greatest impact on spatial resolution, however, implying that the most important aspect of electrode design is not related to the electrode itself, but rather to the physical proximity of the electrode to the tissue.
  • the spatial resolution of intracardiac electrode recordings can be diminished: the amount of tissue that is 'near field' [i.e. immediately beneath the electrode(s)] can be increased, and/or the ratio of near-field to far-field tissue can be diminished.
  • An increased electrode diameter results in an effective increase of the electrode's footprint over the myocardial surface, thereby increasing the amount of tissue contributing to the near-field signal.
  • a computational model was created and validated for evaluating the impact of electrode size, shape, inter-electrode spacing, and height above the tissue on spatial resolution.
  • Two independent metrics were used to quantify spatial resolution, both indicating that spatial resolution becomes degraded roughly in proportion to the above four factors. Electrode height above the tissue has the greatest effect on spatial resolution, so electrode tissue contact is the most important factor impacting resolution.
  • Electrode height above the tissue has the greatest effect on spatial resolution, so electrode tissue contact is the most important factor impacting resolution.
  • the accuracy of any electrogram signal frequency analysis is a function of the ratio between electrode spatial resolution and tissue spatiotemporal variation.
  • the voltage (i.e., the electric potential difference) of an electrogram rises and falls with the net electric field potential at the recording electrode, and the electrogram signal frequency is simply a measure of the frequency of those variations in voltage. Any factor that influences the voltage will also influence the electrogram signal frequency. Because the magnitude of an electric field potential decreases with radial distance from its current source, the net electric field potential at a recording electrode will be dominated by nearby current sources. Effectively, only a limited region of tissue in the vicinity of a recording electrode substantively contributes to the net electric field potential recorded by that electrode. The spatial extent of such an electrode recording region is the spatial resolution of that electrode.
  • spatiotemporal variation (caused by, for example, heart cells whose excitations are dissociated and hence out of phase from each other) between current sources within an electrode recording region may produce a deflection in the electrogram recording.
  • a deflection results in an electrogram signal frequency that is higher than the tissue activation frequency of any individual cell within the electrode recording region.
  • an attempt to determine the maximum tissue activation frequency of individual cells may be inaccurate in the presence of spatiotemporal variation within the electrode recording region.
  • the accuracy with which an electrogram signal frequency indicates the tissue activation frequency of individual cells within the recording region is a function of the ratio between the spatial resolution of the recording electrode and the spatiotemporal variation of the tissue.
  • the electrogram signal frequency becomes the same as the tissue activation frequency in the recording region.
  • This "threshold" spatial resolution and/or higher spatial resolutions accurately reflect tissue activation frequency without over-counting. Therefore, the correlation between electrogram signal frequency and tissue activation frequency (and thus circuit density and distribution) increases as the spatial resolution of the recording electrode increases (i.e., includes fewer cells that are dssynchronously activated); and the optimal spatial resolution is close to the threshold where dssynchronously activated cells are eliminated.
  • the threshold spatial resolution is different for each patient (and at different locations in each patient's heart).
  • the threshold spatial resolution may be found by iteratively employing recording electrodes with higher spatial resolutions until dssynchronously activated cells are eliminated from the recording region.
  • electrogram signal frequency will change if dyssynchrony remains within the recording region.
  • the spatial resolution at which electrogram signal frequency no longer changes may be considered an accuracy -promoting spatial resolution threshold for a particular recording region.
  • FIG. 13 is a system component diagram in accordance with some embodiments of a system for identifying an optimal spatial resolution for local tissue with spatiotemporal variation.
  • the system may include, but is not limited to, an imaging subsystem 131
  • the system may also include a processing unit 135, a memory 134, a transceiver 133 including one or more interfaces 139, a GUI 138, and/or a display 136 (each described in detail below).
  • the catheter subsystem 132 includes one or more catheters according to some embodiments of the present invention.
  • the catheter subsystem 132 also may include, but is not limited to, one or more puncture or surgical devices for accessing a patient's vasculature and/or heart, one or more sheaths with one or more valves for preventing flowback, a saline solution for flushing components of the subsystem, one or more guidewires for positioning the one or more catheters, and/or one or more contrast agents (used in combination with an appropriate imaging subsystem 131) for viewing the tissue during use.
  • the catheter subsystem 132 may include a separate display and/or share a display 136 with other components of the system shown in FIG. 13.
  • the catheter subsystem 132 and its components may be operated manually and/or automatically.
  • the catheter subsystem 132 also may include, but is not limited to, one or more electrode localization technologies, such as triangulati on-based localization, radio-frequency -based localization (e.g., the CARTOTM XP System, which is available from Biosense Webster® (Diamond Bar, CA)), and/or impedance-based localization (e.g., the EnSite NavXTM Navigation & Visualization
  • electrode localization technologies such as triangulati on-based localization, radio-frequency -based localization (e.g., the CARTOTM XP System, which is available from Biosense Webster® (Diamond Bar, CA)), and/or impedance-based localization (e.g., the EnSite NavXTM Navigation & Visualization
  • FIG. 30 is a process flowchart for identifying an optimal spatial resolution for local tissue with spatiotemporal variation in accordance with some embodiments of the present invention.
  • step 301 an electrogram recording is acquired for a particular tissue location using an electrode with an initial spatial resolution.
  • step 302 the frequency of the electrogram signal is calculated and stored.
  • step 303 another electrogram recording is acquired using an electrode with a spatial resolution that is higher than that of the previous electrode.
  • step 304 the frequency of the electrogram signal is calculated and, in step 305, compared to the frequency of the previous electrogram signal. If the frequency has changed, the process returns to step 303 using an electrode with a spatial resolution that is even higher yet.
  • the frequency must change substantially to return to step 303; while in other embodiments, any change in the frequency requires returning to step 303. If the frequency has not changed, the spatial resolution is identified in step 306 as a minimum threshold for and/or optimal spatial resolution. In some embodiments, the frequency must not change at all to identify the optimal spatial resolution; while in other embodiments, a small change in the frequency is not considered in identifying the optimal spatial resolution.
  • Spatial resolution is influenced by electrode location, size, and configuration. More specifically, spatial resolution can be improved by the following: (1) moving the electrode closer in proximity to the tissue surface (i.e., the current source); (2) reducing the size of the electrode itself; and (3) using a bipolar electrode configuration (or another means of producing spatial differentiation).
  • the electrode configuration is not limited to only two electrodes, but may include more than two electrodes, and the differences between the electric field potentials may still be calculated.
  • FIGS. 31A and 3 IB illustrates an example of a contact bipolar electrode configuration.
  • Catheter 313 has two electrodes 314, both of which are close enough to tissue surface 315 to record a signal.
  • intracardiac electrodes are used to measure electrical activity within the heart.
  • Unipolar electrodes are the simplest configuration, with one recording electrode within the heart and another at a relatively long distance away. Unipolar electrodes are adequate but have a tendency to include far field electrical activity in the recorded signal which can result in a fractionated electrogram. This is a particularly relevant when trying to map complex arrhythmias (e.g. cardiac fibrillation) and accurately identifying local activation time.
  • Bipole electrode configurations ameliorate this problem by placing both electrodes within the heart at a relatively narrow distance apart. Since both electodes "see"
  • bipole electrodes There are, however, at least two limitations of bipole electrodes. First, the recorded electrical potential of bipole electrodes vary with their orientation relative to the direction of a passing wavefront. Second, because bipole electrodes have both electodes on the heart surface, there is potential inclusion of distinctly different electrical activity from each electrode. In view of these limitations, it was hypothesized that bipolar electrodes oriented perpendicular to the tissue plane (orthogonal close unipolar (OCU)) retain the superior near/far-field discrimination of common bipolar electrode recordings with the directional independence and smaller footprint of unipolar recordings. A series of in silico and in vivo experiments were performed to test the potential utility of this hypothesis.
  • OFCU orthogonal close unipolar
  • Electrodes were modeled as cylinders with the same dimensions as those used in the in vivo experiments (1-mm length, 2- mm diameter, 4-mm spacing).
  • FIG. 32 illustrates the collection of electrograms in accordance with some aspects of the study. Electrograms were recorded in a plane of a height (1 mm) above the dipole moment using electrodes 320 with length (1 mm) diameter 324 (2 mm). To assess the effect of wavefront direction, electrode bipoles with inter-electrode distance 236 were oriented parallel, perpendicular, and orthogonal to the dipole moment. Measurements were made with the electrode bipoles directly over the dipole, and at increments (0.1 mm) up to a determined distance (10 mm) from the dipole in direction 327.
  • FIG. 33 illustrates the collection of electrograms in accordance with some aspects of the study. Near field dipole is at the origin, and far field dipole 1mm along the x axis.
  • Electrode potential is measured as the electrodes move along the y axis.
  • Common bipolar and OCU electrograms were recorded from two dipoles to assess near- and far-field discrimination. A first dipole was the near field signal, and a second dipole was the far field signal. Measurements were made with the electrode bipoles directly over the first dipole, and at increments (0.1mm) up to a determined distance (10 mm) from the second dipole in direction 327.
  • a cellular automaton model was used to create a two-dimensional plane of tissue (60 ⁇ 60 cells).
  • Two layers of evenly spaced electrodes with standard electrode dimensions (1-mm length and 2-mm diameter) were positioned in an array (10 ⁇ 10 electrodes) over the tissue surface.
  • the electrode array was used to record electrograms in bipolar, OCU, and unipolar orientations. The mean dominant frequency of the recorded electrograms from the different array types was compared with the mean dominant frequency of the tissue directly underneath the electrodes.
  • Electrogram recordings with standard catheters (2mm electrode tip) were made in 5 swine hearts. Recordings were made with a Bard recording system. Catheters were held in place by a spacer that allowed simultaneous recordings of CBP and OCU electrograms with a fixed inter-electrode spacing of 4mm.
  • Electrograms were analyzed offline. MATLAB®-based software was used to measure the amplitude of electrical signals. Groups of values were compared with a Student's t-test.
  • FIG. 34 graphically illustrates near fields spatial electrograms from a model, in accordance with embodiments of the present invention.
  • FIG. 35 graphically illustrates far field spatial electrograms from a model, in accordance with embodiments of the present invention.
  • FIG. 36 illustrates graphically electrical potential recordings at a single electrode, in a model, in accordance with embodiments of the present invention.
  • FIG. 37 graphically illustrates membrane voltage underneath a single electrode, in a model, in accordance with embodiments of the present invention;
  • the average tissue DF was 10.43 +/- 1.44 Hz.
  • the average UNI electrode array recording DF was 9.53 +/- 0.94 Hz.
  • the average BP electrode array recording DF was 10.84 +/- 1.45 Hz.
  • the average OCU electrode array recording DF was 10.33 +/- 1.36 Hz.
  • OCU electrode type
  • OCU electrodes appeared to be superior in part because of the smaller effective electrode footprint compared with that of conventional electrodes. This may explain partially the improved tissue accuracy of the OCU electrode arrays. With complex moving wavefronts, the CBP electrodes can be influenced by independent electrical events that can lead to erroneous estimates of the frequency of repetitive wavefronts within the tissue as a function of time. [0321] OCU electrodes are superior compared with that of CBP electrodes with respect to the ability to resolve near and far field activity. Geometry and relationship of the electrodes to the near and far field sources provide for the improved electrodes. These results are consistent with this in both the FEM model and our animal preparations.
  • OCU electrodes are promising. For mapping complex arrhythmias and atrial fibrillation in particular arrays of OCU electrodes with the spatial resolution and spatial sampling required to more accurately discern tissue electrical activity may lead to more effective ablation procedures. A benefit of such arrays is that they can maintain the OCU electrodes orthogonality relative to the tissue surface, a key determinant of their effectiveness. OCU electrodes may also bear fruit in other fields that require sensors for electromagnetic fields.
  • OCU electrogram recordings are superior to CBP recordings in differentiating near field from far field activity ( ⁇ 50% decrease in the ratio of far and near-field signals) and retaining the wavefront independence of UP electrodes. Furthermore, OCU recordings are more accurate than those obtained with conventional electrodes in delineating tissue frequency. It appears likely that deployed in arrays of electrodes, OCU electrodes will yield electrogam recordings that may be particularly helpful in mapping complex arrhythmias and lead to more effective ablation procedures.
  • one or more electrodes are put in proximity to the cardiac tissue surface using one or more catheters.
  • Existing catheters and electrode configurations used to assist in diagnosis and treatment of fibrillation have several shortcomings for these purposes, including: (1) the inter-electrode spacing is too great; (2) the electrodes are too large; and (3) the electrode configurations are not suitably orthogonal to the tissue surface.
  • a pair of electrodes on catheter 801 are configured to be: (1) “orthogonal”; (2) “close”; and (3) “unipolar” (i.e., an "OCU” electrode configuration).
  • the inter-electrode axis from index electrode 382 to indifferent electrode 383 is "orthogonal" to the tissue surface 384.
  • Existing catheters and electrode configurations are not designed to be suitably orthogonal to the tissue surface.
  • catheter 39 illustrates the difference between two curvilinear catheters in contact with tissue surface 391, where catheter 392 has a pair of electrodes with an inter- electrode axis orthogonal to the surface 391, and catheter 393 has a pair of electrodes with an inter-electrode axis that is not orthogonal to the surface 391.
  • the inter-electrode distance 385 (i.e., the distance between the pair of electrodes) is "close.”
  • the inter-electrode distance 385 may be within an order of magnitude of the electrode size (i.e., from approximately 0.1 mm to 3.0 mm).
  • the inter-electrode distance 385 may vary from approximately 0.01 mm to 30.0 mm.
  • the inter- electrode distance 385 is between approximately 0.1 mm and 1 mm so that the indifferent electrode is "close" enough to the tissue surface to detect a signal.
  • the proximity of the indifferent electrode to the tissue surface may be determined by the thickness of the index electrode 382 and the inter-electrode distance 385.
  • the electrode pair is "unipolar" because only the index electrode 382 may be in contact with the tissue. This unipolar electrode
  • the configuration has at least two advantages over a contact bipolar electrode configuration, in which both electrodes may be in contact with the tissue.
  • the first advantage is that the unipolar electrode configuration retains all of the spatial resolution benefits of the contact bipolar configuration, but with the additional spatial resolution enhancement conferred by a smaller footprint (i.e., only half of the electrodes may be in contact with the tissue surface).
  • the second advantage is that the unipolar electrode configuration can retain the inter- electrode difference 385 independent from the direction of a tissue activation wavefront.
  • Contact bipolar electrogram amplitude depends upon the direction of tissue activation. When an activation wavefront is parallel to the inter-electrode axis, the potential difference between bipolar electrodes is maximum, and the resulting electrogram has maximum amplitude.
  • the unipolar electrode configuration can retain the inter-electrode difference 385 independent from the direction of a tissue activation wavefront and is immune to fractionation in response to changing wave-front direction.
  • FIG. 40 illustrates an example of improved spatial resolution obtained by use of an OCU electrode configuration in accordance with some embodiments of the present invention.
  • the tissue substrate surface 401 is assessed by a catheter with one pair of recording electrodes in an OCU electrode configuration 402.
  • the index electrode records electrogram signal 403, and the indifferent electrode records electrogram signal 404.
  • the resulting OCU electrogram signal 405 is calculated by subtracting the indifferent electrogram 404 from the index electrogram 403.
  • the tissue substrate surface 401 contains three linear non-conducting scars (resulting, e.g., from ablation lesions).
  • the scars separate the tissue surface 401 into four conducting channels 406-409.
  • the index electrode of the catheter is in close proximity to and/or touching the tissue surface 401 directly above the second conducting channel 407.
  • the path of tissue activation within the vicinity of the recording electrodes is serpentine.
  • the index electrode and indifferent electrode electrogram signals 403-404 exhibit large deflections at times 410-413 as the tissue activation wavefront moves through the conducting channels 406-409.
  • the OCU electrogram signal x05 exhibits very small deflections at times 410 and 412-413 as the tissue activation wavefront moves through the conducting channels406 and 408-409 not directly beneath the catheter, and a much larger deflection at time 411 as the tissue activation wavefront moves through the local conducting channel 407 directly beneath the catheter.
  • the index electrode and indifferent electrode electrograms 403-404 feature four deflections, indicating that a measurement of the frequency content of either electrogram would be higher than the true tissue activation frequency content of tissue surface 401. Meanwhile, the frequency content of the OCU electrogram 405 is a more likely indicator of the true tissue activation frequency.
  • Atrial fibrillation is widely treated by catheter ablation, and is curative in about 75% of patients.
  • the remaining patients in whom atrial fibrillation persists would benefit from improved activation mapping methods to resolve the complex dynamic patterns of tissue activation that typify recalcitrant atrial fibrillation.
  • Tissue activation patterns and their corresponding electric potential maps were simulated using a computational model of cardiac electrophysiology, and sampled the maps over a grid of locations to generate a mapping data set. Following cubic spline interpolation and an edge-extension and windowing method the data was deconvolved and compared the results to the model current density fields.
  • Deconvolution can lead to improved resolution for arrays of 10 x 10 electrodes or more that are placed within a few mm of the atrial surface when the activation patterns include 3-4 features that span the recording area.
  • Atrial fibrillation is commonly treated with the use of catheter ablation whereby lines of non-conducting tissue are created across the atria in an attempt to limit the patterns of electrical excitation to include only organized activity and not fibrillation. This procedure has been found to have relatively high overall success rates, even though multiple procedures are often required. In about 25% of cases, however, current approaches to catheter ablation fail to eliminate this arrhythmia. These recalcitrant cases of atrial fibrillation generally involve advanced disease of the atrial myocardium with extensive tissue remodeling. Knowing how to treat these difficult cases with the administration of additional or alternative ablation lesions would be enormously facilitated by accurate mapping of the electrical activity over the atrial surface.
  • An intra-cardiac electrode measures an electric potential that is generated by the combined electrical activities of each cell in the heart, the contribution from each cell being weighted in proportion to the cell's current density and in inverse proportion to the linear distance of the cell to the electrode.
  • the recorded potential field is thus a blurred version of the tissue current density field, the latter being the desired reflection of tissue activation.
  • This blurring process can be approximated as a convolution of the current density field with a point spread function that depends on the height of the electrode above the tissue.
  • a catheter design such as illustrated in FIGS. 68, 69A-69B, and 70, that facilitates the arrangement of electrodes such that they are aligned normal to the tissue surface is described.
  • a soft flexible planar material is used. This is constructed such that while fully deployed (advanced out of a long sheath the end of which is placed in the mapped chamber of the heart) the material is unfurled into a relatively flat surface 692, as shown in FIG. 69B.
  • the material is flexible enough that it can deform to the shape of the local tissue surface.
  • Small, paired electrodes are placed directly opposite each other on both sides of the surface. In this configuration when the catheter surface is in contact with the tissue these electrode pairs are orthogonal to the tissue.
  • the end of the flat portion of the catheter is smoothly tapered so that it can be pulled back into the long sheath and as it enters the sheath it furls to conform to the cylindrical shape 696 of the inside of the sheath.
  • the junction of the flat portion of the catheter (tip) with the catheter shaft is flexible enough that as the shaft is deflected forcing it to approach a position in which the shaft is normal to the tissue surface, the flat portion bends relative to the shaft and is pushed into an orientation co-planar with the tissue surface.
  • the catheter tip (flat portion) catheter shaft junction acts like a hinge such that any pressure of the shaft towards the surface naturally places the tip into a co- planar orientation relative to the tissue surface.
  • mapping the heart's electrical activity one sometimes desires multisite- simultaneous information broadly distributed and at other times one desires more detailed information from a smaller region. It is common that these needs are sequential; first one makes a general assessment of activation over a large area with low density of data points 680, based upon this data one identifies a sub-region (of the larger recording area) in which a higher density of data 682, 694 is required.
  • a catheter design in which the flat two-dimensional surface of the catheter tip is made from a distensible material. Thus when distended the surface area is larger than when the surface is not distended.
  • Electrode pairs distributed as above will be distributed over a smaller or larger area depending upon the amount of distension of the tip allowing for higher or lower density of recording sites.
  • the distance between the electrodes on the bottom and top surface of the tip (the OCU pairs) remains fixed; as such this design allows for each recording site to have high (and unchanging) spatial resolution even as recording site density is varied.
  • Distention of the surface could be achieved with a loop of wire 702 (possibly constructed of nitinol) that when advanced out of the catheter shaft increases the circumference of the tip surface.
  • the tip can be constructed of an inflatable balloon, but with the balloon constructed such that it doesn't inflate in a spherical shape rather it inflates in a flat plate-like shape 704.
  • Variable recording site density can be achieved through the use of a catheter design in which electrodes on the two-dimensional array (described above) are not evenly distributed but rather are concentrated with high density in one part of the catheter tip and lower density at other locations on the catheter tip. In this way using a single catheter and without need for changing the catheter size or shape one can focus density in one region while simultaneously having a broad view of other areas. Much like the increased density of rods and cones in the Fovea of the retina.
  • Atrial tissue is considered to be two-dimensional, as would be the case if one were mapping over a limited region and tissue thickness can be neglected.
  • the electric potential, ⁇ , recorded by a point electrode located above the tissue consists of a contribution from the membrane current density in each cell in the tissue weighted inversely by its linear distance to the electrode. Consequently, the transformation between the tissue membrane current density field and the potential field at height h can be described by the following integral equation:
  • Im(x, y) is the membrane current density field
  • pe is the specific resistivity of the medium between the tissue and the electrode (assumed to be blood)
  • w and z are dummy variables of integration representing the tissue spatial coordinates x and y.
  • ⁇ ( ⁇ , y, h) is the convolution of Im(x, y) with the point spread function (14)
  • FIG. 4 IB an extended version of the map in FIG. 41 A with spatial derivative matching at the boundaries of the original grid.
  • FIG. 41C is the result of multiplying the map in Fig. 4 IB by the window described herein.
  • the map in Fig. 41C is denoted ⁇ (x, y,h) to be able to recapitulate the key dynamic features of the aberrant excitation encountered in atrial fibrillation, including meandering rotors and multi-wavelet reentry.
  • the model consists of a sheet of square cells, each of which represents a small patch of cardiac myocytes.
  • model cells exhibit time-varying voltages according to the particular equations and rules that govern their behavior.
  • the time-derivative of the voltage of a cell located at position (x, y) is taken to be Im(x, y), which then allows ⁇ ( ⁇ , y, h) to be calculated according to Eq. 1.
  • the dimensions of x, y and h are expressed in units of the edge length of a cell, which is nominally 1 mm.
  • the intra-atrial potentials are measured by a square array of electrodes. This is simulated by sampling ⁇ ( ⁇ , y, h) at n x n equally spaced grid points, and then use two- dimensional cubic spline interpolation between the sampled points to create an estimate of the complete potential field over the region encompassed by the electrode array. Varying the value of n thus allows us to experiment with different spatial densities of electrodes. The electrodes themselves are assumed to have negligible extent. To simulate the effect of finite coverage of an electrode array over the atrial tissue, the n x n samples of ⁇ ( ⁇ , y, h) are selected from a square subset of the simulated tissue.
  • edges of the data array are extended by adding synthetic samples around the boundaries of the electrode positions in such a way as to bring the spatially extended grid of sampled values smoothly down to zero.
  • Simply adding extra data samples outside the original set does not guarantee, however, that the transition between the original data and the extra samples will be smooth, something that is desirable when performing deconvolution in the Fourier domain in order to avoid the introduction of spurious high frequencies in the deconvolved map. Therefore, smoothness is ensured as follows. First the continuous function obtained by cubic spline interpolation of the original n x n data points are continued analytically past the boundaries of the grid to a distance of one quarter the nominal width of the point spread function. This width is defined as the horizontal distance from the peak of the point spread function to its value at 10% of peak.
  • Deconvolution is performed in the spatial frequency domain by dividing the fast Fourier transform of ⁇ ( ⁇ , y, h) by the fast Fourier transform of f(x, y, h).
  • theory of the Wiener filter is invoked by replacing simple division in the Fourier domain by
  • ⁇ ( ⁇ , y) is an estimate of I (x, y) , denotes the inverse Fourier transform of the bracketed quantity
  • ⁇ (u,v,h) and f(u, v, h) are the Fourier transforms of ⁇ (x, y,h) and f(x, y, h), respectively.
  • the constant c in Eq. 2 has the effect of adding a small delta function to the point spread function. This serves to prevent division by something close to zero at those frequencies where the power in f(u, v, h) is zero, or very close to zero, and the power in ⁇ ( ⁇ , y,h) is finite.
  • a current density field I(x, y, h) (left-hand panel) is measured at a height of 2mm as a blurred potential field ⁇ ( ⁇ , y, h), as shown in FIGS. 42 A and 42B.
  • Deconvolution without any form of edge extension or windowing yields a poor reconstruction of I(x, y, h) as shown in Figs. 42C and 42D.
  • Deconvolution after edge extension and windowing as described in the text yields a much better reconstruction.
  • Figures 42A and 42D illustrates the importance of edge extension and windowing when deconvolving a truncated potential map.
  • the deconvolved map contains high-frequency line artifacts that obscure the details of the activation pattern (Figs. 42A and 42B). When edge processing is applied, these artifacts are effectively eliminated (Figs. 42C and 42D).
  • Figures 43 A-43L demonstrates the ability of deconvolution to resolve a simple rotor, showing the true current density, the observed potential field, and the deconvolved estimate of the current density at two time steps using arrays of Figs. 43A-43F 20 x 20 electrodes and
  • Figures 45A-45L illustrates a similar demonstration for a more complex activation pattern arising when a rotor begins to degenerate into multi-wavelet reentry.
  • Figures 47A-47I illustrate the effect of increasing h upon both the observed and deconvolved signals.
  • h increases from 1 to 5 the blurring in D(x, y,h) relative to I(x, y) becomes rapidly worse, and even the ability of our edgeprocessing technique to ameliorate the streak artifacts in ⁇ ( ⁇ , y) becomes severely degraded (Fig. 47C).
  • Fig. 47C This demonstrates how important it is to place the mapping electrodes as close to the cardiac tissue as possible. Even so, the deconvolved signal improves upon the raw data at heights up to 5. However, this is not always the case.
  • Figures 48A-48B illustrates that MSRobs becomes greater than MSRdec at a height of 10.
  • Figs. 43 A-43L, 45A-45L and 47A-47I are available on the web site repository.
  • Figs 44 A and 44B MSR for the observed and deconvolved signals relative to the true signal for the two activation patterns shown in Figs. 43 A-43L. Solid line - MSRobs, circles - MSRdec. The unit of MSR is the square of the model cell dimension.
  • catheter ablation therapy for the treatment of atrial fibrillation has an impressive success rate, effectively curing the condition in about 75% of patients, it continues to present a major clinical challenge in the remaining 25% in whom atrial fibrillation persists
  • Prior art electrode arrays do not have sufficient spatial resolution to fully resolve the most complex activation patterns seen in cardiac fibrillation. Finer arrays of electrodes capable of measuring intra-cardiac potential at multiple closely-spaced sites over a localized region of tissue will need to be developed to facilitate atrial fibrillation mapping. Methods of digital signal processing can be used to enhance the spatial resolution of such arrays beyond the physical limitations imposed by electrode size and number. FIGS.
  • 46A and 46B illustrate the MSR for the observed and deconvolved signals relative to the true signal for the two activation patterns shown in FIGS. 45A-45L.
  • the basic resolution enhancement issue in atrial fibrillation mapping can be expressed as a problem in
  • deconvolution Although straightforward in principle, in practice deconvolution is fraught with a number of pitfalls related to noise and data truncation. Fortunately, there are established methods for dealing with these problems in general, although each deconvolution problem stands on its own merits in terms of the details of these methods. In the case of deconvolving maps of atrial fibrillation activity, the two major problems are sparseness of data sampling and incompleteness of spatial coverage. The first of these is readily dealt with through interpolation between the measured data samples, the success of which is dependent upon the sampling density relative to the spatial frequencies in the activation pattern being sampled. A previous study, for example, has applied this approach to the problem of distinguishing local from distant sources in electrogram recordings [8].
  • the problem with this approach is that it eliminates a significant amount of the data around the borders, which should be minimized given the sparseness of the original data set.
  • the alternative approach is to extend the borders of the data array with synthetic data that proceed smoothly to zero beyond the bounds of the original data set. The disadvantage here is that the missing data must be guessed at.
  • Figs. 47A-47I illustrate the effects of electrode height on the resolution of a rotor, showing the true current density, the observed signal, and the deconvolved signal at heights of Fig. 47 A 1, Fig. 47B 3, and Fig. 47C 5.
  • the deconvolution approach was applied to simulated rotors (Figs. 43 A-43L and 47A-47I) and multi-wavelet reentry (Figs. 45A-45L), as these typify the kinds of complex activity patterns seen in atrial fibrillation.
  • the results indicate that deconvolution can provide a useful improvement in map resolution compared with raw electrode array recordings.
  • the accuracy of deconvolution is substantially improved by an edge processing technique that combines windowing and edge extension.
  • Fig. 47D Solid line - MSRobs, circles - MSRdec.
  • the electrode array characteristics required for deconvolution to improve upon unprocessed potential recordings in human atrial fibrillation depend upon the tissue spatial frequency of the atrial activity in such patients. Based upon high density mapping in humans with long standing persistent atrial fibrillation, it is likely that there can be greater than or equal to 1.5 waves across each cm of atrium [15]. In this range of spatial frequency deconvolution would improve spatial resolution for 10x10 arrays in which inter-electrode spacing is ⁇ 0.3 mm. Ultimately, of course, this will need to be tested in humans with atrial fibrillation. In the meantime, the current modeling experiments allow us to accurately compare tissue current density distributions and electrogram recordings, something that is not possible in human experiments. These numerical experiments inform us as to the kinds of electrode array characteristics that should be used when performing biologic confirmation.
  • the electrogram frequency pattern may be measured simultaneously across a tissue substrate to indicate the tissue activation frequency pattern, which indicates the circuit core density and distribution.
  • a multi -electrode array may be deployed via thoracotomy at the time of surgery, percutaneously, and/or transvenously and positioned over a region of cardiac tissue.
  • FIG. 49 illustrates a tissue substrate surface 491, over which a two-dimensional multi- electrode array 492 has been deployed in OCU configuration in accordance with some embodiments of the present invention.
  • 100 index electrodes 493 are paired with 100 indifferent electrodes 494.
  • Each pair of electrodes is itself in OCU configuration.
  • high spatial resolution at each recording site e.g., each OCU electrode pair in a multi-electrode array
  • electrogram signal frequencies to accurately reflect tissue activation frequencies (and hence local circuit core densities).
  • the maximum distance between recording sites relates to the optimal distance between ablation lesions, which, in turn, relates to what extent the circuit core density will be reduced in the area around a lesion as a result of the lesion.
  • the recording sites themselves need not be spaced extremely close together relative to the inter-electrode spacing in accordance with some embodiments of the present invention.
  • the multi-electrode array in FIG. 49 may have an inter-electrode spacing of only 0.1 mm to 3.0 mm, but the distance between each OCU electrode pair may be 5 mm to 10 mm).
  • FIG. 50 illustrates a tissue substrate surface 501, over which a two-dimensional multi- electrode array 502 has been deployed in accordance with some embodiments of the present invention.
  • the array includes 100 OCU electrode pairs, each with one index electrode 503 and one indifferent electrode 504.
  • the multi- electrode array 502 itself is not orthogonal to the tissue surface 501 (due to, e.g., incomplete apposition of the catheter with the tissue).
  • the orientation of a multi-electrode array may be determined without seeing the tissue.
  • electrogram signal 205 is more sudden with greater amplitude than electrogram 506, which is smaller and more gradual, thus indicating that the recording position for the electrogram signal 505 is closer to the tissue surface 501 than the recording position for the electrogram signal 506.
  • electrogram signal 205 is more sudden with greater amplitude than electrogram 506, which is smaller and more gradual, thus indicating that the recording position for the electrogram signal 505 is closer to the tissue surface 501 than the recording position for the electrogram signal 506.
  • Each electrode in a multi -electrode array records a net electric field potential, to which each cardiac cell contributes in an amount proportional to the cell's tissue current density and inversely proportional to the linear distance from the cell to the electrode.
  • the recorded net electric field potential may be a blurred approximation of the tissue current density field, which is used to indicate tissue activation frequency and, in turn, the circuit core density and distribution.
  • this blurring may be treated as though the tissue current density field was convolved with a spatially decaying point spread function, which can be estimated.
  • numerical deconvolution of the measured net electric field potential may be applied to extract information about the spatial nature of tissue activation frequency from multi-electrode recordings and thereby improve spatial resolution.
  • Deconvolution following spatial truncation leads to a phenomenon known as "leakage,” which can be ameliorated by either windowing or artificially extending the edges of the sampled pattern of net electric field potentials.
  • FIG. 51 A is a process flowchart for improving spatial resolution using deconvolution in accordance with some embodiments of the present invention.
  • step 511 a spatially truncated intra-cardiac pattern of net electric field potentials is sampled using an m ⁇ n array of electrodes recording at height h above a tissue surface.
  • interpolation e.g., two- dimensional cubic spline interpolation
  • step 513 a point spread function is calculated from height h.
  • the truncated edges of the continuous function representing the complete net electric field potentials may be processed using a combination of edge extension and windowing in accordance with some embodiments of the present invention.
  • the continuous function is analytically extended beyond the boundaries of the original m ⁇ n sampled data points to a distance of half the nominal width of the point spread function.
  • the nominal width of the point spread function is the horizontal distance from the peak of the function to the value at 10% of peak.
  • the extended continuous function is multiplied by a window.
  • the window may comprise, but is not limited to, a central rectangular section of unity height.
  • the dimensions of the central section are the same as of the dimensions of the original m ⁇ n array of sampled data points less half the nominal width of the point spread function.
  • FIG. 5 IB illustrates an exemplary window in accordance with some embodiments of the present invention.
  • step 516 the continuous function and the point spread function are transformed to the spatial frequency domain using, for example, the fast Fourier Transform ("FFT").
  • step 517 deconvolution is performed in the spatial frequency domain by dividing the transformed continuous function by the transformed point spread function.
  • a Wiener filter may be invoked and/or a small constant may be added to the denominator when dividing in the spatial frequency domain to prevent amplification of noise arising from numerical and measurement errors.
  • electrogram frequencies which may indicate tissue activation frequencies and, in turn, circuit core density and distribution— informs the optimal placement of ablation lesions to treat cardiac fibrillation.
  • FIG. 13 is a system component diagram in accordance with some embodiments of a system for detecting and/or mapping cardiac fibrillation in a patient.
  • the system may include, but is not limited to, a catheter subsystem 132, a processing unit 135, a memory 134, a transceiver 133 including one or more interfaces 139, a GUI 138, and/or a display 136 (each described in detail below).
  • the system may also include, but is not limited to, an ECG/EKG subsystem 130 and/or an imaging subsystem 131 (described above).
  • the catheter subsystem 132 may be configured for determining patient-specific (and location-specific) tissue spatiotemporal variations, mapping one or more measurements indicative of the density and distribution of circuit cores, determining electrode contact and rotation relative to tissue, and/or assessing the efficacy of a treatment procedure (e.g., whether ablation lesions completely prevent conduction in both directions).
  • a catheter in the catheter subsystem 132 may be configured to perform one or more types of procedures according to some embodiments of the present invention.
  • a catheter for mapping one or more measurements indicative of the density and distribution of circuit cores includes one or more pairs of recording electrodes in the OCU electrode configuration.
  • a mapping catheter includes a two-dimensional array of recording electrodes, in which the electrodes are preferably: (1) as small as possible (without incurring too great an increase in noise that results from high impedance); (2) of sufficient number so that deconvolution confers a spatial resolution advantage; and (3) oriented with an inter-electrode relationship that facilitates improved spatial resolution (i.e., the OCU configuration).
  • the same or a similarly configured catheter in the catheter subsystem 132 may be used for identifying the optimal spatial resolution for local tissue with spatiotetmporal variation.
  • FIGS. 52A and 52B illustrate a similarly configured catheter with more than two electrodes on an axis orthogonal to the tissue surface.
  • the same or a similarly configured catheter in the catheter subsystem 132 may be used for mapping and/or assessing the efficacy of a treatment procedure.
  • a similarly configured catheter also may be used to assess whether an ablation lesion completely prevents conduction by selecting one electrode on either side of the lesion for pacing, and then recording the tissue activation timing on the remaining electrodes to quickly identify the presence or absence of a complete conduction block. By selecting one electrode on the opposite side of the lesion for pacing, a complete bi-directional conduction block may or may not be confirmed (by pacing from both sides of the ablation lesion one can confirm bi-directional block).
  • a similarly configured catheter in the catheter subsystem 132 may be used for treating cardiac fibrillation.
  • a similarly configured catheter also may include an ablation electrode configured for creating point and/or linear ablation lesions in the heart tissue.
  • FIGS. 53 and 54 illustrate different views of a catheter configured for both mapping, minimizing, and treating cardiac fibrillation.
  • an ablation electrode may be included on one of a multiple of catheter splines while one or more pairs of recording electrodes may be included on a separate catheter spline.
  • an ablation electrode may be included as part of a multi- electrode array, such that mapping, lesion assessment, and ablation treatment may all be performed using a single catheter.
  • the system for detecting and mapping fibrillation may also include one or more processing units, shown collectively in FIG. 13 as processing unit 135, that process instructions and run software that may be stored in memory.
  • processing unit 135 executes applications, which may include, but are not limited to, catheter-related applications for positioning electrodes and recording electrograms; signal processing applications for performing, for example, deconvolution processes; and topological mapping applications for identifying reentrant circuit core density and distribution in the heart.
  • the software needed for implementing a process or a database includes a high level procedural or an object-orientated language such as C, C++, C#, Java, Perl, or MATLAB®. The software may also be implemented in assembly language if desired.
  • Processing unit 135 can be any applicable processing unit that combines a CPU, an application processing unit, and memory.
  • Applicable processing units may include any microprocessor (single or multiple core), system on chip (SoC), microcontroller, digital signal processor (DSP), graphics processing unit (GPU), combined hardware and software logic, or any other integrated circuit capable of processing instructions.
  • the system for detecting and mapping fibrillation may also include one or more memory devices, shown collectively in FIG. 13 as memory 134.
  • Memory 134 stores the instructions for the above applications, which are executed by processing unit 135.
  • Memory 134 also may store data relating to detecting and mapping fibrillation, such as the electrogram recordings and frequencies.
  • the system for detecting and mapping fibrillation may also include one or more transceivers, shown collectively in
  • Transceiver 133 includes a transmitter and a receiver.
  • the transmitter and the receiver may be integrated into a single chip or may be embodied in separate chips, or may be integrated with processing unit 135 and/or memory 134.
  • Transceiver 133 may also include one or more interfaces 139, that provide an input and/or output mechanism to communicate with other devices, such as the catheter subsystem 132.
  • interface(s) 139 may operate to receive electrogram recordings from as well as transmit instructions to the catheter subsystem 132.
  • Interface(s) 139 can be implemented in software or hardware to send and receive signals in a variety of mediums, such as optical, copper, and wireless, and in a number of different protocols some of which may be non-transient.
  • the system for detecting and mapping fibrillation may also include a GUI 138 to provide communication with an input and/or output mechanism to communicate with a user.
  • a clinician may use input/output devices to send/receive data to/from the processing unit 135 and catheter-based subsystem 132 over the GUI 508.
  • Input devices may include, but are not limited to, a keyboard, a touch screen, a microphone, a pen device, a trackball, a touch pad, and a mouse.
  • output devices may include, but are not limited to, a display 136, a speaker, and a printer.
  • Other input/output devices may also include, but are not limited to, a modem and interface(s) 139 of transceiver 133.
  • the GUI 138 can operate under a number of different protocols, and the GUI interface 138 can be implemented in hardware to send and receive signals via transceiver 133 in a variety of mediums, such as optical, copper, and wireless.
  • FIG. 55 is a process flowchart for detecting and mapping fibrillation in accordance with some embodiments of the present invention.
  • a puncture is made in a distal vessel, a guidewire is inserted, and a vascular sheath is threaded over the wire.
  • a mapping catheter with a multi-electrode array is inserted using a guidewire and moved toward the heart. Alternatively, this insertion can be made percutaneously via the chest or via thoracotomy at the time of surgery.
  • the catheter is positioned so that the one or more inter-electrode axes are orthogonal to the surface of the tissue substrate.
  • an OCU-configured electrode pair or array may be engaged in one tissue location or region at a time so that an array of signals (e.g., net electric field potentials) may be recorded in step 553.
  • an array of signals e.g., net electric field potentials
  • step 554 the signal recorded by each orthogonal indifferent electrode is subtracted from the signal recorded by its associated index electrode to acquire a new array of signals.
  • step 555 signal processing including, but not limited to, interpolation, edge extension and windowing, FFT, deconvolution, and/or calculation of the centroid of a signal power spectrum is performed to return values (e.g., local electrogram signal frequencies as defined by the centroid of the power spectrums) indicative of tissue activation frequencies, which are indicative of reentrant circuit core density and distribution across the tissue substrate.
  • return values e.g., local electrogram signal frequencies as defined by the centroid of the power spectrums
  • step 556 these values are mapped (e.g., in a color-coded fashion) onto a representation (e.g., a two-dimensional image or three-dimensional model) of the tissue substrate surface according to the positions of the recording electrodes, which are identified using an appropriate electrode localization technology.
  • a representation e.g., a two-dimensional image or three-dimensional model
  • FIGS. 56A-56C illustrates the relationship between: (FIG. 56A) an OCU electrogram frequency map of a tissue substrate indicating circuit core density and distribution (using the centroids of the power spectrums); (FIG. 56B) an OCU electrogram recording for a location 1801 in the mapped tissue substrate; and (FIG. 56C) the power spectrum derived through FFT of the OCU electrogram in accordance with some embodiments of the present invention.
  • electrogram signals of an index electrode and its associated indifferent electrode are recorded.
  • the resulting OCU electrogram (i.e., the difference between the two signals) for location 561 is shown in FIG. 56B.
  • the local electrogram frequency at location 561 is calculated by deriving the power spectrum of the FFT of the OCU electrogram.
  • FIG. 56C is a plot of the power spectrum, on which centroid 562 has been calculated and marked. The value of the centroid 562 of the power spectrum is mapped onto a representation of the tissue substrate at the coordinates for location 561 to indicate tissue activation frequency, which is indicative of circuit core density, at location 561.
  • FIG. 57 is a map of a tissue substrate indicating tissue activation frequencies, which are indicative of circuit core densities, in accordance with some embodiments of the present invention.
  • the values on the map are the local electrogram signal frequencies as defined by the centroid of the respective power spectrums.
  • FIG. 57 illustrates the impact of selecting a threshold frequency to define the size and number of high circuit core density regions across a tissue substrate in accordance with some embodiments of the present invention. For example, if threshold frequency 571 is selected for this tissue, four regions of high circuit core density, including region 573 and region 574, are indicated. However, if a lower threshold frequency 572 is selected, all of the regions expand and region 573 and region 574 are fused into one high circuit core density region 575.
  • the efficiency of ablation lesions can be maximized by making use of the previously identified locations of high circuit core density. Because high circuit density sites can be distributed throughout the surface of the atrial tissue in complex arrangements that vary by patient, finding a distribution of ablations that overlaps the largest number of high circuit density sites and connects to the tissue edge with the smallest total lesion length is an important optimization question.
  • connection of multiple sites using the shortest possible distance is as a combinatorial optimization problem that can be solved using a number of computer-based algorithmic solutions.
  • the problem can be solved by exact algorithms, comparing every possible permutation to find the optimal solution.
  • the complexity of the problem rises at the rate of O(n!).
  • heuristics or approximation algorithms can be used to reach a solution very quickly for large numbers of sites, although the solution may not be optimal and complete. Heuristics algorithms iteratively improve a solution until search termination criteria are met, rather than exploring every permutation. Different algorithms have different methods for choosing permutations on their iterations.
  • the termination criteria can include the number of iterations, a threshold value, the speed at which a solution is improving, or a number of iterations without improvement.
  • Some examples of heuristics algorithms include greedy algorithm, genetic algorithm, simulated annealing, particle swarm optimization, and ant colony optimization.
  • a genetic program which is a specialization of genetic algorithms, is used to solve this optimization problem.
  • the genetic program iteratively improves a solution based upon the principles of evolution and "survival of the fittest."
  • "fitness" is characterized as a line distribution that covers the largest total circuit density with the smallest number of ablation points (i.e., shortest total lesion length).
  • the program may also incorporate constraints such as, for example, avoidance of ablating across atrial arteries. Additional fitness criteria can be added so that the search strategy reflects current best lesion distribution characteristics.
  • Embodiments of cardiac fibrillation detection and mapping system may use the genetic program to identify and, optionally, display the highest efficiency distribution of lesions to connect the "peaks" in the topological map representing circuit core density and distribution. This information can then be used by a clinician based upon complete consideration of the clinical context.
  • the genetic program provides a hierarchical tree-like structure to define the genotype of its solutions in accordance with some embodiments of the present invention.
  • Embodiments of the genetic program take a unique approach in which the genotype is also the phenotype.
  • the tree-like structure itself represents the distribution of ablation lesions.
  • the individual elements are potential sets of ablation lesions (i.e., an ablation lesion set).
  • an individual element is defined by the locations of its connection(s) to the tissue's boundary edge, the first branch point, subsequent branch points and each end point.
  • the fitness of each individual element in a population is measured as the total density of the map points that that ablation lesion set overlaps.
  • tissue 80 ⁇ 80 cells was created with heterogeneous electrophysiologic properties. Specifically, the tissue had two different regions, each region having variability of action potential duration randomly distributed around a mean value. In the majority of the tissue, the action potential duration mean was 130 ms (with an intercellular resistance of 9 ohms). However, in one square patch of the tissue (26 ⁇ 26 cells), the action potential duration mean was 80 ms (with an intercellular resistance of 13 ohms).
  • Burst pacing (from each of 64 pacing sites) was applied during multiple simulations in each tissue region. In the presence and absence of ablation lines extending from a tissue edge, measurements were obtained of (1) the percentage of instances in which pacing resulted in successful induction of multi-wavelet reentry, and (2) the duration of each episode of multi-wavelet reentry. The location, length, and number of ablation lines were randomized over 500 iterations.
  • the total ablation line lengths (aggregated from the lengths of individual ablation lines in each set) were calculated and varied from 0 to 150 cells. Measurements of the average circuit density of the cells at each ablation site were obtained and used to calculate the average circuit density underneath the entire ablation line set. Of the total 500 ablation line sets, 10 sets were selected based upon their average circuit density overlap such that there was an even distribution of ablation line sets ranging from minimal to maximal circuit density overlap.
  • FIGS. 64-65 are two views of a three-dimensional plot of the time to termination of induced episodes of multi-wavelet reentry (z-axis) as a function of total ablation length (x-axis) and circuit density overlap (y-axis) in accordance with some aspects of the present invention.
  • FIGS. 64-65 reveal that time to termination is reduced as (1) total ablation length increases and (2) circuit density overlap increases.
  • time to termination and total ablation length are largely linear when circuit density overlap is low but distinctly non-linear when circuit density overlap is high.
  • high circuit density overlap compared to low circuit density overlap
  • greater efficiency may be achieved ( i.e., greater reduction in time to termination per amount of ablation).
  • the total ablation length reaches a point of diminishing returns in terms of the impact on time to termination, that time to termination begins to decline steeply when an ablation line extends from a tissue edge to the high circuit density patch and that the point of diminishing returns is reached when the ablation line extends through the high density patch.
  • FIGS. 66-67 are two views of a three-dimensional plot of the percent inducibility (z-axis) as a function of total ablation length (x-axis) and circuit density overlap (y-axis) in accordance with some aspects of the present invention.
  • z-axis percent inducibility
  • y-axis circuit density overlap
  • FIG. 13 is a system component diagram in accordance with some embodiments of a system for optimizing the placement of ablation lesions in a patient's heart.
  • the system may include, but is not limited to, a processing unit 135, a memory 134, a transceiver 133 including one or more interfaces 139, a GUI 138, and/or a display 136 (each described above).
  • FIG. 59 is a process flowchart for applying a genetic algorithm for optimizing lesion placement to a map indicating circuit core density and distribution according to some embodiments of the present invention.
  • step 591 one or more measurements indicating reentrant circuit core density and distribution across a tissue substrate are mapped.
  • step 591 one or more measurements indicating reentrant circuit core density and distribution across a tissue substrate are mapped.
  • a threshold e.g., the top 20%
  • a threshold e.g., the top 20%
  • the high circuit core density regions are circumscribed.
  • a random initial ablation lesion set i.e., a sample
  • the random sample may include a population of, for example, 100 potential lesions. Each potential lesion in the sample connects a high circuit core density region with a tissue boundary.
  • the connection between a high circuit core density region and a tissue boundary may be direct or indirect. That is, a lesion line may be connected to another lesion line and/or a tissue boundary.
  • connection between high circuit core density regions and between a high circuit core density region and a tissue boundary may be linear, curvilinear, or some other shape, as long as the connections are continuous.
  • total length of the proposed ablation lesions is optimized, which can be used for the fitness selection in step 596.
  • elements with the highest fitness are chosen. For example, two elements in the sample could be chosen.
  • the number of elements to be selected is based on an optimization parameter.
  • the chosen elements based on the fitness selection are used to produce the next generation in step 599, while the other individual elements are discarded.
  • the computer algorithm decides if termination criteria is met. If the termination criteria is met, the optimization is complete as shown in step 598. Otherwise, in step 599, a new generation of individual elements is created through mutation and crossover from the "parents.” Mutation changes one or more elements of the solution but leaves other elements, thus creating a slight variation. Crossover derives a new solution based on parts of two or more parents. For example, a first half of the solution comes from one parent and a second half comes from another parent. Then the process returns to step 592: fitness calculation. The fitness of each individual element in this new generation is calculated so that the fittest may be chosen. The process is repeated and the fitness of the solution evolves to maximize the total density of the map points covered while minimizing the extent of ablation.
  • FIG. 13 is a system component diagram in accordance with some embodiments of a system for assessing fibrillogenicity in a patient.
  • the system may include a catheter subsystem 132, a processing unit 135, a memory 134, a transceiver 133 including one or more interfaces 139, a GUI 138, and/or a display 136 (each described above).
  • the system may also include, but is not limited to, an ECG/EKG subsystem 130 and/or an imaging subsystem 131 (also described above).
  • FIG. 60 is a process flowchart for quantifying and/or assessing fibrillogenicity in a patient in accordance with some embodiments of the present invention.
  • initial fibrillogenicity is assessed.
  • electrograms are acquired, from which electrogram frequencies are derived in step 603.
  • the frequencies indicative of circuit density and distribution are mapped.
  • the process then includes step 605, in which ablation lesion placement is optimized.
  • fibrillogenicity is quantified and compared with a predetermined threshold.
  • ablation lesion therapy is applied, and the process iterates back to step 602, wherein new electrograms are acquired.
  • the process is completed in 608, once the measure of fibrillogencity meets is below the predetermined threshold.
  • clinicians may determine if additional lesions should be placed. This determination can be made by measuring the tissue activation frequency following an ablation. If the tissue activation frequency becomes lower than a threshold frequency, then the process of ablation treatment ends. However, if the tissue activation frequency is higher than a predetermined threshold frequency, clinicians may add more lesions.
  • FIG. 13 is a system component diagram in accordance with some embodiments of a system for iteratively treating cardiac fibrillation in a patient.
  • the system may include a catheter subsystem 132, a processing unit 135, a memory 134, a transceiver 133 including one or more interfaces 139, a GUI 138, and/or a display 136 (each described above).
  • the system may also include, but is not limited to, an ECG/EKG subsystem 130 and/or an imaging subsystem 131 (also described above).
  • FIG. 62 is a system diagram, in accordance with embodiments of the present invention.
  • FIG. 62 describes the EKG subsystem 621, imaging subsytem 622, and catheter subsystem 623, as detailed above.
  • FIG. 61 is a process flowchart for treating cardiac fibrillation in a patient using iterative feedback in accordance with some embodiments of the present invention.
  • step 611 one or more measurements indicative of circuit core density and distribution are mapped.
  • an optimization method is applied to find the optimal distribution of ablation lesions in step 612. The optimization may be based on the regions with, for example, the top 30% of the highest circuit core density sites.
  • step 613 the atria of a patient are ablated based on this optimal distribution.
  • clinicians use a catheter, preferably a mapping catheter in accordance with the systems of the present invention, to ascertain the presence or absence of bidirectional block across ablation lesions.
  • step 615 a determination is made as to whether the ablation lesions are or are not complete as performed (i.e. is further ablation required to achieve bidirectional block?). If bidirectional block is not complete, the process goes back to step 613 and additional ablation is added. If bidirectional block is complete, then F-wave cycle length is checked in step 616. In step 617, a determination is made as to whether the F-wave cycle length is greater than, for example, 180 milliseconds. If the F- wave cycle length is greater than 180 milliseconds, ablation therapy is complete. Otherwise, if the F-wave cycle length is less than 180 milliseconds, the entire process repeats beginning at step 611. [0400] Ablation lesions may be produced via tissue heating or cooling. Such energies include radiofrequency, high frequency and/or focused ultrasound, laser, microwave or cryo- technologies. The only requirement is that tissue be irreversibly damaged such that recovery of conduction cannot occur.
  • embodiments of the present invention include new methods and systems for identifying electrode tissue contact and orientation. These methods and systems make it possible for a clinician to determine whether an electrode pair is in contact with and orthogonal to a tissue surface.
  • the methods and systems of the present invention provide an improvement over prior techniques, for example, in that they are predicated on the recognition and modeling of the actual physiologic and, particularly, electrophysiologic principles underlying electric current flow in cardiac tissue, and therefore can identify electrode tissue contact and electrode orthogonality using electrogram analysis alone. For instance, when electric currents flow in the cardiac tissue, due to propagation of cell activation, there is a fluctuation of the electric potential field surrounding the heart.
  • the amplitude of the electrogram which is the signal generated by the electrode in response to fluctuations of the electric potential field, varies approximately with the inverse of the square of the distance between the electrode and the cardiac current.
  • the electrogram amplitude increases, and as it recedes away from the electrode the amplitude quickly reaches a maximum negative value and then diminishes in amplitude as the wave-electrode distance increases.
  • the result is an electrogram whose amplitude changes with time, as the wave propagates.
  • the instantaneous rate of change in amplitude which is calculated as the derivative of the voltage (V) with respect to time (t), or dV/dt, is a function of several different factors, including the conduction velocity of the propagating wave, the size of the electrode, the height of the electrode above the tissue, the curvature of the wave and the magnitude of the cardiac currents. Because there are so many factors that influence the dV/dt, one cannot deduce whether an electrode is in contact with or raised above the tissue based upon dV/dt alone. However, if the dV/dt is recorded from two electrodes positioned on a catheter such as the catheters disclosed in, for example, FIGS.
  • the difference in dV/dt between the two electrodes is a function of the height of each electrode, while other factors, such as conduction velocity, wave curvature and magnitude of cardiac currents, are the same for both electrodes as they are recording the same wave.
  • all confounding variables cancel out and, if the inter-electrode distance is known, for example by virtue of being on the same catheter, then the difference in dV/dt, or the delta dV/dt between the electrograms of the two electrodes is directly related to the height of the electrodes above the tissue surface.
  • the dV/dt decreases non-linearly as an electrode is raised above the tissue. This means that the amount that dV/dt changes between two electrodes that are at a known inter-electrode spacing, for example 1mm, is dependent upon how high those electrodes are from the tissue. A larger delta dV/dt, indicates that one electrode in the pair is touching tissue and the pair is orthogonal to the tissue, whereas a smaller delta dV/dt indicates that electrodes are not in contact and/or not orthogonal to the tissue.
  • the difference in dV/dt is small, and if the electrodes are touching but they are not orthogonal, then the difference between their heights above the tissue is less than 1mm and hence the difference in their dV/dt will be less as well.
  • FIG. 87 is a process flowchart for identifying electrode tissue contact, in accordance with an embodiment of the present invention.
  • electrograms from two electrodes at a known inter-electrode spacing are recorded 870.
  • dV/dt is recorded from both electrodes 872.
  • the amplitude of each beat of each electrode is measured 873.
  • the difference between the dV/dt value for the two electrodes, or delta dV/dt value is calculated 874.
  • the delta dV/dt value is compared with a threshold value to determine whether first electrode is in contact with tissue and the second electrode is orthogonal to the tissue 875. If the delta dV/dt value is above a threshold value, then it may be deduced that the first electrode in the pair is in contact with and the pair is orthogonal to the tissue. If the delta dV/dt value is below the threshold value, then it may be deduced that the first electrode in the pair is not contact with and/or the pair is not orthogonal to the tissue.
  • the method of determining the delta dV/dt for determining electrode tissue contact can be employed with a pair of electrodes having a known inter- electrode spacing, as shown and described previously, for example, with reference to FIG. 20. In each case one would require prior measurements of the dV/dt (and delta dV/dt) at various heights above the tissue in the electrodes to be used. This would provide empiric data for selecting a threshold value for delta dV/dt that would be used for declaring electrode tissue contact, that is the value above which indicates that the electrode is in contact with and orthogonal to the tissue.
  • the raw electrogram signals would be delivered to a computing device where the dV/dt, peak dV/dt, average of the peak dV/dts and then delta dV/dt would be calculated.
  • the electrode pair To identify a delta dV/dt threshold for frequency mapping in atrial fibrillation the electrode pair must be ⁇ 2mm above the tissue.
  • To identify a threshold for confirming contact for ablation the lower electrode in the pair must be touching the tissue.
  • FIG. 85 is a process flowchart for identifying a threshold value, in accordance with one embodiment of the present invention.
  • a threshold value for identifying adequate electrode contact for frequency mapping of atrial fibrillation may be identified by first placing the catheter including a pair of electrodes perpendicular to the tissue surface and ⁇ 2mm above the tissue surface, during normal rhythm and atrial fibrillation 850 and recording unipolar electrograms from each electrode 851. The derivative of the voltage with respect to time may then be calculated for each electrode 852. Next, the 20 peak negative values of dV/dt in a 4.5 second window may be identified and averaged 853. The averages may then be plotted relative to the height of the respective electrode above the tissue 854.
  • FIG. 86 is a process flowchart for identifying a threshold value, in accordance with another embodiment of the present invention.
  • a separate threshold value for identifying adequate electrode contact for ablation may be identified by first placing the catheter including a pair of electrodes perpendicular to the tissue surface and in contact with the tissue surface, during normal rhythm and atrial fibrillation 860 and recording unipolar electrograms from each electrode 861. The derivative of the voltage with respect to time may then be calculated for each electrode 862.
  • the 20 peak negative values of dV/dt in a 4.5 second window may be identified and averaged 863.
  • the averages may then be plotted relative to the height of the respective electrode above the tissue 864.
  • the value of the difference between dV/dt for the electrode in contact with the tissue and the electrode immediately above that electrode may be identified and used as a threshold value for determining whether the electrodes are in contact with and orthogonal to the tissue 865.
  • Electrograms were recorded on the epicardial surface with the catheter.
  • the catheter included five 1mm electrodes with 1mm inter-electrode spacing, however other electrode number and spacing configurations may be used in accordance with the present disclosure.
  • the catheter was connected to an electrogram recording system. Electrograms were analyzed with custom software developed in Matlab (The Mathworks, Natick, MA). Statistical comparisons were made with Student's t-tests.
  • This catheter was positioned on the epicardial surface of the heart and maintained in an orthogonal orientation relative to the heart surface (via manual stabilization and visual inspection), as illustrated in FIG. 52B.
  • electrograms were recorded during sinus rhythm and pace induced atrial fibrillation. Induction of atrial fibrillation was facilitated by stimulation of the vagus nerve (2-5 V at 10Hz).
  • FIG. 80 using a 4.5 second recording we obtained the first derivative of the electrogram amplitude. The 20 largest amplitude peaks were selected from the derivative, which are highlighted with circles in FIG. 80. The average of these 20 amplitudes was taken as the average maximum dV/dt for each of the 5 electrodes. The average dV/dt of each adjacent pair of electrodes (1st and 2nd, 2nd and 3rd, 3rd and 4th, 4th and 5th) was then subtracted. This process was repeated in 3 swine.
  • a computational model of cardiac excitation was developed to generate reentrant rhythms with emergent behavior including formation of stable and meandering spiral waves as well as multi-wavelet reentry.
  • the model possessed a sufficiently small computational burden such that multiple simulations of extended periods of excitation could be run in a manageable amount of time.
  • the model is a hybrid of a physics based diffusion model and a cellular automaton.
  • the model allows rapid, i.e., computationally efficient, simulation of cardiac electrical propagation, including fibrillation.
  • This computational model did not include all the known biophysical details of individual cardiac cells. Nevertheless, it did incorporate the key behavioral features of individual cells that are required to reproduce realistic global conduction behavior. This behavior included source-sink relationships with wave curvature-dependent conduction velocity and safety factor, and the potential for excitable but unexcited cells to exist at the core of a spiral-wave.
  • the computational model thus combined the computational expediency of cellular automata with the realism of much more complicated models that include processes at the level of the ion channel.
  • tissue was created with heterogeneous physiologic parameters. Each tissue was made up of 6400 cells (80x80mm 2 ) to provide sufficient tissue area to support multiwavelet reentry. To generate heterogeneity in the activation frequency, a Gaussian filter was applied to an array (80x80) with a random distribution of values to create smooth gradients between regions of higher and lower action potential durations (APDs) (Range 60- 100ms). Local APD heterogeneity was added with random white noise between -10 and 10ms. Intercellular resistance remained constant in all tissues (1 lohms).
  • APDs action potential durations
  • a virtual electrode catheter 717 with 4 hemi-cylindrical electrodes 710 was created and positioned around the surface of a cylindrical catheter shaft.
  • the electrodes 710 were positioned such that pairs were on opposite sides of the shaft.
  • four electrodes were made up of the quadrants of a cylinder positioned on its side.
  • Each electrode was created using a finite element mesh (20 elements per electrode); electrogram calculations were made using the equation:
  • ? is the resistivity of the blood
  • I(x,y) is the current density field in the tissue. Electrogram recordings were made from an 8x8 array of evenly spaced recording sites (each site consisting of 2 pairs of electrodes as described above.
  • Delta dV/dt was calculated as explained above. Any delta dV/dt value less than a threshold value of O.OlmV/ms was considered to be either non-orthogonal, non-contact or both.
  • Multiwavelet reentry (“MWR”) was induced by burst pacing (20ms cycle length for 1 second) from random locations within the tissue. Electrograms and cell voltages were collected during 10s of MWR. Action potential times were detected at each cell and cycle lengths between activations were identified. Tissue activation frequency (TF) was calculated as the inverse of the average cycle-length during the recorded 10s episode of MWR.
  • the electrode closest to the tissue was identified by the electrogram with the highest magnitude of its time derivative (sharpest peaks).
  • Bipolar electrograms were created at each location using the electrogram of the closest electrode and subtracting the electrogram recorded from the electrode on the opposite side of the cylindrical catheter shaft. Bipolar electrograms were then filtered using a low pass filter (75Hz cutoff frequency) to remove high frequency noise. Peaks were identified as the zero crossings of the time derivative of the electrogram signal.
  • catheters include electrodes placed on opposite sides of a cylindrical spline and these splines can rotate relative to the plane of the tissue surface.
  • Orthogonality relative to the plane of the tissue surface has the best spatial resolution compared with other electrode orientations, (Thompson, N. C, et al., Improved Spatial Resolution and Electrogram Wave Direction Independent with the Use of an Orthogonal Electrode Configuration, Journal of Clinical Monitoring and Computing, in press (2013)), and that spatial resolution affects the accuracy of electrogram frequency mapping. Benson, B.
  • Electrograms were recorded using virtual electrodes as described above and shown in FIG. 71B.
  • Electrograms were recorded as the virtual catheter was rotated in 15° increments 711, 714, 715, 716.
  • the catheter 717 was oriented such that one electrode 710 was facing directly downward towards the tissue surface 713 making the opposite electrode orthogonal to the tissue. After each reading, the electrodes were rotated 711, 714-716.
  • Electrograms were recorded in each catheter position 711, 714, 715, 716, and electrogram frequency was calculated and compared to local cellular activation frequency such that the impact of catheter rotation on the correlation between tissue and electrogram frequency could be assessed.
  • I l l - use analysis of electrograms to determine whether the electrodes were orthogonal at the time of electrogram acquisition.
  • frequency mapping during atrial fibrillation can identify the areas of highest circuit core density, i.e. identify the sites responsible for perpetuation of the arrhythmia. Therefore, a series of experiments were performed to demonstrate that the delta dV/dt method for identifying electrode tissue contact improves the accuracy of frequency mapping.
  • Electrogram frequency was calculated at each site (as described above) and the average correlation from at all 64 sites was assessed. Average correlation was then measured excluding electrodes that were placed > 2mm above the tissue.
  • electrogram frequency mapping can identify tissue frequency and that this in turn can identify the tissue sites that are responsible for perpetuating atrial fibrillation.
  • the height of the electrode above the tissue can also reduce the accuracy of electrogram frequency mapping.
  • Tissue frequency during atrial fibrillation varies with circuit core density, hence the need for/value of, frequency mapping.
  • the range of frequencies can be on the order of l-3Hz. Because frequency can vary the same amount due to changes in tissue frequency, and therefore circuit core density, and changes in electrode height or rotation one must confirm that the electrodes are orthogonal and in contact with the tissue in order to unambiguously determine that electrogram frequency variation is due to tissue frequency variation, that is, in order to avoid false positive high frequency sites or false negative low frequency sites on the map.
  • FIGS. 73 A-73D show the effect of catheter rotation on the correlation between bipolar electrogram frequency and the activation frequency of the tissue immediately beneath the catheter.
  • tissue frequency TF
  • EF electrogram frequency
  • FIG. 73 A shows TF plotted against EF when the catheter is in contact with the tissue and rotated from orthogonal (0°) top left, to 15° top right, 30° bottom left and 45° bottom left.
  • FIG. 73B shows TF plotted against EF when the catheter is 2mm above the tissue and rotated from orthogonal (0°) top left, to 15° top right, 30° bottom left and 45° bottom left.
  • FIG. 73C shows TF plotted against EF when the catheter is 4mm above the tissue and rotated from orthogonal (0°) top left, to 15° top right, 30° bottom left and 45° bottom left.
  • FIG. 73D shows TF plotted against EF when the catheter is 6mm above the tissue and rotated from orthogonal (0°) top left, to 15° top right, 30° bottom left and 45° bottom left.
  • FIGS. 73A-73D illustrate, additional height from contact with tissue and rotation away from orthogonal decreases the correlation between electrogram and tissue frequency.
  • a delta dV/dt threshold of 0.01 mV/ms was therefore selected for identifying contact/orthogonality.
  • FIG. 74 shows map accuracy with and without correcting for electrode height.
  • the bars indicate the correlation between electrogram and tissue frequency when analyzing all electrode data (unfiltered), only those electrodes that are measured to be ⁇ 2mm above the tissue ( ⁇ 2mm ) or including only those electrodes in which delta dV/dt signal processing determined that height and rotation was ⁇ 2mm ("delta dV/dt"). Electrogram and tissue frequency were measured during atrial fibrillation with electrodes palced at random heights and rotations.
  • FIG. 75 shows the correlation between tissue and electrogram frequency during atrial fibrillation using electrodes with various heights and degrees of rotation. As shown in FIG. 75, five different tissues were studied. The three bars for each experiment depict all electrodes, exclusion of electrodes above 2mm using delta dV /dt and excluding electrodes measured to be above 2mm. This figure indicates that map accuracy is improved when excluding data from electrodes that are not in adequate contact with the tissue as measured either physically (height) or by deducing the tissue height using the methods described herein.
  • FIG. 76 is a close up on one activation, and shows electrograms as a function of height above the tissue. As shown in FIG. 76, unipolar electrograms from electrodes at varied height above the tissue were recorded during organized propagation. The amplitude decreases and dV/dt decreases as the electrode is elevated off the tissue.
  • FIG. 77 shows a first derivative of electrograms (dV/dt) measured at various heights above the tissue. Unipolar electrograms from electrodes at varied height above the tissue recorded during organized propagation. In this figure, the maximum negative dV/dt is marked with stars. As shown in FIG. 77, the dV/dt changes with height.
  • FIG. 78 shows dV/dt as a function of height above the tissue. Specifically, it shows the average maximal negative amplitude of the first derivative of electrograms versus the height of the electrodes above the tissue. As illustrated in FIG. 78, if the maximum negative dV/dt is measured and plotted as a function of height, the mean peak dV/dt falls off quickly as height is increased. Because the mean peak dV/dt decreases non-linearly, i.e. the decrease from l-2mm above the tissue is much larger than the decrease from 2-3mm, which in turn is much larger than the decrease from 3-4mm, one is able to distinguish how high the electrodes are above the tissue.
  • FIG. 79 shows the delta dV/dt as a function of height above the tissue. Specifically, it shows the difference in average maximal negative amplitude of the first derivative of electrograms from two orthogonal electrodes (delta dV/dt) versus the height of the electrodes above the tissue. Recorded during organized propagation. As illustrated in FIG. 79, as the height increases, the delta dV/dt falls off quickly.
  • FIG. 81 shows dV/dt as a function of height above the tissue during MWR.
  • FIG. 91 shows examples of the first derivative of unipolar electrograms recorded from electrodes at various heights above a tissue during atrial fibrillation.
  • the dV/dt changes quite a bit over time due to different heart beats.
  • the dV/dt alone cannot be used to assess electrode height above the tissue.
  • Factors such as wave collision, wave curvature and velocity, all of which vary during AF, all effect dV/dt. Since these factors cannot be isolated accounted for separately dV/dt alone is not sufficient to determine the height of the electrode above tissue.
  • FIG. 83 shows a plot of the first derivative of a unipolar electrogram (dv/dt) recorded during atrial fibrillation versus electrode height above the tissue surface.
  • FIG. 84 shows a plot of the difference in average maximal negative amplitude of the first derivative of electrograms from two orthogonal electrodes (delta dV/dt) versus the height of the electrodes above the tissue during atrial fibrillation.
  • delta dV/dt falls off quickly, meaning that the disclosed methods for determining electrode tissue contact may be used even during atrial fibrillation.

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US11844616B2 (en) 2019-08-13 2023-12-19 Biosense Webster (Israel) Ltd. Enhanced visualization of organ electrical activity

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US11844616B2 (en) 2019-08-13 2023-12-19 Biosense Webster (Israel) Ltd. Enhanced visualization of organ electrical activity

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