CN106725448B

CN106725448B - System and method for mapping electrophysiological information onto complex geometries

Info

Publication number: CN106725448B
Application number: CN201611107434.7A
Authority: CN
Inventors: E·J·沃斯
Original assignee: St Jude Medical Atrial Fibrillation Division Inc
Current assignee: St Jude Medical Atrial Fibrillation Division Inc
Priority date: 2006-05-17
Filing date: 2007-05-15
Publication date: 2020-01-31
Anticipated expiration: 2027-05-15
Also published as: CN101443792A; CN106725448A

Abstract

The invention relates to an electrophysiology apparatus (8) and a method for measuring electrical activity occurring in a portion of tissue of a patient (11) and for visualizing the electrical activity and/or information related to the electrical activity. More particularly, the present invention relates to three-dimensional mapping of the electrical activity and/or information related to the electrical activity.

Description

System and method for mapping electrophysiological information onto complex geometries

This application is a divisional application of the chinese patent application having application number 200780017743.8 entitled "system and method for mapping electrophysiological information onto complex geometries".

Cross reference to related applications

This application claims benefit of U.S. provisional patent application 60/800,848 (abbreviated' 848 application), filed 2006, 5, 17. This application also claims benefit of currently pending U.S. application 11/647,276 (abbreviated' 276 application), filed 2006, 29/12. The entire contents of both the '848 and' 276 applications are incorporated by reference into this application as if fully set forth herein.

The following co-pending applications are all hereby incorporated by reference in their entirety as if fully set forth herein: us application 11/227006 filed on 9/15 2005; 10/819027 filed 4/6/2004; 11/647275 filed on 29/2006 of U.S. provisional application, 8/2006, entitled to benefit from 60/800858 filed on 17/5/2006; and 11/647298 filed on 29/2006 (which is a partial continuation of us provisional 11/139908 filed on 27/2005 which claims the benefit of us provisional 60/575411 filed on 28/5 2004) which claims the benefit of us provisional 60/851042 filed on 12/10/2006.

Background

Technical Field

The present invention relates to an electrophysiology apparatus and method for measuring electrical activity occurring in a portion of a patient's tissue and for visualizing the electrical activity and/or information related to the electrical activity. More particularly, the present invention relates to three-dimensional mapping of the electrical activity and/or information related to the electrical activity.

Background

The present invention relates to generating electrophysiology maps of human anatomy, including, for example, electrophysiology maps of the human heart.

Existing conventional modeling systems use techniques such as CT scanning, MRI, radar imaging, X-ray imaging, and fluoroscopic imaging to produce a three-dimensional model of the heart. Three-dimensional modeling techniques are typically used to process this data. The imaging technique is generally useful in preparing a patient for treatment and/or surgery, and the imaging procedure is typically performed hours and in some cases days prior to treatment and/or surgery.

During this treatment and/or surgery, an electrophysiology map for the patient can be generated using conventional systems. Electrophysiology maps are particularly useful in conjunction with the diagnosis and treatment of atrial fibrillation of a patient's heart. The points at which the electrophysiology data is measured rarely correspond to data points defining a three-dimensional model prepared prior to treatment.

Accordingly, improvements are needed that allow electrophysiological data to be correlated with a three-dimensional surface model of a patient's anatomy.

Disclosure of Invention

The present invention expands upon the existing capabilities of cardiac electrophysiology mapping systems by providing the ability to directly map electrophysiology measurements to previously acquired three-dimensional images.

The present invention provides the ability to utilize high resolution image data in conjunction with electrophysiological measurements taken during treatment. Thus, the present invention allows for a combination of different techniques for improved treatment.

The foregoing and other aspects, features, details, utilities, and advantages of the present invention will be apparent from reading the following specification and claims, and from reviewing the accompanying drawings.

Embodiments of the present invention provide methods for mapping electrophysiology information onto a three-dimensional model, including the steps of A) obtaining a three-dimensional model of at least a portion of a heart including location information for a plurality of location points on a surface of the heart, B) obtaining a cardiac electrophysiology map including location information for the plurality of measurement points and electrophysiology measurements made at each of the plurality of measurement points, C) selecting a location point from the plurality of location points in the three-dimensional model and determining two closest measurement points from the cardiac electrophysiology map, D) defining a Delaunay edge between the two measurement points determined to be closest to the selected location point, repeating steps C) and D for each of the plurality of location points in the three-dimensional model for defining a plurality of Delaunay edges connecting at least 34 of the plurality of measurement points in the cardiac electrophysiology map, F) connecting the Delaunay edges to form a plurality of triangles, and G) identifying a plurality of location points from the three-dimensional model wherein the identified locations points include identifying a plurality of vertices 56 and assigning the measured electrophysiology measurements at each of the triangle .

The method optionally further includes assigning a color or grayscale to each individual location points of the plurality of location points in the three-dimensional model based on the relative magnitudes of the electrophysiology levels assigned to the individual location points, and rendering the three-dimensional model using the colors assigned to the plurality of location points in the three-dimensional model if electrophysiology levels have been assigned to the plurality of location points.

Optionally, the step of obtaining an electrophysiology map of the heart further includes inserting an electrode in a portion of the heart, positioning the electrode at a plurality of measurement points along a surface of the heart, receiving location information for each of the plurality of measurement points along the surface of the heart, receiving an electrophysiology measurement at each of the plurality of measurement points, and associating the electrophysiology measurement with a respective measurement point at which the electrophysiology measurement is measured.

Optionally, the step of obtaining a three-dimensional model of at least a portion of the heart further comprises inserting an electrode in the portion of the heart, positioning the electrode at a plurality of location points along a surface of the heart, receiving location information for each of the plurality of location points along the surface of the heart, and generating a three-dimensional model of at least a portion of the heart, the three-dimensional model comprising location information for each of the plurality of location points along the surface of the heart.

Optionally, the step of obtaining a three-dimensional model of at least a portion of a heart further comprises inserting an electrode in the portion of the heart, positioning the electrode at a plurality of position points along a surface of the heart, receiving position information for each of a plurality of position points along the surface of the heart, generating a preliminary three-dimensional geometry of at least the portion of the heart comprising position information for each of a plurality of position points along the surface of the heart, and processing the preliminary three-dimensional geometry to generate the three-dimensional model comprising position information for each of a second plurality of position points, wherein the second plurality (position points) comprises at least position points from the plurality .

Optionally, the step of processing the preliminary three-dimensional geometry to generate the three-dimensional model may include processing the preliminary three-dimensional geometry to generate the three-dimensional model having location information for every of the second plurality of location points, wherein the three-dimensional model has a higher resolution than the preliminary three-dimensional geometry such that the second plurality of location points is greater in number than the th plurality of location points.

Optionally, the steps of selecting a location point from the plurality of location points in the three-dimensional model and determining the two closest measurement points from the cardiac electrophysiology map may further comprise selecting a location point from the plurality of location points in the three-dimensional model and using a Kirsanov-Hoppe geodesic algorithm to determine the two measurement points in the cardiac electrophysiology map that are closest in distance to the selected location point. Further, the step of connecting the delaunay edge to a triangle may further comprise generating additional triangles using measurement points that have not yet been connected to the delaunay edge.

Optionally, the steps of selecting a location point from the plurality of location points in the three-dimensional model and determining the two closest measurement points from the cardiac electrophysiology map may comprise selecting a location point from the plurality of location points in the three-dimensional model and using a Fast-Marching geodesic algorithm to determine the two measurement points in the cardiac electrophysiology map that are closest in distance to the selected location point.

According to another embodiment of the present invention, methods for mapping electrophysiology information onto a three-dimensional model are provided, including the steps of A) acquiring a three-dimensional model of at least a portion of a heart including location information of a plurality of location points on a surface of the heart, B) acquiring a cardiac electrophysiology map including location information of a plurality of measurement points and electrophysiology measurements achieved at every of the plurality of measurement points, C) selecting a location point from the plurality of location points in the three-dimensional model and determining two measurement points closest to the selected location point from the cardiac electrophysiology map, D) defining a Delaunay (in Delaunay) edge between the two measurement points determined to be closest to the selected location point, E) repeating steps C) and D for every of the plurality of location points in the three-dimensional model for defining at least of the plurality of measurement points in the cardiac electrophysiology map connecting the plurality of measurement points, F) connecting the inner edges to generate a new electrophysiology points and assigning at least three-dimensional coordinates of the measured locations at least three-dimensional model based on the determined electrophysiology measurements at least one of the triangle apex, and at least one of the triangle interpolation points, and at least one of the triangle insert 3663, and wherein the determined at least one of the three-dimensional model is assigned at least one of the measured electrophysiology points.

According to yet another embodiment of the present invention, there is provided systems for mapping electrophysiology information onto a three-dimensional model, including a modeling processor for generating a three-dimensional model of at least a portion of a heart including location information for a plurality of location points on a surface of the heart, an electrophysiology measurement device for generating a cardiac electrophysiology map including location information for a plurality of measurement points and electrophysiology measurements taken at each of the plurality of measurement points, the electrophysiology measurements being associated with respective measurement points of the measured electrophysiology measurements, a delaunay edge processor for processing a subset of the plurality of location points in the three-dimensional model and for each location points processed, determining two measurement points in the cardiac electrophysiology map that are closest in distance to the location point processed, the processor defining a plurality of delaunay edges, each delaunay edge including a pair of measurement points determined to be closest to the location point processed per , a triangulation processor for determining a plurality of delaunay edges based on the electrophysiology vertices of the plurality of the electrophysiology maps and a plurality of the electrophysiology vertices located in a triangle projection relationship using at least a plurality of triangles 6778.

Optionally, the processor assigns electrophysiology levels to at least location points located within a proximity threshold of a delaunay edge based on bilinear interpolation using electrophysiology measurements measured at endpoints of the delaunay edge.

Optionally, the processor further assigns the electrophysiology levels to at least location points based on the electrophysiology measurements measured at the measurement points that are within the proximity threshold, wherein the assigned electrophysiology levels are the same as the electrophysiology levels at the measurement points.

According to another embodiment of the present invention, there is provided a method for mapping electrophysiological information onto a three-dimensional model, comprising the steps of A) obtaining a three-dimensional model of at least a portion of a heart including location information for a plurality of location points on a surface of the heart, B) obtaining a cardiac electrophysiology map including location information for a plurality of measurement points and electrophysiology measurements made at each of the plurality of measurement points, C) selecting a location point from the plurality of location points in the three-dimensional model and determining two closest measurement points from the cardiac electrophysiology map, D) defining an edge between the two measurement points determined to be closest to the selected location point, E) repeating steps C) and D for each of the plurality of location points in the three-dimensional model for defining a plurality of edges connecting at least of the plurality of measurement points in the cardiac electrophysiology map, F) connecting the edges to generate a plurality of three-dimensional polygons, and G) identifying from the plurality of location points of the three-dimensional model wherein the identified edges surround of the plurality of measurement points and wherein the identified polygon is divided into at least 64 the identified polygon based on the measured electrophysiology measurements.

According to yet another embodiment of the present invention, there is provided a system for mapping electrophysiology information onto a three-dimensional model, comprising a surface modeling controller for obtaining a three-dimensional model of at least a portion of a heart including location information for a plurality of location points on a surface of the heart, an electrophysiology measurement device for generating a cardiac electrophysiology map including location information for a plurality of measurement points and electrophysiology measurements taken at each of the plurality of measurement points, the electrophysiology measurements being associated with respective measurement points of the measured electrophysiology measurements, an edge processor for processing a subset of the plurality of location points in the three-dimensional model and determining, for each processed location point, two measurement points in the cardiac electrophysiology map that are closest in distance to the processed location point, the processor defining a plurality of edges, each edge including a pair of measurement points determined to be closest to each location point processed, a geometry processor for defining a plurality of edges in the centered electrophysiology map based on the plurality of edges, and a polygon map and assigning at least 64 polygon points based on the associated with the plurality of vertices and wherein the polygon map and the plurality of vertices are located at least 3875 polygon of the processed location points.

Optionally, the processor further assigns electrophysiology levels to at least location points located near an edge based on bilinear interpolation using the electrophysiology measurements measured at the endpoints of the edge.

The mapping projector assigns electrophysiology levels based on interpolation to at least location points located in of the triangles using electrophysiology measurements associated with each vertices of the triangles.

According to a further embodiment of the invention, there is provided computerized methods for mapping electrophysiology information onto a three-dimensional model, including the steps of A) receiving a three-dimensional model of at least a portion of an anatomy including location information for a plurality of location points on a surface of the anatomy, B) receiving an electrophysiology map for the anatomy including location information for the plurality of measurement points and electrophysiology measurements made at each of the plurality of measurement points, C) for each individual location points of the plurality of location points in the three-dimensional model, using a computer to determine two measurement points from the electrophysiology map that are closest to the individual location point and then define an edge that includes a pair of the determined measurement points, D) using a computer to connect the edges to form a mesh of closed polygons, E) using a computer to identify location points from the three-dimensional model located on a closed polygon surface of the edges around the identified location points, wherein the computer uses each of the plurality of measured locations at vertices of the edges around the identified location points and assigns the measured electrophysiology output points to a horizontal file based on the electrophysiology output of the plurality of locations.

According to another embodiment of the invention, a method for mapping electrophysiological information onto a three-dimensional model is provided that includes the steps of A) obtaining a three-dimensional model of at least a portion of a heart including location information for a plurality of location points on a surface of the heart, B) obtaining an electrophysiological map of the heart including the location information for a plurality of measurement points and electrophysiological measurements taken at each of the plurality of measurement points, C) processing the three-dimensional model using triangulation to produce a subdivided three-dimensional model including a plurality of triangles in which each of the plurality of measurement points are vertices, and D) processing the subdivided three-dimensional model using a decimation algorithm to produce a revised three-dimensional model including a second plurality of triangles in which each of the plurality of measurement points are vertices of a triangle.

Optionally, the triangulation processing step is programmed to inhibit the generation of triangle edges longer than a predetermined distance threshold.

The present embodiment may further comprise the step of projecting electrophysiological measurements of the measurement points to the vertices or edges of the subdivided three-dimensional model using a Kirsanov-Hoppe or Fast Marching geodesic algorithm.

Optionally, the present embodiment may further comprise the step of assigning a color or grayscale to each vertices of the revised three-dimensional model based on the relative magnitude of the assigned electrophysiology levels, and rendering the revised three-dimensional model using the colors assigned to the plurality of vertices in the revised three-dimensional model.

Drawings

FIG. 1 is a schematic diagram of a system for performing a cardiac electrophysiology exam or ablation procedure, wherein the location of or more electrodes may be determined and recorded;

FIG. 2 is a schematic representation of a heart examined by an electrophysiology catheter having a plurality of distal electrodes;

FIG. 3 is a schematic diagram of an exemplary method of providing a surface of a heart chamber using recorded electrode location data points;

FIG. 4 is a schematic depiction of a graphical user interface for displaying an electrocardiogram and associated electrophysiological information to a physician;

FIG. 5 is an enlarged view of the panel 66 depicted in FIG. 4;

FIG. 6 shows side-by-side views of time-varying electrograms collected at different locations along the wall of the heart;

FIG. 7 shows side-by-side views of time-varying electrograms collected at different locations along the wall of the heart;

FIG. 8 shows a side-by-side comparison of electrograms of typical compact and fibrillar myocardial muscle tissue in the time and frequency domains;

FIG. 9A illustrates a side-by-side comparison of time domain and frequency domain information of an electrogram;

FIG. 9B illustrates a side-by-side comparison of time domain and frequency domain information of an electrogram, with cross-hatching to illustrate energy in multiple spectral bands;

FIG. 10 illustrates a method of collecting electrograms and mapping time domain and/or frequency domain electrogram information onto a three-dimensional model;

FIG. 11 illustrates a three-dimensional model of a portion of the heart, here again showing the same color version of FIG. 11 (no reference numeral);

FIG. 12 illustrates a graph of electrophysiological data for the same portion of the heart shown in FIG. 11, also here showing the same color version (no reference numeral) of FIG. 12;

FIG. 13 includes the three-dimensional model of FIG. 11 with distance lines drawn from midpoints measured using FIG. 12, again showing the same color version of FIG. 13 (no reference numeral);

fig. 14 shows a voltage diagram of the same part of the heart shown in fig. 11, wherein the electrophysiology data map from fig. 12 has been projected onto the three-dimensional model of fig. 11, here again showing the same color version (without reference numerals) of fig. 14.

Detailed Description

The present invention improves system capabilities to produce improved electrophysiological mapping of the anatomy. The present invention is not limited to generating an accurate model of the heart, but for illustrative purposes reference will generally be made herein to a navigation and positioning system for evaluation and treatment of cardiac tissue. The methods described herein are equally applicable to the modeling of other parts of the human anatomy. For the purpose of illustrating the present invention, techniques for generating an electrophysiology map of cardiac tissue will be described below.

There are a number of conventional systems for generating three-dimensional models of the heart, including systems using techniques such as CT scanning, MRI, ultrasound imaging, radar imaging, X-ray imaging, and fluoroscopic imaging. The output of this data may be a plurality of x-y-z data coordinates, spherical coordinates, and/or other formats for providing a three-dimensional image. These imaging techniques are commonly used in diagnostics, as well as in preparation for treatment and/or surgery of a patient. Sometimes, the imaging procedure is performed hours and in some cases days before the treatment and/or surgery.

Of course, the three-dimensional model may use a piecewise approximation, such as a CT or MRI scan image that includes the segmentation. The segmented model illustrates that the partitions of the three-dimensional image have been digitally separated from the larger three-dimensional image, e.g., the image of the right atrium separated from the rest of the heart. Other methods and techniques for generating a three-dimensional model of a portion of a patient may also be used in accordance with the present invention, including, for example, the methods and techniques disclosed in U.S. patent 6728562 (the' 562 patent), the entire contents of which are incorporated herein by reference.

Additional other techniques for generating a three-dimensional model of the anatomy are discussed further below.

The available techniques for generating electrophysiology maps are discussed below in connection with FIG. 1, FIG. 1 showing a schematic diagram of a localization system 8, the system 8 conducting a cardiac electrophysiology study by navigating cardiac catheters and measuring electrical activity occurring in a heart 10 of a patient 11, and three-dimensionally mapping the electrical activity and/or information related to or characterizing the electrical activity. the system 8 may be used to facilitate generation of an anatomical model using or more electrodes. the system 8 may also be used to measure electrophysiology data at multiple points along the surface of the heart and store the measured data in association with location information for each measurement points at which the electrophysiology data is measured.

For simplicity, the patient 11 is depicted schematically as an oval, three sets of surface electrodes (e.g., patch electrodes) are shown applied to the surface of the patient 11 along the X, Y, and Z axes the

X-axis surface electrodes

12, 14 are applied to the patient along the th axis, such as on the sides of the chest region of the patient (e.g., to the skin under each arm of the patient) and may be referred to as left and right electrodes the Y-

axis electrodes

18, 19 are applied to the patient along a second axis generally perpendicular to the X axis, such as along the medial thigh and neck regions of the patient and may be referred to as left leg and neck electrodes, the Z-

axis electrodes

16, 22 are applied along a third axis generally perpendicular to the X and Y axes, such as along the sternum and spine of the patient in the chest region and may be referred to as chest and back electrodes, the heart 10 is located between these pairs of surface electrodes, an additional surface reference electrode (e.g., "belly patch" 21) provides a reference for the ground electrode for the system 8 and/or a belly patch 21 is an alternative to the fixed intracardiac electrode 31.

In a preferred embodiment, the location/mapping system is the EnSite of St.Jude Medical, atomic fibre division, Inc

Navigation and visualization systems, however, other positioning systems may be used in connection with the present invention, such as the CARTO navigation and positioning system including Biosense Webster, Inc and the locaisa intra-cardiac navigation system of Medtronic, Inc the positioning and mapping systems described in the following patents, all of which are incorporated herein by reference, may be used with the present invention , U.S. patents 6990370, 6978168, 6947785, 6939309, 6728562, 6640119, 5983126 and 5697377.

Also shown is a representative catheter 13 having at least electrodes 17 (e.g., distal electrodes). The representative catheter electrode 17 shown is referred to throughout the specification as a "roving electrode" or "measuring electrode". typically, multiple electrodes on the catheter 13 or on multiple such catheters will be used.e., in embodiments, the system 8 may include up to 64 electrodes on up to 12 catheters disposed within the patient's heart and/or vasculature.

Also shown on the second catheter 29 is an optional fixed reference electrode 31 (e.g., attached to the wall of the heart 10). For calibration, the electrode 31 may be stationary (e.g., attached to or near the wall of the heart) or disposed in a fixed spatial relationship with the roving electrode 17. Fixed reference electrode 31 may be used in addition to or in place of surface reference electrode 21 described above. In various examples, a coronary sinus electrode or other fixed electrode in the heart 10 may be used as a reference for measuring voltage and displacement.

Each surface electrode is coupled to a multiswitch 24 and an electrode pair is selected by software running on computer 20, which couples the electrode to a signal generator 25. for example, computer 20 may comprise a conventional general purpose computer, a special purpose computer, a distributed computer, or any other type of computer 20 may include or more processors, such as a single central processing unit, or multiple processing units, commonly referred to as a parallel processing environment.

In general, three nominally vertical electric fields are generated by the series of driven and induced electric dipoles for achieving catheter navigation in biological conductors.

Thus, any two of the

surface electrodes

12, 14, 16, 18, 19, 22 may be selected as dipole sources and drains with respect to a ground reference (e.g., belly patch 21), while the unexcited electrodes measure voltages with respect to the ground reference the measurement electrodes 17 disposed in the heart 10 are exposed to fields from current pulses and measure with respect to ground (e.g., belly patch 21). in practice, a catheter in the heart may include multiple electrodes and may measure potentials per electrodes.

One of ordinary skill in the art will readily recognize that the measurement electrodes 17 may also be used to measure electrophysiological data, and that the system 8 may be used to store electrophysiological data (e.g., voltage readings, including without limitation voltage changes over a time period) in association with location information of the measurement points at which the electrophysiological data is measured.

This process of electrode actuation occurs rapidly and sequentially as alternate sets of surface electrodes are selected and the remaining non-driven electrodes are used to measure voltages, this collection of voltage measurements is referred to herein as an "electrode data set".

Raw electrode data is used to determine the "base" position in three-dimensional space (X, Y, Z) of electrodes inside the heart, such as the roving electrode 17, and any number of other electrodes located in or around the heart and/or vasculature of the patient 11 fig. 2 shows the catheter 13 extending into the heart 10, which may be a conventional electrophysiology catheter (sometimes referred to as an "EP catheter"). in fig. 2, the catheter 13 extends into the left ventricle 50 of the heart 10 the catheter 13 includes the distal electrode 17 discussed above with reference to fig. 1 and has

additional electrodes

52, 54, and 56 since every of these electrodes are present in the patient (e.g., located in the left ventricle of the heart), position data may be collected simultaneously for each electrode, furthermore, when the electrode is disposed adjacent to the surface, although not necessarily directly on the surface of the heart, and when the current source 25 is "off" (i.e., when no surface electrode pair is energized), at least of the

electrodes

17, 52, 54, and 56 may be used to measure electrical activity (e.g., voltage) on the surface of the heart 10.

In another embodiments, position data may be collected in synchronization with or multiple phases of the heartbeat or without considering any particular phase of the heartbeat.

The electrode data may also be used to generate breathing compensation values to improve the raw position data of the electrode position, as described in U.S. patent application publication 2004/0254437, which is incorporated by reference herein in its entirety. The electrode data may also be used to compensate for changes in impedance of the patient's body, as described in co-pending U.S. patent application 11/227580 filed on 9, 15, 2005, the entire contents of which are also incorporated herein by reference.

In summary, the system 8 first selects sets of surface electrodes and then drives them using current pulses when delivering current pulses, electrical activity, such as voltage, measured at least of the remaining surface and in vivo electrodes is measured and stored.

Exemplary segmentation applications include ANALYZE (Mayo, Minneapolis, MN), Verismo (St.Jude Medical, Inc., St.Paul, MN), and CardEP (general electric Medical Systems, Milwaukee, Wis.) when a three-dimensional model is generated from location data points collected by system 8, such as during a single procedure by scanning or more electrodes on the surface of the heart, the location points of the data can be used to determine the shape of the outermost volume corresponding to the region of the heart.

Other methods and techniques for generating a three-dimensional model of a portion of a patient may also be used in accordance with The present invention, for example, a convex hull (covex hull) may be generated using standard algorithms such as The Qhull algorithm described in Barber, C.B., Dobkin, D.P., and Huhdanpaa, H.T. "The Quickhull algorithm for covhulls," ACM trans., on physical Software,22(4):469-483, 1996. other algorithms for calculating The convex hull shape are also known and may be applicable in The implementation of The present invention.

FIG. 3 schematically depicts another example method for generating a shell corresponding to the shape of a heart chamber, access location data identifying or more electrodes within the heart chamber over periods of time, the location data may be represented as a point cloud within the heart chamber, such that the farthest location data point 40 corresponds to the inner wall of the heart chamber in a relaxed or diastolic state (corresponding to a maximum volume). by fitting an array of "bins" 44 around sets of location data points 40, providing a shell or surface from the location data, building a bin 44 by determining an average center point 42 within the cloud of location data points 40 and then extending a boundary radially outward from the center point 42. the bin 44 extends to the farthest location data point within a slice enclosed by the bin 44. it should be noted that although FIG. 3 is schematically represented in two dimensions, the bin 44 is a three-dimensional body. thus the radial end surface 46 of the bin 44 approximates the surface of the heart chamber wall.

Another example of using point clouds to generate three-dimensional maps is described in U.S. application 11/647275 filed on day 29, 2006 (which claims the benefit of U.S. provisional application 60/800858 filed on

day

17, 5, 2006 Another techniques for generating three-dimensional maps of tissue surfaces are described in U.S. application 11/647298 filed on day 29, 2006 (which is a partial continuation of U.S. application 11/139908 filed on

day

27, 5, 2005 (which claims the benefit of U.S. provisional application 60/575411 filed on day 28, 5, 2004)) which claims the benefit of U.S. provisional application 60/851042 filed on

day

12, 10, 12, 2006.

The image panel 60 shows a three-dimensional model of the heart chamber 62 to identify regions that simultaneously receive depolarization waveforms, i.e., map to "isochrones" of the model in false colors or gray levels, in variations the isochrones are mapped to three-dimensional coordinates (e.g., X, Y, Z) corresponding to the electrograms they obtain from, the isochrones are also shown with an indication bar 64 as a legend, identify information related to the particular colors or gray levels mapped to the three-dimensional model, in this image the positions of the plurality of three-dimensional electrodes on the catheter are also mapped to the three-dimensional model.

For example, in the variation shown in FIG. 4, the indicator bar 64 is graduated in milliseconds and shows the assignment of a specific time relationship to each color or gray scale mapped to the three-dimensional model the relationship between the three-dimensional model image 62 and the color or gray scale on the indicator bar 64 may also be determined by a user referencing information shown on the panel 66. FIG. 5 shows an enlarged view of the panel 66 depicted in FIG. 4. in this variation, the panel 66 shows timing information for generating an isochrone mapped onto the three-dimensional model 62 shown in FIG. 4. typically, when a fiducial point is selected as "zero". in FIG. 5, for example, the inflection point 70 of the voltage appearing on the reference electrode is used as the base timing point for generating the isochrone. this voltage may be taken from a virtual reference or a physical reference (such as the roving electrode 17 shown in FIG. 1. in this variation, the voltage trace corresponding to the fiducial point is labeled in FIG. 5 with a "REF". the roving electrode signal is depicted in FIG. 5 and labeled with a "ROV". the ROV ". 72 of the voltage signal ROV corresponds to the inflection point 31. the color indicator bar 65 shows the assignment of the color or gray scale and the roving signal assignment, respectively, the roving timing relationship between the roving reference.

The amplitude of the voltage signal ROV corresponding to the roving electrode 17 is also shown on the panel 66 of fig. 5. The amplitude of the time-varying signal ROV is located between two adjustable bands 74 and 76, which can be used to set a selection criterion for the peak-to-peak voltage of the signal ROV. In a particular implementation, the regions of the heart with low peak-to-peak voltages are the result of infarcted tissue, and the ability to convert the peak-to-peak voltages to gray scale, or false color, allows identification of infarcted or atrophic regions. In addition, a time-varying signal "V1" is also shown and corresponds to a surface reference electrode, such as a conventional ECG surface electrode. For example, signal V1 may direct a user (such as a physician) to the same event detected on the surface of the patient.

For example, the time difference of the measured action potentials at the roving electrode and the reference electrode, the peak-to-peak voltage of the measured action potential at the roving electrode, and/or the peak negative voltage of the measured action potential at the roving electrode may be mapped to the three-dimensional model.

The CFE information relates to irregular electrical excitations (e.g., atrial fibrillation), wherein the electrogram includes at least two discrete deviations and/or perturbations of a baseline of the electrogram with a sustained deviation of extended excitation complexity (e.g., greater than a 10 second period), the electrogram with very fast and continuous excitation, e.g., with myocardial preservation with short refractory periods and small reentries, e.g., FIG. 6 shows series electrograms (FIG. 6 and related articles: NADEMANEE, Koonlay, M.D., FACC, et al, 2004, A new approach for diagnosis of atrial fibrillation: the electrogram is shown in series electrogram, and the electrogram with short refractory periods and small reentries, e.g., the electrogram is shown in NADEMANEE, Koonlay, M.D., FACC, et al, A new approach for diagnosis of atrial fibrillation, the electrogram includes three distal electrical activation images and two distal electrical activation images, e.g., the electrogram, and the cardiac retention map include two distal electrical activation images, e.g., three electrical activation images, e.g., a-34, a rapid electrical activation images, a-34, a distal electrical activation, a-7-a lateral electrical activation, a-a lateral electrical activation, a-lateral electrical signal, a-b, a lateral electrical signal, a-a lateral electrical signal, a signal.

The presence of CFE information may be detected from EP information (e.g., electrograms) collected by the electrodes, for example, by monitoring the number of deviations in the electrogram segments, calculating the average time between deviations in the electrogram segments, monitoring the time-varying changes between deviations in the period length of the electrogram, and calculating the slope, derivative, and amplitude of the electrogram.

In diagnosing atrial fibrillation and guiding ablation catheters, electrograms corresponding to physiological mechanisms for initiating and maintaining atrial fibrillation may be identified by quantifying the fragmentation in the electrograms. These quantifications may in turn be used to identify areas to be ablated to remove atrial fibrillation. Mid-diastolic potentials in atrophic regions of the cardiac chamber may also be identified by quantifying the fragmentation of the electrogram collected in the cardiac region. Healthy tissue will correspond to an electrogram without fragmentation (i.e., a single discrete excitation), while unhealthy tissue (e.g., atrophic tissue) will correspond to an electrogram with fragmentation (i.e., multiple discrete excitations and/or perturbations of the baseline). The time of day or other quantification of the CFE information in the electrogram may then be mapped into the three-dimensional model described above.

For example, in embodiments, a Fast Fourier Transform (FFT) or other method of transforming a time-varying signal into frequency-domain information may be used to transform the collected signal into the frequency domain.

FIG. 8 shows a side-by-side comparison of compact and fibrillar myocardial muscle tissue that collectively form the wall of the heart, the compact myocardial muscle tissue comprising groups of tightly connected cells that conduct electrical activity by transmitting electrical activity at the same rate in any direction during depolarization of the heart, however, fibrillar myocardial muscle tissue typically comprises loosely connected cells, such as the transitions between nerves, vessels, and atrial tissue.

In row B, the time domain electrogram signals of compact myocardial muscle tissue and fibrillar myocardial muscle tissue during the depolarization phase of the heartbeat are shown. As shown in fig. 8, the time domain electrogram signal typically includes a biphasic or triphasic shape for compact myocardial muscle tissue (shown in column 1) and a more phasic shape for fibrillar myocardial muscle tissue (shown in column 2). Finally, the frequency domain of the electrogram signals for row B of compact myocardial muscle tissue and fibrillar myocardial muscle tissue is shown in row C. The frequency domain is obtained by performing an FFT on the time period of the time-varying electrograms shown for the compact myocardial muscle tissue of row B column 1 and the fibrillar myocardial muscle tissue of row B column 2. As shown in row C of fig. 8, the frequency spectrum for compact myocardial muscle tissue typically includes a larger amplitude at a single peak around the fundamental frequency, while the frequency spectrum for fibrillar myocardial muscle tissue typically includes a smaller amplitude at its fundamental frequency due to the right shift in frequency caused by the multiple harmonic frequency components.

In this region, the "atrial fibrillation nest" (or "AFIB nest") may be identified as a possible source of atrial fibrillation.

In exemplary variations of The invention, The dominant frequency of The electrogram signal may be identified in The frequency spectrum that has been obtained by FFT, for example, as shown in FIG. 9A, typical normal or dense myocardial tissue may have a single peak in The spectrum, while fibrous myocardial tissue has more spectral peaks (spectral peaks) than dense myocardial tissue, The number of spectral peaks may be determined for a plurality of points around The wall of The heart on The three-dimensional model as described above (FIGS. 7-9A and related articles: PACHON, Jose, C, et al, A new for actual fibrous tissue analysis, A < 2004 > for fibrous tissue analysis, a < 11 > and related articles, 601, C, 590, A < 601 > A < 1 > A </601 > A < 1 > A </601 > A < 2 > A </601 < A > A </601 < A > A </601 < A > of < A </601 < A > of < A < 1 > of <

For example, in FIG. 9A, it can be seen that the maximum peak amplitude of compact myocardial muscle tissue at dominant frequency is higher, approximately 175dB mV, while the maximum peak amplitude of fibrillar myocardial muscle tissue at dominant frequency is lower, approximately 80dB mV., values that can also be mapped onto the three-dimensional model of the heart.

In yet another variations, the ratio of the energy of a band of the frequency domain to the energy of a second band of the frequency domain can be determined and mapped to a three-dimensional model of the heart, for example, FIG. 9B shows the ratio of energy in the pass band of 60-240Hz and energy below 60Hz, with the ratio in the spectrum of the electrogram for fibrillar myocardial muscle tissue being greater than the ratio in the spectrum of the electrogram for compact myocardial muscle tissue.

While examples of time domain and frequency domain information that can be converted into a three-dimensional map of a patient's heart have been described herein, one of ordinary skill in the art will recognize that other time domain and frequency domain information may also be determined and mapped to a three-dimensional model, for example, information from the time domain or frequency domain may be determined and mapped to a three-dimensional model for low or high frequency passbands of interest (e.g., in Hz), frequencies with the greatest energy in the passbands (e.g., in Hz), multiple peaks in the passbands (e.g., counts), energy, power and/or area per peak (e.g., in dB), ratios of energy and/or area per peak and energy and/or area per peak in another passband, and widths per peak in the spectrum (e.g., in Hz).

FIG. 10 shows examples of methods for determining information from a time-varying electrogram in the time domain and/or frequency domain and for mapping the information to a three-dimensional model (e.g., a heart). in operation 100, a plurality of electrodes (e.g., contact or non-contact, mono-polar or bi-polar mapping electrodes) are used to sample a time-varying electrogram signal.

An FFT is then performed at operation 102 over a time period of the time-varying electrogram to determine frequency domain information of the electrogram, in operation 104, a real-time display of the time domain and/or frequency domain information may be displayed, in operation 106, a plurality of parameters are then determined, the exemplary parameters described above and including, for example, a time difference between the roving electrode and the reference electrode, a peak-to-peak voltage of the roving electrode, a peak negative voltage of the roving electrode, CFE information, a dominant frequency of the electrogram signal, a maximum peak amplitude at the dominant frequency, a ratio of energy and/or area in a frequency domain band to energy in a second band in the frequency domain, a low or high frequency passband of interest, a frequency with maximum energy in the passband, a plurality of peaks in the sum frequency spectrum, an energy, power and/or area per peak, a ratio of energy and/or area per peak to energy and/or area per 3929 peak in the other passbands, a width of the peak in the sum frequency spectrum, a width of the peak, a light color and/or a color of the operation 108 and/or color of the electrode is identified and updated by, for example, a light gray scale parameter, a gray scale, a color, and/or color of the electrode, and/or a color of the electrode is assigned to a continuous gray scale, in the real-time model, and/or color of the heart, and/or a corresponding to the heart.

The starting point of the electrical signal is typically the autonomic cell bundle or nerve center plexus (ganglia plexi.) for the extent of any arrhythmia induced by a malfunction in autonomic cells, the ability to detect for this malfunction can significantly enhance the therapeutic effect and minimize the extent of the treatment.

As described above, electrophysiological data can be very useful in locating tissue in need of treatment. But presents challenges for mapping the electrophysiology data onto a three-dimensional model of the heart. The projection process according to the invention will now be described.

The set of location points and associated measurements is referred to herein as the "EP data set" this data is then projected onto the surface of the three-dimensional model corresponding to the electrode location at which the sampled EP data was acquired because the model was not generated when the locating surface electrodes were powered up, the projection process may be used to place the electrical information onto the closest heart surface represented by the geometric shape.

The EP data points are projected onto the three-dimensional model for display because the points at which the EP data is measured may not be the same set as the physical location for generating the three-dimensional model, the EP data must be projected onto the surface of the three-dimensional model, in this preferred embodiment, the EP data values (peak voltage, excitation time, maximum frequency, or other magnitude) must also be interpolated onto the points of the three-dimensional geometry, . the EP data may be projected onto the three-dimensional model, converted to color and presented according to standard computer graphics techniques, the method of relating the three-dimensional model to the EP data structure must be determined, for a number of surface interpolation problems, it is desirable to generate a good subdivision of the subdivision' which is connected to a triangle filling the x-y plane (2-dimensional) and then a smooth weighted average of the three end points of this triangle, the data values of any point within the triangle may be approximated by a well-known centroid interpolation, but it is understood that it may not exist, it is connected to a well-known triangulation of the triangle which fills the x-y plane (2-dimensional) and then the triangle may be approximated by a well-known triangulation algorithm, and the triangle may be generated by a well-known triangulation algorithm, and the use a well-known triangulation algorithm, it is known per-known that the vertex map found that the vertex map of this triangle, and the two mesh, the mesh model, the mesh.

The embodiments described in the preceding paragraph will be discussed in the context of FIGS. 11-14, FIG. 11 is a three-dimensional model of a portion of the heart where the location points 91 have been connected using triangulation, the surface may be resampled on a more uniform grid and may be interpolated further to steps to give a reasonably smooth surface, stored as a three-dimensional model for display to the physician during the same or a later procedure.

Fig. 12 shows an EP data set comprising series of measurement points 93, each measurement point having a corresponding voltage level, indicated by the label 92, the color of the label 92 being changed for displaying the voltage level.

It will be appreciated that the EP data set depicted in FIG. 12 is the same as the overall geometry of FIG. 11, and it can be observed that the measurement points 93 of the EP data set do not correspond to the location points 91 of the three-dimensional model, although generated using the same regions of the same heart, lack the location correspondence of pairs , which creates a need to project the measured EP data onto the three-dimensional model to aid in the projection process, location points 91 are selected from a plurality of location points 91 comprising the three-dimensional model of FIG. 11. next, the locations of the selected location points 91 are compared to the locations of at least subsets of the plurality of measurement points 93 for determining the two measurement points 93 that are closest to the selected location points 91. this closest measurement point pair is considered to form a Deloson edge 94 (which is drawn in green on FIG. 12), it is likely that the identified pair of closest measurement points 93 is a Vooi. any number of algorithms designed for estimating distance can be used (including such algorithms as Kirsanov-Hoppzing or Marsting) to identify the closest measurement points to the most likely to form a triangle if the shortest distance between the selected location points is identified by the algorithm, the shortest distance of the most likely to be the shortest distance-forming a triangle, the most likely to be identified by the algorithm, the length of the remaining triangle, the shortest of the selected triangle, the most likely to be identified by the algorithm , the most likely to be identified by the algorithm, the most likely to be used to form the shortest distance of the most likely to form the most likely to be the.

This relationship is graphically illustrated in both fig. 12 and 13 when the proximity relationship between the selected location point 91 and its respective pair of closest measurement points 93 can be tracked using a variety of methods, hi fig. 12, the midpoints 95 of most delaunay edges have at least and typically a plurality of lines (which are illustrated in dark, red ink) in contact with the midpoints 95, these lines represent connections to a plurality of location points in the three-dimensional model, the presence of a line to a particular location point means that for that particular location point, the closest measurement point pair is determined to be the pair that forms the identified delaunay edge, the same red lines are illustrated in fig. 12 and 13, but with delaunay edges as illustrated in fig. 12 and with a three-dimensional model as illustrated in fig. 13, fig. 13 includes the three-dimensional model of fig. 11, with distance lines added thereto for identifying the relationship between the selected location point in the three-dimensional model and the delaunay edge closest to the selected location point.

The actual projection of EP data values is described below, every location point in the three-dimensional model is accessed relative to the triangles that have been used to model the EP data set, theoretically, if the three-dimensional model is added to the triangulated model of the EP data set, the relationship between the location point and the triangle is more easily observed, most location points 91 will be inside of the triangles of the triangulated model of the EP data set, and the EP data values assigned to the location points 91 can be interpolated using barycentric interpolation based on the measurements of the three vertices of the triangle (measurement locations 93). barycentric interpolation is known in the art and is preferred.

In yet another embodiment, the three-dimensional model is subdivided using triangulation in such a way that all EP data point vertices are in the subdivided three-dimensional model, then the subdivided three-dimensional model can be processed using mesh-coarsening or an extraction algorithm (allowing one to specify a set of output vertices that will be specified as just the set of EP data points).

While various embodiments of the present invention have been described above with a certain degree of particularity, in , it is to be understood that various changes to these disclosed embodiments may be made by those skilled in the art without departing from the spirit or scope of the invention.

Claims

1, a system for mapping electrophysiological information onto a three-dimensional model, the system comprising:

a modeling processor for generating a three-dimensional model of at least a portion of the heart, the three-dimensional model including positional information for a plurality of location points on a surface of the heart;

an electrophysiology measurement device to generate a cardiac electrophysiology map that includes location information for a plurality of measurement points and electrophysiology measurements made at every of the plurality of measurement points, the electrophysiology measurements being associated with respective measurement points at which the electrophysiology measurements were measured;

a delaunay edge processor for processing a subset of the plurality of location points in the three-dimensional model and for determining, for each processed location point, two measurement points in the cardiac electrophysiology map that are closest in distance to the processed location point, the delaunay edge processor defining a plurality of delaunay edges, each delaunay edges including pairs of measurement points determined to be closest to each processed location point;

a triangulation processor for defining a plurality of triangles in the centered electrophysiology map based on the plurality of delaunay edges; and

a projection processor assigns electrophysiology levels to at least location points located in of the plurality of triangles based on center of gravity interpolation using electrophysiology measurements associated with each of the vertices of the triangles.

2. The system of claim 1, wherein the projection processor further assigns electrophysiology levels to at least location points located within a proximity threshold of a delaunay edge based on bilinear interpolation using electrophysiology measurements measured at endpoints of the delaunay edge.

3. The system of claim 1, wherein the projection processor further assigns electrophysiology levels to at least location points based on the electrophysiology measurements measured at measurement points within the proximity threshold, wherein the assigned electrophysiology levels are the same as at the measurement points.

A system for mapping electrophysiological information onto a three-dimensional model, the system comprising:

a surface modeling controller for acquiring a three-dimensional model of at least a portion of the heart, including positional information for a plurality of location points on a surface of the heart;

an electrophysiology measurement device to generate a cardiac electrophysiology map that includes location information for a plurality of measurement points and electrophysiology measurements taken at each of the plurality of measurement points, the electrophysiology measurements being associated with respective measurement points at which the electrophysiology measurements were measured;

an edge processor for processing a subset of the plurality of location points in the three-dimensional model and for determining, for each processed location point, two measurement points in the cardiac electrophysiology map that are closest in distance to the processed location point, the edge processor defining a plurality of edges, each of the edges including pairs of measurement points determined to be closest to each processed location point;

a geometry processor to define a plurality of polygons in the centered electrophysiology map based on the plurality of edges; and

the mapping projector assigns electrophysiology levels to at least location points located in of the plurality of polygons based on interpolation using electrophysiology measurements associated with each vertices of the polygons.

5. The system of claim 4, wherein the mapping projector assigns electrophysiology levels to at least location points located near an edge based on bilinear interpolation using electrophysiology measurements measured at endpoints of the edge.

6. The system of claim 4, wherein the geometry processor defines the cardiac electrophysiology map using a plurality of triangles, and wherein the mapping projector assigns electrophysiology levels to at least location points located in of the triangles based on interpolation using electrophysiology measurements associated with each vertices of the triangles.