Classifications

• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
  • A61B5/7271—Specific aspects of physiological measurement analysis
  • A61B5/7285—Specific aspects of physiological measurement analysis for synchronizing or triggering a physiological measurement or image acquisition with a physiological event or waveform, e.g. an ECG signal
  • A61B5/7292—Prospective gating, i.e. predicting the occurrence of a physiological event for use as a synchronisation signal
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
  • A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
  • A61B5/7235—Details of waveform analysis
  • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
  • A61B5/024—Measuring pulse rate or heart rate
  • A61B5/02416—Measuring pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
  • A61B5/026—Measuring blood flow
  • A61B5/0295—Measuring blood flow using plethysmography, i.e. measuring the variations in the volume of a body part as modified by the circulation of blood therethrough, e.g. impedance plethysmography

Definitions

• the invention pertains to a synchronisation system, notably for triggering acquisition of imaging data, that involves a trigger delay.
• the known synchronisation system is in fact an experimental set up for synchronisation between MR imaging data (k-space data) acquisition and subject cardiac activity to reduce imaging artefacts due to (cardiac) motion.
• Contact free triggering is done by estimating the phase of the cardiac cycle from a remote photo plethysmography (rPPG)-signal obtained from skin colour variations with a video camera. That is, the above paper reports on MR image acquisition based on video triggers per se.
• rPPG remote photo plethysmography
• An object of the present invention is to provide a synchronisation that more accurately determines trigger base events that form the basis of synchronisation of imaging data acquisition with during subject motion.
• the sensor arrangement of the invention to detect a trigger base event comprising an analysis module and an arithmetic unit configured to access prior information on a time delay between the sensor arrangement's detection of the trigger base and a starting point of an acquisition time interval for acquiring imaging data and compute the starting point of the acquisition time interval from the detected trigger base event and the prior information of the time delay, wherein the analysis module and the arithmetic unit are configured to access the prior information in the image information of a subject to be examined and on the basis of the accessed image information to derive the time delay between the sensor arrangement's detection of the trigger base and a starting point of an acquisition time interval for acquiring imaging data.
• the synchronisation system of this aspect of the invention comprises a sensor arrangement to detect a trigger base event that represents an upcoming acquisition time interval during which imaging data, such as MR k-space data or CT attenuation profiles, may be acquired by a tomographic (MRI, CT, NM(PET, SPECT) diagnostic imaging system at a low level or even absence of perturbations, e.g.
• imaging data such as MR k-space data or CT attenuation profiles
• prior information is accessed on the time delay between the sensor arrangement's detection of the trigger base event and the occurrence of the acquisition time interval.
• the prior information includes image information that contains information or represents anatomical distances and sizes. Notably, these distances and sizes determine the path that blood needs to travel from the patient’s heart to the location from which the skin colour change is recorded. That is, from the prior information , by image analysis (e.g. automatic pattern recognition or indication of anatomical landmarks by a human user) anatomical sizes and distances can be computed.
• the time delay between the sensor arrangements’ detection of the trigger base event and the actual occurrence of the trigger base event can be computed.
• a trained neural network may be provided in the analysis module to return the time delay from the input image information. This forms a machine learning analysis module. This computation of the time delay from the image information may be done by way of a suitably trained machine-learning model or trained neural network. An explicit computation of anatomical distances from the image information is an implementation using relatively simple feature recognition and geometric calculations.
• the trigger base event may be an R-peak in an electrocardiogram (ECG) of the patient's heart and the acquisition time interval may be the quiescent heart phase following the R-peak and in which the is no or little heart motion and the acquired k-space data or attenuation profiles are hardly or not at all affected by motion.
• ECG electrocardiogram
• the time delay between the sensor arrangement's detection of the trigger base event and the acquisition time interval may vary between individual subjects, but for each individual subject the time delay is well reproducible and hence on a per subject basis may be calibrated for. The calibrated time delay allows to synchronise acquisition of imaging data with the motion of the subject such that image data can be acquired.
• acquisition of image data may be done on the basis of a trigger base event closely preceding the acquisition time interval.
• the trigger base event may be an R-peak of an electrocardiogram and the acquisition interval may be in the quiescent phase closely subsequent to the detected R-peak. That is, the quiescent interval immediately after the detected R-peak may be used for the acquisition of the imaging data.
• the image acquisition may be adapted to time available between the detection of the current trigger base event and the expected next trigger base event
• the computation of the starting point of the acquisition time interval also accounts for latency of the sensor arrangement.
• This latency represents the technical delay caused by the technology of the sensor arrangement.
• the sensor arrangement's software can determine that the blood rushes into the skin, e.g. on the patient's face.
• an insight of the present invention is that still, most of the sensor arrangement delay is caused by the pulse transit time from the heart to the face. Further details of corrections of the latency of the sensor arrangement are described in the European patent application EP20185605.1.
• the prior information on the time delay between the actual trigger base event and the timing of the acquisition interval is obtained from a separate (to the imaging data acquisition) calibration.
• this calibration the trigger base event and the timing of the acquisition interval are directly measured. That is, in an examining separate from a synchronised acquisition of imaging data there are done
• the calibration involves the combination of a direct measurement and determination by a sensor arrangement that is sufficiently similar (same class of same type) to the individual sensor arrangement to be employed in in image acquisition at a later point in the patient's care cycle.
• the R-peaks of the electrocardiogram are used.
• the direct measurement of the R-peak may be based on electronic measurements of the electrical activity of the heart by way of a set of electrodes placed on the patient's thorax.
• the acquisition interval is timed in the quiescent (mid to end) diastolic phase between successive R-peaks in the electrocardiogram.
• the electrocardiogram may be directly electronically measured by picking-up electronic cardiac signals by electrodes attached to the patient's thorax.
• the trigger base events are also detected by the sensor arrangement, which may be camera-based.
• the time delay between the actual occurrence of the trigger base event and its detection by the sensor arrangement (arrangement) can be calibrated for.
• An insight of the present invention is that this time delay may vary between individual patients, while the time delay is well reproducing for a single individual patient.
• a direct measurement of trigger base events in the form of R-peaks of the electrocardiogram is done early in the care cycle of a patient. This direct measurement when combined with a detection of the trigger base event by the sensor arrangement (arrangement) provides the calibrated time delay that can also be employed in a subsequent imaging procedure.
• an ECG recording system may be equipped with an additional photo plethysmography (PPG) sensor arrangement, which may be a camera-based PPG sensor arrangement or a conventional finger-tip sensor arrangement.
• PPG photo plethysmography
• Such an combined ECG-recording system with a PPG-sensor arrangement may be installed at a local point of care, such as a general practitioner's office.
• the camera-based PPG sensor arrangement detects variations in skin colour of the patient to be examined that represents pulsating blood flow. Usually skin colour is detected from the patient's face, e.g. forehead or temple.
• an adhesive contact PPG-sensor arrangement may be placed on the patient's skin.
• a conventional finger-tip PPG may be employed that is clamped to the patient's fingertip.
• Such a combined ECG-recording and PPG sensor arrangement can evaluate the patient specific delay between the actual trigger base event, i.e. the actual R-peak and a PPG-trigger marker detected by the PPG-sensor arrangement.
• This evaluation provides a calibration of the patient specific delay of the PPG-sensor arrangement to the actual R-peak recorded almost instantaneously by the ECG recording system based on electrodes on the patient's chest.
• This calibrated delay value may be employed subsequently in a PPG-based triggered magnetic resonance imaging protocol.
• the calibrated delay may also be employed for accurate time stamping magnetic resonance images relative to the R-peak forming the trigger base event.
• the calibrated delay between the PPG-sensor arrangement's recording of the trigger base event (R-peak) and the actual occurrence of the trigger base event by the PPG-sensor arrangement may be stored in the patient's digital health record and be made available during the subsequent magnetic resonance imaging procedure.
• the calibrated delay found form the comparison of the direct (ECG) measurement and the (PPG) sensor-based measurement may be compared to the delay that is computed from the image information on the subject that notably represents anatomical distances and sizes. This comparison provides a quantitative measure of the accuracy of the delay time derived from the image information.
• the delay between the sensor arrangement's detection of the trigger base event (R-peak) and the trigger base event itself is caused by pulse transit time (PTT) from the heart to the PPG site and delays cardiac triggering.
• PTT pulse transit time
• the face-based camera-PPG has an advantage, because respective PTTs are significantly shorter than for finger-tip-PPG.
• the PTT is known to vary with various physiological parameters as heart rate and blood pressure.
• a stress-ECG e.g. dining physical stress by cycling
• the heart rate varies significantly. It is proposed to map the above delay as a function of heart rate. This mapping may be used during the MR exam, where the current heart rate is known from the PPG-signal.
• An aspect of the invention concerns a computer programme comprising instructions to access prior information on a time delay between the sensor arrangement's detection of the trigger base and a starting point of an acquisition time interval for acquiring imaging data and compute the starting point of the acquisition time interval from the detected trigger base event and the prior information of the time delay.
• Another aspect of the invention concerns a computer programme comprising instructions to perform a direct measurement of the actual instant of the trigger base event and of the acquisition time interval, simultaneously detect the trigger base event by a sensor arrangement and determine a time delay between the actual instant of the trigger base event the detection of the trigger base event by the sensor arrangement.
• the invention may at least in part me implemented in software that is capable to bring about the technical effects of the invention when installed in the synchronisation system’s processor or computer and to implement the calibration procedure in software.
• the delay between the sensor arrangement's detection of the trigger base event and the trigger base event itself is derived from image information on the subject.
• the image information represents anatomical information of the subject, such as body height, arm length, shoulder width, distances from the aortic valve to the patient's forehead or finger. This anatomical information is relevant for the determination of the trigger delay.
• the accessed image information may be (colour or greyscale, infrared) images acquired by a camera system.
• the camera system may be mounted outside the examination zone of the tomographic diagnostic imaging system and controlled to acquire the images during preparation of the subject to be examined in the tomographic diagnostic imaging system.
• the camera system may also be mounted in or next to the examination zone.
• Such an in-bore camera system may acquire the image information during the tomographic image procedure.
• the image information may also be accessed from a preparatory magnetic resonance image, such as a low-resolution survey image.
• This embodiment of the synchronisation achieves to accurately determine the trigger delay taking into account differences between individual patients.
• the accurate trigger delay may be employed to synchronise acquisition of imaging data by the tomographic diagnostic imaging system with recurring motion, such as the subject's cardiac motion.
• the accurate trigger delay may also be employed for correct timing of magnetisation preparation (e.g. inversion recovery, magnetisation transform techniques and black-blood angiography) and excitation in magnetic resonance imaging.
• the accurate delay may also be employed to optimise scan efficiency by optimally using the time between the sensor arrangement's detection of a trigger base event and the subsequent trigger base event for magnetization preparation and image data acquisition.
• the trigger delay is estimated based on anatomical sizes and distances. It appears that these parameters predominantly determine variations among subjects of the trigger delay.
• the trigger delay may be due to the transit time of blood from the patient's heart to the anatomical location (forehead, fingertip).
• an estimation of the trigger delay may be performed by machine learning (e.g. a convolutional network). This may be achieved in two variants: a) direct estimation of the delay by the network with the image as input parameter or b) estimation of the anatomical features as arm length by the network based on the input image, and regression of the delay based on these anatomical features.
• the synchronisation system of the invention also at least two trigger base events e.g. based on PPG measurements at different locations are used to estimate the pulse transit velocity PTV.
• This approach is based on the insight that the PTV also depends on physiological parameters such as stiffness of the arteries and blood pressure.
• the pulse delay of the detection of the trigger base event e.g. by way PPG measurement at the patient’s face is calculated.
• a further aspect of the invention concerns a computer programme comprising instructions to control a sensor arrangement to detect trigger base events at different locations in a subject's body to be examined and to derive a pulse transit velocity from the time differences between the detected trigger base events and the derived anatomical distances between these different locations.
• the derivation of the pulse transit velocity may be implemented in software.
• a further aspect of the invention concerns a computer programme comprising instructions to access image information on a subject to be examined and to derive on the basis of the accessed image information the time delay between the sensor arrangement's detection of the trigger base and a starting point of an acquisition time interval for acquiring imaging data.
• the derivation of the time delay from image information may be implemented in software.
• Fig. 1 shows a schematic representation of a synchronisation system of the invention.
• Fig. 2 illustrates an example of a camera-PPG signal from the face of a contact sensor at the finger and the underlying physiology that causes the time delay;
• Fig. 3 shows a schematic representation of the calibration of the time delay for the synchronisation system of the invention
• Fig. 4 shows a schematic representation of an implementation of the synchronisation system of the invention in which use is made of image information
• Fig. 5 shows an example of linear regression of the delay between the PPG trigger obtained from the face and the R-peak (here called “backward distance” or “PTT”) versus body height as obtained in a volunteer study and
• Fig. 6 shows a schematic representation of an implementation of the synchronisation system of the invention in which individual trigger base events are detected from different positions on the body of the patient to be examined.
• Fig. 1 shows a schematic representation of the synchronisation system 1 of the invention.
• the synchronisation system functions to estimate a subsequent trigger base event from a detected current trigger base event (TBE) 11.
• the trigger base events are instances that prompt to trigger image acquisition e.g. by a tomographic imaging system 31.
• the tomographic imaging system may be a magnetic resonance examination system, a computed tomography system of a nuclear medicine tomographic imaging system.
• the acquired imaging information may be k-space profiles, attenuation profiles or detected gamma (g) photons.
• a magnetic resonance image may be reconstructed form the k-space profiles, a computed tomography image may be reconstructed from (x-ray) attenuation profiles at various orientations.
• the imaging information in the form of k-space profiles, attenuation profiles or detected photons may be acquired in multiple sets of imaging data at successive intervals, notably dining successive equal or comparable motion states of the subject to be imaged (patient to be examined). For example imaging data sets may be acquired an equal, comparable of corresponding cardiac or respiratory phases.
• the synchronisation system is provided with the sensor 10 to detect a current trigger base event 11.
• the synchronisation system 1 is provided with an analysis model 20 to which the detected trigger base event’s instant is applied by the sensor 10.
• the analysis module has access to prior information on the latency of the sensor (t) 22 and the time interval (Int) 21 between the actual trigger base event and the timing of the acquisition interval. This prior information may be obtained from a previous (to the imaging data acquisition) calibration.
• the analysis module includes an arithmetic unit or a machine-learning unit to compute or return the trigger signal (TS) from the detected instant of the trigger base event and the prior information.
• the trigger signal is applied to a control unit of the image acquisition system 31.
• the synchronisation system may be integrated in the image acquisition system of may be a stand-alone synchronisation system coupled to the image acquisition system for the triggered image acquisition in point.
• Fig. 2 illustrates an example of a camera-PPG signal from the face, an ECG signal, and a contact-PPG signal from the finger, all measured simultaneously during about one cardiac cycle.
• “Camera-PPG valley” and “Contact-PPG peak” denote PPG markers suitable for cardiac triggering. They are delayed with respect to the R-peak which is conventionally used for triggering.
• Fig. 2 illustrates that the trigger base event as detected by the ECG directly from electrodes placed on the patient's chest is detected with a negligible trigger delay.
• the trigger base event detected by the camera from the subject's forehead or by a contact sensor at the fingertip are delayed by respective trigger delays relative to the directly detected ECG R-peak.
• Fig. 3 shows a schematic representation of the calibration of the time delay for the synchronisation system of the invention.
• the calibration procedure 60 involves to perform a direct detection 61, i.e. having a priori a negligible trigger delay, to the trigger base event. That is the direct detection 61 is done by a measurement set up that has negligible technical sensor delay and also negligible pules transit time associated with the subject’s physiology. Additionally, the trigger base event (same or corresponding) is detected 62 by the sensor arrangement (same or correspondingly equivalent) and the trigger delay is determined from the comparison of the detection instant and the direct detection and the detection by the sensor arrangement.
• This trigger delay represents the time span between the sensor arrangement detection of the trigger base event and the actual occurrence of the trigger base event in a reproducible manner for the individual subject at issue.
• the calibrated trigger delay may be employed as the prior information in subsequent synchronisation, e.g. of diagnostic image acquisition. Further refinements may be made to correct the trigger delay for difference in heart rate of the subject during calibration and during synchronisation of the diagnostic image acquisition.
• Fig. 4 shows a schematic representation of an implementation of the synchronisation system of the invention in which use is made of image information.
• Image information 51 may have been acquired by a camera or from a magnetic resonance or computed tomography (survey) image.
• a geometry analyser 53 derives anatomical distances that are applied to the analysis module.
• a trained neural network 55 returns anatomical distances from the input image information 51.
• the trained neural network may be trained on the basis of training datasets of sets of images and separately measured anatomical distances of the anatomies represented by the images.
• the analysis module 20 estimates the trigger delay.
• the trigger delay may be estimated on the basis of a linear regression analysis of calibration measurements of body height versus actual trigger delay or pulse transit time. Empirically the pulse transit time appears to be approximately linear with body height. This is illustrated in Fig. 5 which shows an example of linear regression of the delay between the PPG trigger obtained from the face and the R-peak (here called “backward distance” or “PTT”) versus body height as obtained in a volunteer study.
• the labels 80Hz and 20Hz refer to the camera frame rates employed in the camera-based detection of the R-peaks. In this experiment the camera is located above the patient table.
• Fig. 6 shows a schematic representation of an implementation of the synchronisation system of the invention in which individual trigger base events are detected from different positions on the body of the patient to be examined.
• the sensor includes multiple sensor elements that detect the individual trigger base event at different locations R 1 , 2,3 ⁇ ⁇ ⁇ 71 on the patient’s body.
• the sensor elements detect the trigger base events from the respective locations at respective arrival times Tai , 2 , 3 lake. 73.
• the analysis module may compute the pulse transit velocity PTV. Based on the PTV and known anatomical distances as from heart to face, the pulse delay of the PPG measurement at the patient’s face is calculated.

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• 2021
  • 2021-07-20 EP EP21186781.7A patent/EP4122386A1/en not_active Withdrawn
• 2022
  • 2022-07-11 US US18/578,757 patent/US20240324971A1/en active Pending
  • 2022-07-11 WO PCT/EP2022/069216 patent/WO2023001606A1/en not_active Ceased
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  • 2022-07-11 CN CN202280050651.4A patent/CN117677344A/zh active Pending
  • 2022-07-11 JP JP2024501789A patent/JP2024525738A/ja active Pending

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