Dynamic cardiac electrical excitation diagram generation method and device

Abstract

The invention relates to the technical field of medical and industrial cross, in particular to a method and device for generating a dynamic cardiac electrical excitation diagram, and the method comprises the steps: carrying out the phase alignment of the electrical excitation diagram and the cardiac image data of a preset mode, and obtaining time domain alignment data; on the basis of the time domain alignment data, aligning the heart models reconstructed in different modes according to the anatomical form to obtain space domain alignment data; and projecting an electrical mapping result to a corresponding anatomical structure of the heart based on the time domain alignment data and the spatial domain alignment data, and constructing a dynamic heart model of individualized electrical anatomical mapping of the target patient so as to display propagation of the electrical excitation diagram in the whole cardiac cycle on the dynamic heart model according to the conduction velocity in one cardiac cycle. According to the method, the dynamic heart model of the individualized electroanatomical mapping of the specific patient can be constructed by using the cardiac electrophysiology and anatomical structure data, the dynamic cardiac electrical excitation diagram of the human body is reconstructed, and the catheter ablation treatment of the tachycardia patient is guided by using the dynamic cardiac electrical excitation diagram.

Description

Technical Field

[0001] The present application relates to the field of medical and engineering intersection technology, and in particular to a method and device for generating a dynamic cardiac electrical activation map. Background Art

[0002] Catheter ablation is a widely used, minimally invasive procedure used to treat cardiac arrhythmias when medications fail to restore normal heart rhythm. During the procedure, a steerable catheter is inserted into the heart and uses radiofrequency (RF) energy to ablate the target area, blocking abnormal electrical signals. Before performing catheter ablation, a three-dimensional electrical map of the patient's heart is typically obtained.

[0003] Among related technologies, the Carto mapping system is a commonly used three-dimensional electroanatomical mapping system that can obtain a three-dimensional electrical map inside the heart. It uses a magnetic catheter to continuously displace in the heart, and reconstructs a three-dimensional anatomical map of the heart based on the spatial position change of its position relative to a fixed magnetic field. By point-by-point displacement of the electrode catheter in the heart or on the surface of the heart, the changes in the heart's current are sensed, and potential change maps and electrical excitation sequence mapping maps are inserted on the anatomical map to complete the three-dimensional electroanatomical mapping. The intracardiac non-contact mapping technology EnSite 3000 can display the excitation of the entire cardiac chamber of the mapped heart, intuitively showing the origin of tachycardia, conduction pathways, reentrant excitation loops, slow conduction areas, and key isthmuses, which can help analyze the mechanism of difficult arrhythmias and formulate corresponding ablation strategies.

[0004] However, the clinical mapping systems or technologies in related technologies cannot obtain the movement information of the heart. The surgeon can only perform radiofrequency ablation surgery for arrhythmias on static images, which causes certain inconveniences during the operation and cannot meet the usage requirements in actual treatment scenarios, and needs to be solved urgently. Summary of the Invention

[0005] The present application provides a method and device for generating a dynamic cardiac electrical activation map to solve the problems in related technologies such as the inability of clinical mapping systems or technologies to obtain cardiac motion information, the surgeon can only perform arrhythmia radiofrequency ablation surgery on static images, which causes certain inconveniences during the operation and cannot meet the usage requirements in actual treatment scenarios.

[0006] The first aspect of the present application provides a method for generating a dynamic cardiac electroexcitation map, comprising the following steps: performing phase alignment on the electroexcitation map and cardiac imaging data of a preset modality to obtain time domain alignment data; based on the time domain alignment data, aligning cardiac models reconstructed by different modalities according to anatomical morphology to obtain spatial domain alignment data; based on the time domain alignment data and the spatial domain alignment data, projecting the electromapping results of the dynamic heart onto the corresponding anatomical structure of the dynamic heart to construct a dynamic cardiac model with individualized electroanatomical mapping for the target patient, so as to display the propagation of the electroexcitation map throughout the cardiac cycle on the dynamic cardiac model according to the conduction velocity in one cardiac cycle.

[0007] Optionally, in one embodiment of the present application, the phase alignment of the electroexcitation map and the cardiac imaging data of the preset modality includes: calculating the cardiac cycle time based on the reference signal of the electroexcitation map, and using the marked point as the time zero point in a cardiac cycle to determine the local excitation time; and performing phase alignment based on the local excitation time and the cardiac imaging data of the preset modality.

[0008] Optionally, in one embodiment of the present application, the alignment of heart models reconstructed in different modalities according to anatomical morphology includes: based on the left ventricle, right ventricle, left atrium and / or right heart, solving a least squares optimization problem using at least one landmark point reconstructed by a landmark system and at least one landmark point reconstructed by segmentation to calculate the rigid body transformation between the three-dimensional models; and aligning using the rigid body transformation between the three-dimensional models to complete the alignment of heart models reconstructed in different modalities according to the anatomical morphology.

[0009] Optionally, in one embodiment of the present application, the electrical mapping results of the dynamic heart are projected onto the corresponding anatomical structure of the dynamic heart based on the time domain alignment data and the space domain alignment data, including: constructing a statistical shape model based on training data of known heart chamber segmentation; aligning the statistical shape model with the data to be segmented, so as to use the statistical shape model to match and segment the heart chambers in the data to be segmented to obtain a segmentation result; and verifying the segmentation result to project the electrical mapping results of the dynamic heart onto the corresponding anatomical structure of the dynamic heart.

[0010] Optionally, in one embodiment of the present application, the calculation formula of the conduction velocity is:

[0011]

[0012] where T(x) is the local excitation time function at point x, and f(x,t) is the scalar field function describing the activation wavefront.

[0013] The second aspect of the present application provides a device for generating a dynamic cardiac electroexcitation map, including: a first alignment module, used to phase-align the electroexcitation map and cardiac imaging data of a preset modality to obtain time-domain alignment data; a second alignment module, used to align heart models reconstructed with different modalities according to anatomical morphology based on the time-domain alignment data to obtain space-domain alignment data; a generation module, used to project the electromapping results of the dynamic heart onto the corresponding anatomical structure of the dynamic heart based on the time-domain alignment data and the space-domain alignment data, to construct a dynamic heart model with individualized electroanatomical mapping for the target patient, so as to display the propagation of the electroexcitation map throughout the entire cardiac cycle on the dynamic heart model according to the conduction velocity in one cardiac cycle.

[0014] Optionally, in one embodiment of the present application, the first alignment module includes: a first calculation unit, used to calculate the cardiac cycle time based on the reference signal of the electrical excitation map, and use the marked point as the time zero point in a cardiac cycle to determine the local excitation time; a first alignment unit, used to perform phase alignment based on the local excitation time and the cardiac imaging data of the preset modality.

[0015] Optionally, in one embodiment of the present application, the second alignment module includes: a second calculation unit, used to solve the least squares optimization problem based on the left ventricle, right ventricle, left atrium and / or right heart, using at least one landmark point reconstructed by the landmark system and at least one landmark point reconstructed by the segmentation, so as to calculate the rigid body transformation between the three-dimensional models; a second alignment unit, used to perform alignment using the rigid body transformation between the three-dimensional models, so as to complete the alignment of heart models reconstructed in different modalities according to the anatomical morphology.

[0016] Optionally, in one embodiment of the present application, the generation module includes: a construction unit for constructing a statistical shape model based on training data of known heart chamber segmentation; a segmentation unit for aligning the statistical shape model with the data to be segmented, so as to use the statistical shape model to match and segment the heart chambers in the data to be segmented to obtain a segmentation result; and a projection unit for verifying the segmentation result, so as to project the electrical mapping result of the dynamic heart onto the corresponding anatomical structure of the dynamic heart.

[0017] Optionally, in one embodiment of the present application, the calculation formula of the conduction velocity is:

[0018]

[0019] where T(x) is the local excitation time function at point x, and f(x,t) is the scalar field function describing the activation wavefront.

[0020] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for generating a dynamic cardiac electrical activation diagram as described in the above embodiment.

[0021] A fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned method for generating a dynamic cardiac electrical activation diagram.

[0022] The fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, is used to implement the above-mentioned method for generating a dynamic cardiac electrical activation diagram.

[0023] The embodiment of the present application can perform phase alignment between the electroexcitation map and cardiac imaging data of other modalities, align the cardiac models reconstructed in different modalities according to the anatomical morphology, and project the obtained electromapping results onto the corresponding anatomical structure of the heart, and finally complete the display of the propagation of the electroexcitation map throughout the cardiac cycle on the dynamic cardiac model according to the conduction velocity within one cardiac cycle. Thus, it is achieved that a dynamic cardiac model of electroanatomical mapping personalized for a specific patient is constructed by utilizing cardiac electrophysiological and anatomical structure data, thereby reconstructing the human body's dynamic cardiac electroexcitation map, and finally the reconstructed dynamic cardiac electroexcitation map can be used to guide catheter ablation treatment for patients with tachycardia. Thus, it solves the problem that the clinical mapping system or technology in the related art cannot obtain the motion information of the heart, the surgeon can only perform arrhythmia radiofrequency ablation surgery on static images, there are certain inconveniences during the operation, and it cannot meet the use requirements in actual treatment scenarios.

[0024] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0026] Figure 1 A flowchart of a method for generating a dynamic cardiac electrical activation map according to an embodiment of the present application;

[0027] Figure 2 This is a schematic diagram of the definition of local excitation time according to one embodiment of the present application;

[0028] Figure 3 A schematic diagram of selecting the phase corresponding to the end-diastole of the heart in 4D CCTA data according to one embodiment of the present application;

[0029] Figure 4 This is a schematic diagram of cardiac structure alignment according to one embodiment of the present application;

[0030] Figure 5 This is a schematic diagram of left atrial landmarks according to one embodiment of the present application;

[0031] Figure 6 This is a schematic diagram of conduction velocity calculation according to one embodiment of the present application;

[0032] Figure 7 A schematic diagram of local activation time with superimposed conduction velocity vectors according to one embodiment of the present application;

[0033] Figure 8 A schematic diagram of using radial basis functions to interpolate mapping points into continuous electrical activation maps according to one embodiment of the present application;

[0034] Figure 9 This is a schematic diagram of electrical mapping result mapping results according to one embodiment of the present application;

[0035] Figure 10 Schematic diagram of the structure of a device for generating a dynamic cardiac electrical activation map according to an embodiment of the present application;

[0036] Figure 11 Schematic diagram of the structure of an electronic device according to an embodiment of the present application.

[0037] Reference numerals:

[0038] 10-Device for generating dynamic cardiac electrical activation diagram: 100-first alignment module, 200-second alignment module and 300-generation module; 1101-memory, 1102-processor and 1103-communication interface. DETAILED DESCRIPTION

[0039] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0040] The following describes a method and device for generating a dynamic cardiac electrocardiogram according to an embodiment of the present application with reference to the accompanying drawings. In view of the fact that the clinical mapping system or technology in the related art mentioned in the above background art cannot obtain the motion information of the heart, the operator can only perform radiofrequency ablation surgery for arrhythmias on static images, which is inconvenient during the operation and cannot meet the use requirements in actual treatment scenarios, the present application provides a method for generating a dynamic cardiac electrocardiogram, in which the electrocardiogram and cardiac imaging data of other modalities can be phase-aligned, and the cardiac models reconstructed in different modalities can be aligned according to the anatomical morphology, and the electrical mapping results of the dynamic heart can be projected onto the corresponding anatomical structure, and finally, the propagation of the electrocardiogram throughout the cardiac cycle can be displayed on the dynamic cardiac model according to the conduction velocity within one cardiac cycle. Thus, it is achieved by constructing a dynamic cardiac model of individualized electroanatomical mapping for a specific patient using cardiac electrophysiological and anatomical structure data, thereby reconstructing the human body's dynamic cardiac electrocardiogram, and finally the reconstructed dynamic cardiac electrocardiogram can be used to guide catheter ablation treatment for patients with tachycardia. This solves the problem that the clinical mapping system or technology in related technologies cannot obtain the movement information of the heart, the operator can only perform arrhythmia radiofrequency ablation surgery on static images, which causes certain inconveniences during the operation and cannot meet the usage needs in actual treatment scenarios.

[0041] Before explaining the method for generating a dynamic cardiac electrical activation map in the embodiment of the present application, the dynamic cardiac scanning technology involved in the embodiment of the present application is first explained.

[0042] The embodiment of the present application can generate a dynamic cardiac electrocardiogram, so that the propagation of the electrocardiogram throughout the cardiac cycle can be displayed on a dynamic cardiac surface model, thereby realizing the linkage between heart beats and electrocardiogram information.

[0043] Specifically, Figure 1 A flowchart of a method for generating a dynamic cardiac electrical activation diagram provided in an embodiment of the present application.

[0044] like Figure 1 As shown, the method for generating the dynamic cardiac electrical activation diagram includes the following steps:

[0045] In step S101 , phase alignment is performed on the electrocardiogram and cardiac image data of a preset modality to obtain time-domain aligned data.

[0046] It can be understood that the preset mode here can be understood as a pre-established heart model of different states. The dynamic cardiac electrical excitation map here can be understood as an image that displays the cardiac electrical excitation process based on the electrocardiogram (ECG) and combines the time axis and the dynamic changes of the heart's electrical activity. This image not only reflects the rhythmicity of the heart's electrical activity, but also reveals the order and speed of electrical excitation in various parts of the heart, which is of great significance for the diagnosis of heart disease. It should be noted that the electrical excitation map in the embodiment of the present application is part of the electrical mapping results.

[0047] In some embodiments, given that the heart is an organ in constant cyclical motion, the image data of its contraction and relaxation processes can reflect the heart's rhythm and state. This application can phase-align the electrocardiogram with cardiac image data from other modalities, ensuring the synchronization of image data at specific cardiac phases (such as systole and diastole), reducing artifacts caused by cardiac motion, and improving image quality. This more accurately reflects the structure and function of the heart, helps precisely locate the location and extent of cardiac lesions, and provides strong support for clinical diagnosis and treatment.

[0048] Optionally, in one embodiment of the present application, the electroexcitation map and the cardiac imaging data of the preset modality are phase-aligned, including: calculating the cardiac cycle time based on the reference signal of the electroexcitation map, and using the marked point as the time zero point in a cardiac cycle to determine the local excitation time; and performing phase alignment based on the local excitation time and the cardiac imaging data of the preset modality.

[0049] During the actual implementation process, when the present application performs phase alignment on the electrocardiogram and the cardiac imaging data of the preset modality, it can, but is not limited to, first calculate the cardiac cycle time based on the reference signal (marker point) of the electrocardiogram, and use the mark point as the time zero point in a cardiac cycle, thereby determining the local activation time (LAT, Local activation time, which refers to the time from the earliest recorded ventricular excitation to the start of local excitation), so as to perform phase alignment based on the local activation time and the cardiac imaging data of the preset modality.

[0050] For example, for an electrocardiogram, the present application can collect signals at the end of diastole and select a stable signal as a reference signal (marker point). The cardiac cycle time is calculated and the marker point is used as the time zero in a cardiac cycle. The excitation time of the ECG signal is then subtracted from the time zero to obtain the local excitation time. Figure 2 This is a schematic diagram of the definition of local excitation time in one embodiment of the present application. In this embodiment of the present application, the time zero point can be, but is not limited to, a typical time at the end-diastolic phase of the heart.

[0051] Taking 4D CCTA (four-dimensional cardiac CT angiography, which uses computed tomography technology to create high-speed, three-dimensional images of cardiac structures and blood vessels, capturing dynamic information during the cardiac cycle, thus providing a fourth dimension, time axis information) as an example, dynamic cardiac scanning involves diastole, the relaxation phase of the cardiac cycle, when the heart chambers refill with blood. The opposite phase is systole, when the heart chambers contract.

[0052] Figure 3 This is a schematic diagram of selecting the phase corresponding to the end diastole of the heart from the 4D CCTA data in one embodiment of the present application. Figure 3 As shown, for 4D CCTA, the phase corresponding to the end of cardiac diastole is also selected (the black dotted box identifies the cardiac chamber model diagram at this time), that is, time (or phase) alignment is performed with the data of the electrical activation diagram.

[0053] It should be noted that when performing dynamic cardiac scanning, professionals in this field may select or adjust the technical method according to actual circumstances. This is only an example and is not a specific limitation. Dynamic cardiac scanning can be used clinically to evaluate cardiac structure and function. Common dynamic cardiac scanning methods include dynamic magnetic resonance imaging (MRI), 4D CCTA scanning, echocardiography, and radionuclide imaging, among which:

[0054] Dynamic magnetic resonance imaging (MRI): Dynamic MRI can provide high temporal and spatial resolution images of cardiac structure and function, observing the movement and blood flow of the heart through continuous scanning.

[0055] 4D CCTA: Through CT scanning, multi-layer images of the heart can be continuously obtained to observe the dynamic changes of the heart and the condition of blood vessels.

[0056] Echocardiography: Echocardiography can observe the movement of the heart in real time. Through different scanning methods and imaging modes, dynamic heart images can be obtained.

[0057] Radionuclide imaging: Radionuclide imaging techniques, such as single-photon emission computed tomography (SPECT) or positron emission tomography (PET), can be used to dynamically observe cardiac metabolism and perfusion.

[0058] These methods have their own advantages and scope of application, and can provide doctors with comprehensive dynamic cardiac information to help diagnose and treat heart diseases.

[0059] Step S102 : Based on the time domain alignment data, the heart models reconstructed in different modalities are aligned according to the anatomical morphology to obtain space domain alignment data.

[0060] In some embodiments, taking into account the diversity of heart models and heart structures, the embodiments of the present application can also align heart models reconstructed with different modalities to obtain spatial domain alignment data, so as to perform subsequent dynamic cardiac electrical activation map generation process based on the spatial domain alignment data.

[0061] Optionally, in one embodiment of the present application, cardiac models reconstructed with different modalities are aligned, including: based on the left ventricle, right ventricle, left atrium and / or right heart, solving a least squares optimization problem using at least one landmark point reconstructed by a landmark system and at least one landmark point reconstructed by segmentation to calculate the rigid body transformation between the three-dimensional models; aligning using the rigid body transformation between the three-dimensional models to complete the alignment of cardiac models reconstructed with different modalities according to the anatomical morphology.

[0062] During the actual implementation process, when aligning heart models reconstructed with different modalities, the present application can, but is not limited to, solve the least squares optimization problem based on the left ventricle, right ventricle, left atrium and / or right heart of the heart using at least one landmark point reconstructed by the landmark system and at least one landmark point reconstructed by the segmentation, calculate the rigid body transformation between the three-dimensional models, and then align them, thereby completing the alignment of heart models reconstructed with different modalities according to the anatomical morphology.

[0063] Taking the left atrium as an example, Figure 4 This is a schematic diagram of cardiac structure alignment according to an embodiment of the present application. Figure 4 As shown, on the left is a model example from the CARTO 3 mapping system, and on the right is the result of segmentation and reconstruction of a 4D CCTA scan from the same patient.

[0064] Specifically, the left atrial apex in the example of the present application can be, but is not limited to, selected at the junction of the left atrial body and the LSPV (Leftsuperior pulmonary vein) and the RSPV (Right superior pulmonary vein), that is, the highest posterior position of the left atrium. Figure 5 The following is a schematic diagram of the left atrium landmark points according to an embodiment of the present application, wherein (a) is an example of two vertices of the left atrium, and (b) is an example of a spacer point of the left atrium. Figure 5 As shown in (a), these two landmarks (black points) can be used to construct a roof line to define how the geometry is divided into the rear and front parts; Figure 5 As shown in (b), the left atrial septum point (black mark) can be selected just in front of the fossa ovalis.

[0065] The three landmark points on the cavity A reconstructed by the mapping system are denoted as p a(i), (i=1,2,3), the three landmark points on the cavity B reconstructed by 4DCCTA are denoted as p b (i), (i=1,2,3). The rigid body transformation T between the two 3D models is calculated by solving the least squares optimization problem, so that model A is aligned with model B after the transformation T. The rigid body transformation T includes rotation R and translation t, p b (i) = R·p a (i)+t, R is a 3×3 matrix,

[0066] Since the cardiac cavity reconstructed by electrical mapping and the cardiac cavity reconstructed by 4D CCTA segmentation are from the same cardiac phase of the same patient, the alignment of the cardiac models reconstructed by different modalities can be completed through the same-scale rigid body transformation as above.

[0067] In step S103, based on the time-domain alignment data and the space-domain alignment data, the dynamic heart electrical mapping results are projected onto the corresponding anatomical structures of the dynamic heart to construct a dynamic heart model with individualized electroanatomical mapping for the target patient. The propagation of the electrical activation map throughout the cardiac cycle is displayed on the dynamic heart model based on the conduction velocity. The calculation formula for the conduction velocity can be expressed as:

[0068]

[0069] where T(x) is the local excitation time function at point x, and f(x,t) is the scalar field function describing the activation wavefront.

[0070] As a possible implementation method, after obtaining the time domain alignment data and the space domain alignment data, the present application can project the electrical mapping results of the dynamic heart onto the corresponding anatomical structure of the dynamic heart based on the two, and construct a dynamic heart model with personalized electroanatomical mapping for the target patient, thereby realizing the display of the propagation of the electrical excitation map throughout the entire cardiac cycle on the dynamic heart model according to the conduction velocity in one cardiac cycle.

[0071] Taking the reconstruction of the three-dimensional grid model of the end-diastolic phase from the dynamic sequence images of 4D CCTA as an example, the present application can, but is not limited to, maintain the grid structure and vertex correspondence between time frames through the method of phase-by-phase alignment of CT data, propagate the template grid of the end-diastole to all phases, and then map the electrical excitation map collected in a certain phase to each phase of the cardiac cycle based on the consistency of the grid topology of different phases.

[0072] It is understood that atrial conduction velocity (CV) is an indicator of the health of the myocardial matrix, which describes the speed and direction of propagation of the electrical wavefront through the myocardium. Among them, CV calculation methods can be divided into three categories: (1) local methods, which only use LAT observations from the direct spatial neighborhood to calculate CV; (2) global methods, which simultaneously fit the complete CV map to all LAT observations; (3) inverse methods, which infer the CV field that is most consistent with the LAT observations in a physically considered manner. In the embodiment of the present application, the conduction velocity formula derived from the spatiotemporal gradient of the scalar field used to define the activation wavefront can be used to obtain the conduction velocity at point x, where the formula can be expressed as follows:

[0073]

[0074] where T(x) is the local excitation time function at point x, and f(x,t) is the scalar field function describing the activation wavefront.

[0075] Figure 6 This is a schematic diagram of calculating conduction velocity from a local activation time map according to an embodiment of the present application. Figure 6 Figure 6(a) shows the conduction velocity calculated from the local activation time map. Figure 6 (b).

[0076] Furthermore, the embodiment of the present application can also convert the conduction velocity vector v f The dynamic cardiac local activation time map is drawn to complete the display of the propagation of the electrical activation map throughout the cardiac cycle based on the conduction velocity on the dynamic cardiac model. Figure 7 FIG. 1 is a schematic diagram of local activation time with a conduction velocity vector superimposed on an embodiment of the present application. Figure 7 As shown, it shows the effect of superimposing the conduction velocity vector (shown as an arrow) on the local activation time map of the left atrial roof wall, and the contour lines in the figure represent the activation wavefront corresponding to different values.

[0077] Optionally, in one embodiment of the present application, the electrical mapping results of the dynamic heart are projected onto the corresponding anatomical structure of the dynamic heart, including: constructing a statistical shape model based on training data of known heart chamber segmentation; aligning the statistical shape model with the data to be segmented, so as to use the statistical shape model to match and segment the heart chambers in the data to be segmented to obtain a segmentation result; and verifying the segmentation result to project the electrical mapping results of the dynamic heart onto the corresponding anatomical structure of the dynamic heart.

[0078] Based on the relevant descriptions of other embodiments, it can be understood that before the present application realizes the propagation of the electrical excitation diagram according to the conduction velocity on the dynamic heart model within a cardiac cycle, it is necessary to first project the electrical mapping results of the dynamic heart onto the corresponding anatomical structure of the dynamic heart.

[0079] Specifically, a statistical shape model can be first constructed based on the training data of known heart chamber segmentation, and then the statistical shape model can be aligned with the data to be segmented, so as to use the statistical shape model to match and segment the heart chambers in the data to be segmented. After obtaining the segmentation results, the segmentation results can be verified, so that the electrical mapping results of the dynamic heart can be projected onto the corresponding anatomical structure of the dynamic heart.

[0080] For example, Figure 8 This is a schematic diagram of using radial basis functions to interpolate the measured points into a continuous electrical activation map according to one embodiment of the present application, wherein (a) is a discrete measured point and (b) is the result after interpolation. Figure 8 As shown, the embodiment of the present application can, but is not limited to, use radial basis functions to interpolate discrete mapping points into a continuous electroactive map distribution. Including but not limited to: n three-dimensional mapping points: and its corresponding local excitation time Define the interpolation function The hybrid weight is assigned according to the inverse of the distance between the query position x and the actual calibration point. The formula can be expressed as follows:

[0081]

[0082] Among them, p is used to adjust the smoothing effect of the interpolation result.

[0083] The 4D CCTA is then segmented and reconstructed to create a left atrial model. 4D CCTA segmentation methods primarily include, but are not limited to, deep learning methods, including machine learning techniques such as convolutional neural networks (CNNs), which train models to automatically segment images; and statistical shape models, which consider the shape and variation of structures and are suitable for segmenting complex structures.

[0084] In the embodiments of the present application, the cardiac chambers can be segmented using, but are not limited to, a statistical shape model method. The method mainly includes the following steps: (1) establishing a shape model: first, constructing a statistical shape model from a set of training data, which can be achieved by performing shape modeling and statistical analysis on the training data with known cardiac chamber segmentation. (2) shape alignment: aligning the obtained statistical shape model with the 4D CCTA data to be segmented to adapt to the specific anatomical structure and size. (3) shape matching: using the statistical shape model to match and segment the cardiac chambers in the 4D CCTA data. This can be achieved by evaluating the fit between the shape model and the actual data. (4) verification and adjustment: finally, verifying the obtained segmentation results, and adjusting and optimizing them as needed to ensure that the structure and shape of the cardiac chambers are accurately captured.

[0085] Finally, the electrical mapping results of the dynamic heart are mapped onto the left atrium at the end of diastole, as shown in Figure 9 As shown, it is a schematic diagram of the mapping result of the electrical mapping result of an embodiment of the present application, (a) is the discrete mapping value, and (b) is the electrical mapping result after interpolation.

[0086] According to the method for generating a dynamic cardiac electroexcitation map proposed in the embodiment of the present application, the electroexcitation map and cardiac imaging data of other modalities can be phase-aligned, and the cardiac models reconstructed in different modalities can be aligned according to the anatomical morphology, and the electrical mapping results of the dynamic heart can be projected onto the corresponding anatomical structure, and finally the propagation of the electroexcitation map throughout the cardiac cycle can be displayed on the dynamic cardiac model according to the conduction velocity within one cardiac cycle. Thus, it is achieved by constructing a dynamic cardiac model of electroanatomical mapping individualized for a specific patient using cardiac electrophysiological and anatomical structure data, thereby reconstructing the human body's dynamic cardiac electroexcitation map, and finally the reconstructed dynamic cardiac electroexcitation map can be used to guide catheter ablation treatment for patients with tachycardia. Thus, it solves the problem that the clinical mapping system or technology in the related art cannot obtain the motion information of the heart, the operator can only perform arrhythmia radiofrequency ablation surgery on static images, there are certain inconveniences during the operation, and it cannot meet the use requirements in actual treatment scenarios.

[0087] Next, a device for generating a dynamic cardiac electrical activation diagram according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0088] Figure 10 It is a structural schematic diagram of a device for generating a dynamic cardiac electrical activation diagram according to an embodiment of the present application.

[0089] like Figure 10 As shown, the device 10 for generating a dynamic cardiac electrical activation map includes: a first alignment module 100 , a second alignment module 200 and a generation module 300 .

[0090] The first alignment module 100 is used to perform phase alignment on the electro-activation diagram and cardiac imaging data of a preset modality to obtain time-domain aligned data.

[0091] The second alignment module 200 is configured to align the heart models reconstructed in different modalities according to the anatomical morphology based on the time domain alignment data to obtain space domain alignment data.

[0092] The generation module 300 is used to project the electrical mapping results of the dynamic heart onto the corresponding anatomical structure of the dynamic heart based on the time domain alignment data and the space domain alignment data, and to construct a dynamic heart model with individualized electroanatomical mapping of the target patient, so as to display the propagation of the electrical excitation diagram throughout the cardiac cycle on the dynamic heart model according to the conduction velocity in one cardiac cycle.

[0093] Optionally, in one embodiment of the present application, the first alignment module 100 includes: a first calculation unit and a first alignment unit.

[0094] The first calculation unit is used to calculate the cardiac cycle time based on the reference signal of the electrical excitation diagram, and use the marked point as the time zero point in a cardiac cycle to determine the local excitation time.

[0095] The first alignment unit is configured to perform phase alignment based on the local excitation time and cardiac image data of a preset modality.

[0096] Optionally, in one embodiment of the present application, the second alignment module 200 includes: a second calculation unit and a second alignment unit.

[0097] Among them, the second calculation unit is used to solve the least squares optimization problem based on the left ventricle, right ventricle, left atrium and / or right heart using at least one landmark point reconstructed by the landmark system and at least one landmark point reconstructed by segmentation to calculate the rigid body transformation between the three-dimensional models.

[0098] The second alignment unit is used to perform alignment using rigid body transformation between the three-dimensional models, so as to complete the alignment of the heart models reconstructed in different modalities according to the anatomical morphology.

[0099] Optionally, in one embodiment of the present application, the generation module 300 includes: a construction unit, a segmentation unit, and a projection unit.

[0100] The construction unit is used to construct a statistical shape model based on training data of known cardiac chamber segmentation.

[0101] The segmentation unit is used to align the statistical shape model with the data to be segmented, so as to match and segment the cardiac chambers in the data to be segmented using the statistical shape model to obtain a segmentation result.

[0102] The projection unit is used to verify the segmentation result so as to project the electrical mapping result of the dynamic heart onto the corresponding anatomical structure of the dynamic heart.

[0103] Optionally, in one embodiment of the present application, the calculation formula of the conduction velocity can be expressed as:

[0104]

[0105] where T(x) is the local excitation time function at point x, and f(x,t) is the scalar field function describing the activation wavefront.

[0106] It should be noted that the above explanation of the embodiment of the method for generating a dynamic cardiac electrocardiogram is also applicable to the apparatus for generating a dynamic cardiac electrocardiogram in this embodiment, and will not be repeated here.

[0107] According to the device for generating a dynamic cardiac electroexcitation map proposed in the embodiment of the present application, the electroexcitation map and cardiac imaging data of other modalities can be phase-aligned, and the cardiac models reconstructed in different modalities can be aligned according to the anatomical morphology, and the electrical mapping results of the dynamic heart can be projected onto the corresponding anatomical structure, and finally the propagation of the electroexcitation map throughout the cardiac cycle can be displayed on the dynamic cardiac model according to the conduction velocity within one cardiac cycle. Thus, it is achieved by constructing a dynamic cardiac model of electroanatomical mapping individualized for a specific patient using cardiac electrophysiological and anatomical structure data, thereby reconstructing the human body's dynamic cardiac electroexcitation map, and finally the reconstructed dynamic cardiac electroexcitation map can be used to guide catheter ablation treatment for patients with tachycardia. Thus, it solves the problem that the clinical mapping system or technology in the related art cannot obtain the motion information of the heart, the surgeon can only perform arrhythmia radiofrequency ablation surgery on static images, there are certain inconveniences during the operation, and it cannot meet the use requirements in actual treatment scenarios.

[0108] Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0109] A memory 1101 , a processor 1102 , and a computer program stored in the memory 1101 and executable on the processor 1102 .

[0110] When the processor 1102 executes the program, the method for generating a dynamic cardiac electrical activation map provided in the above embodiment is implemented.

[0111] Furthermore, the electronic device further includes:

[0112] The communication interface 1103 is used for communication between the memory 1101 and the processor 1102 .

[0113] The memory 1101 is used to store computer programs that can be run on the processor 1102 .

[0114] The memory 1101 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0115] If the memory 1101, the processor 1102, and the communication interface 1103 are implemented independently, the communication interface 1103, the memory 1101, and the processor 1102 can be connected to each other via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 11 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0116] Optionally, in a specific implementation, if the memory 1101, the processor 1102 and the communication interface 1103 are integrated on a chip, the memory 1101, the processor 1102 and the communication interface 1103 can communicate with each other through an internal interface.

[0117] The processor 1102 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0118] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for generating a dynamic cardiac electrical activation diagram.

[0119] An embodiment of the present application also provides a computer program product, including a computer program, which can run computer instructions. When the computer instructions are executed by a processor, the method for generating a dynamic cardiac electrical activation map provided in the embodiment of the present application is implemented.

[0120] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0121] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0122] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing a custom logical function or process step, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed in a different order than shown or discussed, including performing functions in a substantially simultaneous manner or in a reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0123] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or N wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing it in other suitable ways as necessary, and then storing it in a computer memory.

[0124] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented using hardware, as in another embodiment, it can be implemented using any one or a combination of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0125] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0126] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0127] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for generating a dynamic cardiac electrical activation diagram, characterized in that: The following steps are involved: Phase-align the electro-activation diagram and the cardiac imaging data of the preset modality to obtain time-domain aligned data; Based on the time domain alignment data, align the heart models reconstructed in different modalities according to the anatomical morphology to obtain space domain alignment data; Based on the time domain alignment data and the space domain alignment data, the electrical mapping results of the dynamic heart are projected onto the corresponding anatomical structure of the dynamic heart, and a dynamic heart model with individualized electroanatomical mapping of the target patient is constructed, so that in one cardiac cycle, the propagation of the electrical activation diagram throughout the cardiac cycle can be displayed on the dynamic heart model according to the conduction velocity.

2. The method according to claim 1, characterized in that The phase alignment of the electro-activation diagram and the cardiac image data of the preset modality includes: Based on the reference signal of the electroacoustic map, the cardiac cycle time is calculated, and the marked point is used as the time zero point in a cardiac cycle to determine the local activation time; Phase alignment is performed based on the local excitation time and the cardiac image data of the preset modality.

3. The method according to claim 1, characterized in that The step of aligning the heart models reconstructed in different modalities according to the anatomical morphology includes: Based on the left ventricle, the right ventricle, the left atrium and / or the right heart, a least squares optimization problem is solved using at least one landmark point reconstructed by the landmark system and at least one landmark point reconstructed by the segmentation to calculate a rigid body transformation between the three-dimensional models; The rigid body transformation between the three-dimensional models is used for alignment, so as to complete the alignment of the heart models reconstructed in different modalities according to the anatomical morphology.

4. The method according to claim 1, characterized in that The step of projecting the electrical mapping result of the dynamic heart onto the corresponding anatomical structure of the dynamic heart comprises: Building a statistical shape model based on training data of known cardiac chamber segmentations; Aligning the statistical shape model with the data to be segmented, so as to match and segment the cardiac chambers in the data to be segmented using the statistical shape model to obtain a segmentation result; The segmentation result is verified to project the electrical mapping result of the dynamic heart onto the corresponding anatomical structure of the dynamic heart.

5. The method according to claim 1, characterized in that The calculation formula of the conduction velocity is: Where T(x) is the local excitation time function at point x, and f(x,t) is the scalar field function that describes the activation wavefront.

6. A device for generating a dynamic cardiac electrical activation diagram, characterized in that: include: A first alignment module is used to perform phase alignment between the electroacoustic activation diagram and the cardiac imaging data of a preset mode to obtain time domain alignment data; A second alignment module is used to align the heart models reconstructed in different modalities according to the anatomical morphology based on the time domain alignment data to obtain space domain alignment data; A generation module is used to project the electrical mapping results of the dynamic heart onto the corresponding anatomical structure of the dynamic heart based on the time domain alignment data and the space domain alignment data, and to construct a dynamic heart model with individualized electroanatomical mapping of the target patient, so as to display the propagation of the electrical activation diagram throughout the cardiac cycle according to the conduction velocity on the dynamic heart model in one cardiac cycle.

7. The device according to claim 6, characterized in that The first alignment module comprises: A calculation unit, used for calculating the cardiac cycle time based on the reference signal of the electro-activation diagram, and taking the marked point as the time zero point in a cardiac cycle to determine the local activation time; An alignment unit is used to perform phase alignment based on the local excitation time and the cardiac image data of the preset modality.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for generating a dynamic cardiac electrical activation diagram as described in any one of claims 1-5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for generating a dynamic cardiac electrical activation map as described in any one of claims 1-5.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed, it is used to implement the method for generating a dynamic cardiac electrical activation map as described in any one of claims 1-5.

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