Heart electrophysiology simulation system

Abstract

The application provides a heart electrophysiology simulation system, comprising: an image acquisition module for acquiring a plurality of thoracic cavity images; the three-dimensional grid reconstruction module is used for obtaining a ventricle three-dimensional grid through a finite element method according to the plurality of thoracic cavity images; the ventricular conduction network construction module is used for generating a ventricular conduction network according to the ventricular three-dimensional grid, the ventricular conduction network comprises a plurality of first grid points, and the geometric position of each first grid point shares the point cloud of the ventricular three-dimensional grid; the electrophysiological parameter simulation module is used for simulating the conduction process of the heart action potential in the ventricle according to the geometric position of the first grid point and electrophysiological parameters, and the electrophysiological parameters comprise cell level parameters and tissue level parameters; and the dynamic simulation module is used for simulating the cardiac electric signal according to the conduction process of the cardiac action potential in the ventricle to obtain a dynamic simulation result.

Description

Technical Field

[0001] The present application mainly relates to the field of biomedical engineering simulation, and in particular to a cardiac electrophysiological simulation system. Background Art

[0002] Simulation technology based on the heart can simulate heart characteristics, diseases, etc., and can help doctors diagnose or evaluate diseases, which is of great significance. At present, in the simulation research of the heart, it is usually through a relatively large number of electrodes to collect multi-lead ECG signals on the surface of the trunk, and then through the conduction matrix, the distribution of the epicardial action potential phase diagram is inferred in the form of an ECG inverse problem, and then the lesions and treatment plans are evaluated. However, the relevant technologies of the ECG inverse problem face difficulties in principle and accuracy. In principle, the ECG inverse problem relies on the boundary element method to calculate the conduction matrix between the epicardium and the geometric grids on the trunk surface to establish the relationship between the potentials on the corresponding grids. The calculation of the conduction matrix is ​​very sensitive to the accuracy of the geometric grid, and is interfered by the physiological parameters of the patient's own chest, lungs and other organs, resulting in limited accuracy of the obtained conduction matrix. In addition, the equations solved by the inverse problem are severely underdetermined equations, which makes the numerical solution seriously unstable during calculation. The accuracy and number of electrodes on the trunk surface are used as input parameters, and for underdetermined equations, the accuracy required to eliminate this instability cannot always be achieved.

[0003] Therefore, the accuracy of the solution obtained by the inverse problem is very limited. If it is used to predict the lesion point, such as the arrhythmia lesion point, its accuracy is not reliable.

[0004] The inventor of the present application proposed a simulation system for evaluating cardiac ablation schemes in a Chinese patent application with publication number CN119028528A, which can more accurately simulate the electrophysiological activity of actual myocardial fibers. In order to more accurately simulate the actual pacing process of the heart and simulate the conduction of electrical signals in the His bundle and Purkinje fiber cell network, the inventor of the present application proposed the cardiac electrophysiological simulation system of the present application. Summary of the invention

[0005] In view of the above technical problems, the present application provides a cardiac electrophysiological simulation system, which can simulate the ventricular conduction network including the His bundle and the Purkinje fiber network, and realize the simulation of the overall cardiac electrophysiological activity.

[0006] To solve the above technical problems, the present application provides a cardiac electrophysiological simulation system, comprising: an image acquisition module, used to acquire multiple chest images, wherein the chest images include ventricular images; a three-dimensional grid reconstruction module, used to obtain a ventricular three-dimensional grid according to the multiple chest images by a finite element method; a ventricular conduction network construction module, used to generate a ventricular conduction network according to the ventricular three-dimensional grid to simulate the conduction of cardiac action potentials in the ventricles, wherein the ventricular conduction network includes a His bundle and a Purkinje fiber network, and the ventricular conduction network includes multiple first grid points, and the geometric position of each first grid point shares the point cloud of the ventricular three-dimensional grid; an electrophysiological parameter simulation module, used to simulate the conduction process of cardiac action potentials in the ventricles according to the geometric position and electrophysiological parameters of the first grid points, wherein the electrophysiological parameters include cell-level parameters and tissue-level parameters, the cell-level parameters include current parameters of ion channels, and the tissue-level parameters include conductivity, electrical signal propagation rate and pacing stimulation parameters; and a dynamic simulation module, used to simulate cardiac electrical signals according to the conduction process of the cardiac action potentials in the ventricles to obtain dynamic simulation results.

[0007] In one embodiment of the present application, the ventricular conduction network construction module is configured to use the following method to simulate and generate the ventricular conduction network: using a fractal method to form a two-dimensional fractal network; projecting the two-dimensional fractal network onto the endocardial surface to generate a three-dimensional fractal network, wherein the endocardial surface is a non-smooth surface; and using the three-dimensional fractal network as the ventricular conduction network.

[0008] In one embodiment of the present application, the fractal method is used to form a two-dimensional fractal network, including: using the fractal method to create initial nodes and initial branches of the two-dimensional fractal network, the initial branches having an initial growth direction; creating multiple new branches from the ends of the initial branches, and iteratively creating new branches of the next generation from the new branches to generate the two-dimensional fractal network, wherein during the iteration process, fractal motion parameters are set according to the geometric structure of the ventricle, and the fractal motion parameters include: branch length, branch angle and repulsion parameter.

[0009] In one embodiment of the present application, each branch includes n line segments and n+1 nodes, and the n+1 nodes mutually exclude each other to generate a curve, wherein the direction vector of each node is determined by the direction vector of the previous node and the distance gradient, and n is a natural number.

[0010] In one embodiment of the present application, the projecting of the two-dimensional fractal network onto the endocardial surface to generate a three-dimensional fractal network includes: obtaining the vertex normal of the current node, the vertex normal being the weighted sum of all normals of adjacent fractal grids of the current node; projecting the current node onto the surface defined by the fractal grid through the vertex normal; determining whether the projection result of the current node is located within the fractal grid; if the projection result of the current node is not located within the fractal grid, projecting the projection result onto the surface through the surface normal of the grid unit.

[0011] In one embodiment of the present application, the projection result is projected onto the surface through the surface normal of the grid unit, including: calculating the direction vectors on all k-1 nodes before the current k-th node, k is a positive integer; projecting the k-th node to the surface according to the direction vector and the length of the branch line segments of all k-1 nodes; if the projected k-th node is located in the fractal grid, or the node line segment length is greater than or equal to a preset range, continue to project the next node, otherwise stop the iterative process.

[0012] In one embodiment of the present application, the distance gradient is calculated using the following formula: : , Among them, ϵ is a preset constant, e i represents a Cartesian basis vector, k represents the serial number of the current node on the ventricular conduction network, i represents a component x, y, z of the three-dimensional coordinate, g represents the distance gradient, p k represents the length of the line segment of the kth node on the 3D grid of the ventricle, dist cp Represents a function that returns the distance from node k to the nearest node in the network.

[0013] In one embodiment of the present application, the direction vector d of the kth node is calculated using the following formula: k : , Among them, w represents the repulsion parameter of the fractal structure, d k-1 represents the direction vector of the k-1th node, represents the distance gradient of the k-1th node; According to the direction vector d, the following formula is used: k And the branch line segment lengths of all k-1 nodes project the kth node onto the surface: .

[0014] In one embodiment of the present application, the direction vector is initialized using the following formula: , Among them, d 0 Represents the initial direction vector of the initial node, n 0 represents the initial normal vector of the initial node, and α represents the single-step change angle of the branch angle.

[0015] In one embodiment of the present application, the fractal method includes a kd tree method.

[0016] In an embodiment of the present application, the pacing stimulation parameter corresponds to a pacing stimulation, and the pacing stimulation includes a stimulation signal applied to the His bundle.

[0017] In one embodiment of the present application, the three-dimensional grid reconstruction module is also used to mark the ablation points of the multiple chest images, and obtain the three-dimensional grid of the heart through the finite element method, and the ablation points include estimated ablation points to be ablated, and / or actual ablation points where ablation has been performed; the cardiac electrophysiological simulation system also includes: a fiber rotation direction calculation module, which is used to calculate the myocardial fiber rotation direction according to the three-dimensional grid of the heart to obtain the direction vector of the myocardial fiber rotation direction corresponding to each second grid point on the three-dimensional grid of the heart; the electrophysiological parameter simulation module is also used to simulate the cardiac action potential excitation process according to the geometric position of the second grid point, the fiber rotation direction corresponding to the second grid point and the electrophysiological parameters, wherein the electrophysiological parameters include cell level parameters and tissue level parameters, the cell level parameters include current parameters of ion channels, and the tissue level parameters include conductivity of different heart regions, pacing stimulation parameters and the propagation rate of electrical signals set according to the direction vector of the myocardial fiber rotation direction.

[0018] In one embodiment of the present application, the electrophysiological parameter simulation module obtains the current parameters of the ion channel corresponding to each first grid point on the ventricular conduction network based on the first ion channel model, and obtains the current parameters of the ion channel corresponding to each second grid point on the three-dimensional grid of the heart based on the second ion channel model, and the first ion channel model and the second ion channel model are different.

[0019] In one embodiment of the present application, the first grid point and the second grid point share the point cloud of the ventricular three-dimensional grid, the end of the ventricular conduction network is connected to the end of the cardiac three-dimensional grid, and the electrical signal can be conducted from the ventricular conduction network to the cardiac three-dimensional grid.

[0020] The cardiac electrophysiological simulation system of the present application obtains multiple chest images through an image acquisition module, simulates the conduction of cardiac action potentials in the ventricles through a ventricular conduction network construction module, sets the physiological parameters corresponding to each first grid point in the ventricular conduction network through an electrophysiological parameter simulation module, and simulates the cardiac electrical signals through the conduction process of cardiac action potentials in the ventricles through a dynamic simulation module. It can realize personalized cardiac electrophysiological simulation for the subjects, with accurate results and good timeliness, which is conducive to assisting users in applying the simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are included to provide a further understanding of the present application. They are included and constitute a part of the present application. The accompanying drawings illustrate embodiments of the present application and together with the present specification serve to explain the principles of the present application. In the accompanying drawings: Figure 1 is a block diagram of a cardiac electrophysiological simulation system according to an embodiment of the present application; Figure 2 is an exemplary flow chart of generating a ventricular conduction network by a ventricular conduction network construction module in a cardiac electrophysiology simulation system according to an embodiment of the present application; Figure 3 This is an exemplary flow chart of a ventricular conduction network construction module in a cardiac electrophysiology simulation system according to an embodiment of the present application using a fractal method to form a two-dimensional fractal network; Figure 4 is an exemplary flow chart of a two-step projection method adopted by a ventricular conduction network construction module in a cardiac electrophysiology simulation system according to an embodiment of the present application; Figure 5 It is a schematic diagram of a single-step projection method; Figure 6 is a schematic diagram of a two-step projection method according to an embodiment of the present application; Figure 7 This is an exemplary flow chart of a ventricular conduction network construction module in a cardiac electrophysiology simulation system according to an embodiment of the present application projecting a current node onto a surface through the normal of a grid unit. DETAILED DESCRIPTION

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0023] As shown in this application, unless the context clearly indicates an exception, the words "a", "an", "a kind" and / or "the" do not refer to the singular, but also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0024] Unless otherwise specifically stated, the relative arrangement, numerical expressions and numerical values ​​of the parts and steps set forth in these embodiments do not limit the scope of the application. Meanwhile, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to actual proportional relationships. The technology, methods and equipment known to those of ordinary skill in the relevant art may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be considered as a part of the specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0025] In the description of the present application, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present application and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction, and therefore cannot be understood as limiting the scope of protection of the present application; the directional words "inside and outside" refer to the inside and outside relative to the contours of each component itself.

[0026] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatially relative descriptions used here are interpreted accordingly.

[0027] In addition, it should be noted that the use of words such as "first" and "second" to define components is only for the convenience of distinguishing the corresponding components. If not otherwise stated, the above words have no special meaning and cannot be understood as limiting the scope of protection of this application. In addition, although the terms used in this application are selected from well-known and commonly used terms, some terms mentioned in the specification of this application may be selected by the applicant at his or her discretion, and their detailed meanings are explained in the relevant parts of the description of this article. In addition, it is required to understand this application not only by the actual terms used, but also by the meaning implied by each term.

[0028] Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps may be processed in reverse order or simultaneously. At the same time, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0029] The cardiac electrophysiology simulation system of the present application is an improvement on a simulation system for cardiac ablation scheme evaluation proposed by the inventor of the present application in Chinese patent application publication number CN119028528A. The entire contents of CN119028528A can be used to assist in explaining the relevant contents of the simulation system of the present application.

[0030] The cardiac electrophysiological simulation system of the present application can simulate the electrophysiological activities of the heart, especially the conduction process of the cardiac action potential in the ventricles, thereby simulating the conduction process of the real cardiac electrical excitation in the whole heart including the ventricles.

[0031] Figure 1 is a block diagram of a cardiac electrophysiological simulation system according to an embodiment of the present application. Figure 1As shown, the cardiac electrophysiological simulation system 100 of this embodiment includes an image acquisition module 110 , a three-dimensional grid reconstruction module 120 , a ventricular conduction network construction module 130 , an electrophysiological parameter simulation module 140 and a dynamic simulation module 150 . Among them, the image acquisition module 110 is used to acquire multiple chest images, which include ventricular images; the three-dimensional grid reconstruction module 120 is used to obtain the ventricular three-dimensional grid by the finite element method based on the multiple chest images; the ventricular conduction network construction module 130 is used to generate a ventricular conduction network based on the ventricular three-dimensional grid to simulate the conduction of cardiac action potentials in the ventricles, wherein the ventricular conduction network includes the His bundle and the Purkinje fiber network, and the ventricular conduction network includes multiple first grid points, and the geometric position of each first grid point shares the point cloud of the ventricular three-dimensional grid; the electrophysiological parameter simulation module 140 is used to simulate the conduction process of cardiac action potentials in the ventricles according to the geometric position and electrophysiological parameters of the first grid points, wherein the electrophysiological parameters include cell-level parameters and tissue-level parameters, the cell-level parameters include the current parameters of ion channels, and the tissue-level parameters include conductivity, electrical signal propagation rate and pacing stimulation parameters; the dynamic simulation module 150 is used to simulate the cardiac electrical signal according to the conduction process of the cardiac action potential in the ventricles to obtain a dynamic simulation result.

[0032] The image acquisition module 110 , the three-dimensional grid reconstruction module 120 , the ventricular conduction network construction module 130 , the electrophysiological parameter simulation module 140 and the dynamic simulation module 150 are described in detail below.

[0033] This application does not limit how the image acquisition module 110 obtains the chest images.

[0034] In some embodiments, the image acquisition module 110 is specifically implemented as an MRI device, and more specifically, can be implemented as an LGE-MRI device for obtaining LGE-MRI enhanced magnetic resonance images.

[0035] In some embodiments, the image acquisition module 110 is specifically implemented as a medical imaging device such as CT.

[0036] The three-dimensional mesh reconstruction module 120 obtains the required multiple chest images from the image acquisition module 110. In some embodiments, the multiple chest axial enhanced MRI slice images are segmented into the left ventricular endocardium, the right ventricular endocardium and the epicardium, which is equivalent to marking the boundaries of the left ventricular endocardium, the right ventricular endocardium and the epicardium on each chest image. Further, the three-dimensional mesh reconstruction module 120 obtains a ventricular three-dimensional mesh based on the multiple chest images by a finite element method. The ventricular three-dimensional mesh corresponds to the ventricle, including the left ventricle and / or the right ventricle, which includes multiple grid points. The present application does not limit the mesh form, which can be a triangular mesh, a tetrahedral mesh, a hexahedral mesh, etc. The finite element method used is a common method in the field and will not be described in detail here.

[0037] In other embodiments, for example, for the atrial region, the same operation can also be used to mark the outer surface of the left atrium, right atrium and atrium. In this way, a three-dimensional mesh of the atrium can be generated. It can be understood that in some embodiments, a three-dimensional mesh of the heart including the atrium and ventricle can be generated. At the same time, the abnormal area on the MRI slice image can also be marked by finite element software. The present application does not limit the number of chest images. The multiple chest images can be multiple chest slice images from a subject. The more chest images, the more conducive to the subsequent simulation and emulation process.

[0038] It should be noted that the His bundle and Purkinje fiber network are key components of the cardiac excitation system. Purkinje fibers, also known as bundle cells, are a special type of myocardial fiber. The Purkinje fiber network is composed of special fast-conducting cells and is located under the endocardium, just below the inner wall of the heart. Compared with myocardial cells, Purkinje cells are larger, have fewer myofibrils, and more mitochondria, so as to efficiently and quickly conduct excitation waves. The present application can generate a ventricular conduction network according to the ventricular three-dimensional grid simulation through the ventricular conduction network construction module 130, simulate the conduction of cardiac action potentials in the ventricles, and simulate the conduction process of emulation cardiac electrical signals through the His bundle and Purkinje fiber network, which is conducive to discovering problems in the electrophysiological conduction of the patient's ventricles. The application of the simulation results is not limited to the diagnosis of heart-related diseases, but can also be used for other scientific research purposes such as drug development.

[0039] In some embodiments, a finite element method may be used to simulate and generate the ventricular conduction network.

[0040] Figure 2 FIG. 1 is an exemplary flow chart of a ventricular conduction network construction module in a cardiac electrophysiology simulation system according to an embodiment of the present application generating a ventricular conduction network. Figure 2As shown, in this embodiment, the ventricular conduction network construction module is configured to simulate and generate the ventricular conduction network using the following method:

[0041] Step S210: using a fractal method to form a two-dimensional fractal network; Step S220: Projecting the two-dimensional fractal network onto the endocardial surface to generate a three-dimensional fractal network, wherein the endocardial surface is a non-smooth surface; and Step S230: using the three-dimensional fractal network as the ventricular conduction network.

[0042] The fractal method is a mathematical method for generating complex self-similar structures, which is widely used in computer graphics, natural phenomenon simulation, art design and other fields. Its basic implementation method is to generate structures with sub-similarity by recursion or iteration. The inventor of the present application found that the His bundle and Purkinje fiber network also show certain self-similarity at different scales, so the fractal method is applied to the cardiac electrophysiology simulation system of the present application.

[0043] The fractal method is generally applied to two-dimensional space or two-dimensional graphics. In step S210, a two-dimensional fractal network is first formed using the fractal method. Figure 3 This is an exemplary flow chart of a ventricular conduction network construction module in a cardiac electrophysiology simulation system according to an embodiment of the present application using a fractal method to form a two-dimensional fractal network. Figure 3 As shown, in this embodiment, step S210 specifically includes: Step S211: using a fractal method to create initial nodes and initial branches of a two-dimensional fractal network, where the initial branches have an initial growth direction; Step S212: Create multiple new branches from the end of the initial branch, and iteratively create the next generation of new branches from the new branches to generate a two-dimensional fractal network, wherein during the iteration process, the fractal motion parameters are set according to the geometric structure of the ventricle, and the fractal motion parameters include: branch length, branch angle α and rejection parameter w.

[0044] In some implementations, the fractal method includes a kd tree method, or "kd tree algorithm". The kd tree is a data structure for organizing multidimensional spatial data, mainly used to efficiently perform spatial search operations, such as nearest neighbor search, range search, etc. The kd tree method constructs a binary tree structure by recursively dividing the data space into two subspaces. At each level, the kd tree selects a dimension as the partition axis, and divides the data points into two parts according to the median value of the dimension, which are stored in the left subtree and the right subtree of the tree respectively.

[0045] When the kd tree method is adopted, "creating multiple new branches from the end of the initial branch" in step S212 includes: creating 2 new branches from the end of the initial branch.

[0046] The present application adopts a kd tree method in a fractal method to generate a two-dimensional fractal network for simulating a ventricular conduction network. Specifically, the present application adopts a kd tree construction strategy to determine the collision between two nodes in the ventricular conduction network. In order to detect potential collisions, all nodes in the ventricular conduction network are considered, excluding nodes in the mother branch and sibling branches. If the distance between the new node and any existing node is less than a certain tolerance, the branch can no longer grow and the new node is removed. In some cases, a closed loop can be created by adding the closest node in the network as the last node in the branch.

[0047] In some embodiments, the above fractal method includes three random sources: first, from mean β, variance 0.4β 2 The branch length of each branch k is calculated from the normal distribution of ; secondly, the order of growing branches is randomly disrupted in each generation to randomly distribute the impact of curvature on existing nodes; thirdly, the order of growing sub-branches is randomly disrupted. The following is a pseudo code example of a kd tree fractal growth algorithm: for generation = 1 to total number of generations Disrupt the current node for node in current node for current child node = 1 to total number of child nodes Create a new child node If the child node does not touch the existing shape and is within the boundary The child node is added to the current node According to the above pseudo code example, the two-dimensional fractal network in step S210 can be formed.

[0048] In step S212, the repulsion parameter is used to adjust the curvature of the branch. The larger the repulsion parameter, the stronger the repulsion between the branches. The fractal motion parameters are all set according to the ventricular three-dimensional grid. The ventricular three-dimensional grid comes from the heart three-dimensional grid constructed by the three-dimensional grid reconstruction module 120. In this way, it is possible to achieve a personalized construction of the ventricular conduction network for the ventricle of a certain subject.

[0049] In some embodiments, each branch includes n line segments and n+1 nodes, so that each branch is represented as a broken line with n+1 nodes. Among them, the n+1 nodes mutually exclude each other to generate a curve, which can be achieved by determining the direction vector of each line segment in the branch. Specifically, the direction vector of each node is determined by the direction vector of the previous node and the distance gradient, and n is a natural number. The specific calculation method of the distance gradient and its application will be described later.

[0050] After the ventricular conduction network construction module 130 obtains the two-dimensional fractal network in step S210, in step S220, the two-dimensional fractal network is projected onto the endocardial surface to generate a three-dimensional fractal network.

[0051] It should be noted that the endocardial surface is a non-smooth surface. In some embodiments, the projection step in step S220 includes: projecting the node onto the plane defined by the fractal grid through the normal of the fractal grid, and checking whether the projected node is inside the fractal grid. If so, it means that the projection result is available, otherwise, it means that the projection result is not available. It should be noted that the shape of the fractal grid can be a triangle, a polygon, etc. In each iteration of the fractal method, when a new branch is generated, the new node is projected so that the two-dimensional fractal network is projected into a three-dimensional fractal network. This projection method is also called single-step projection. For regular and smooth surfaces, single-step projection can achieve better results. However, in some cases, for irregular and non-smooth surfaces, the single-step projection effect is poor and may fail. This is because when there are sharp angles on the surface, the single-step projection method will have blind spots. Therefore, in some embodiments, the present application adopts a two-step projection method. Figure 4 FIG. 1 is an exemplary flow chart of a two-step projection method used by a ventricular conduction network construction module in a cardiac electrophysiology simulation system according to an embodiment of the present application. Figure 4 As shown, the two-step projection method includes: Step S221: obtaining the vertex normal of the current node, where the vertex normal is the weighted sum of all normals of adjacent fractal meshes of the current node; Step S222: Projecting the current node onto the surface defined by the fractal grid through the vertex normal; Step S223: determining whether the projection result of the current node is within the fractal grid; Step S224: If the projection result of the current node is not located in the fractal grid, the projection result is projected onto the surface through the surface normal of the grid unit.

[0052] Among them, steps S221-S222 are an additional pre-projection step based on the single-step projection, and step S224 is the second projection step. If the judgment result of step S223 is "yes", step S224 is not required.

[0053] Figure 5 is a schematic diagram of a single-step projection method. Figure 5 As shown in Figure 1, when there is a sharp angle on the surface, the single-step projection method has a blind area, so that the projected points in the blind area cannot be projected onto the mesh surface. Figure 5 The area shown by the inverted triangle including the projected point. Figure 5 The projection points P1 and P2 in are both outside the fractal grid.

[0054] According to the above embodiment, in step S222, pre-projection is first attempted once using the vertex normal, and then based on the pre-projection result, the surface normal of the mesh unit is used for re-projection, which can ensure that the projection result is on the surface defined by the fractal mesh.

[0055] Figure 6 Schematic diagram of a two-step projection method according to an embodiment of the present application. Figure 6 As shown, first, in step S222, a pre-projection is performed along the vertex normal 610 to obtain a projection point P3. The projection point P3 is located outside the fractal grid. Secondly, in step S224, the projection point P3 is projected onto the grid surface through the surface normal 620 of the grid unit to obtain a projection point P4. The projection point P4 is located inside the fractal grid.

[0056] The above embodiment adopts a two-step projection method, so that the projected points in the blind area can also be projected onto the grid surface.

[0057] Figure 7 This is an exemplary flow chart of a ventricular conduction network construction module in a cardiac electrophysiology simulation system according to an embodiment of the present application projecting a projection result onto a surface through the surface normal of a grid unit. Figure 7 As shown, in this embodiment, projecting the projection result onto the surface through the surface normal of the grid unit in step S224 includes: Step S2241: Calculate the direction vector of the k-1 nodes before the current k-th node, where k is a positive integer; Step S2242: projecting the kth node onto the surface according to the direction vector and the lengths of the branch line segments of all k-1 nodes; Step S2243: If the kth node after projection is located in the fractal grid, or the length of the node line segment is greater than or equal to a preset range, continue to project the next node, otherwise stop the iteration process.

[0058] In some embodiments, the distance gradient is calculated using a central finite difference approximation. For example, the distance gradient is calculated using the following formula (1): : (1) Among them, ϵ is a preset constant, e i represents the Cartesian basis vector, k represents the serial number of the current node on the ventricular conduction network, i is a component of the three-dimensional coordinate x, y, z, g represents the gradient of distance, p k represents the length of the line segment of the kth node on the 3D grid of the ventricle, dist cp Represents a function that returns the distance from node k to the nearest node in the network.

[0059] In some embodiments, the direction vector d of the current k-th node in step S2241 is calculated using the following formula (2): k : (2) Among them, w represents the rejection parameter, d k-1 represents the direction vector of the k-1th node, represents the distance gradient of the k-1th node; The following formula (3) is used to implement the step S2242 according to the direction vector d k The lengths of the branch segments of all k-1 nodes are projected onto the surface to form the kth node: (3) In some embodiments, before step S2241, an initialization step is also included. For example, the direction vector d is initialized using the following formula: 0 : (4) Among them, d 0 Represents the initial direction vector of the initial node, n 0 represents the initial normal vector of the initial node, and α represents the single-step change angle of the branch angle. These initial parameters can be set based on experience.

[0060] A pseudo code example for implementing step S224 is given below:

[0061] for k=1 to total number of generations Calculate all nodes p before the kth node k-1 The gradient direction on : , Also projects nodes onto the mesh surface .

[0062] If p k Out of grid or less than error Break Need to explain, p k represents the length of the line segment of the kth node on the 3D grid of the ventricle. The length of the line segment is calculated from the coordinates of the line segment in 3D space. Therefore, p k It includes three-dimensional coordinate information. According to the three-dimensional coordinate information, p k Whether the line segment represented by it exceeds the grid. At the same time, according to p k The length of the line segment represented by the pixel is used to determine whether it is less than the error. The error can be set manually based on experience.

[0063] refer to Figure 1 The electrophysiological parameter simulation module 140 can simulate and generate electrophysiological parameters corresponding to the ventricular conduction network from the cell level and the tissue level, so that each first grid point on the ventricular conduction network has a corresponding electrophysiological parameter.

[0064] In some embodiments, the electrophysiological parameter simulation module 140 obtains the current parameters of the ion channel corresponding to each first grid point on the ventricular conduction network based on the first ion channel model. The electrophysiological parameters can be built into the electrophysiological parameter simulation module 140, or set by the user through a graphical user interface. In one embodiment, the ion channel model is the Stewart model (Stewart, 2009). The transmembrane domain of the ion channel constitutes an aqueous pore that allows ions to pass smoothly. It can only allow specific ions to pass through, and controls the transmembrane flow of specific ions by opening and closing a "gate". Many different types of ion channels can usually be found on the myocardial cell membrane, among which sodium (Na+), potassium (K+) and calcium (Ca2+) channels are the main types of ion channels. The present application does not limit the type of ion channel. The ion current satisfies the basic Ohm's law, Ix=Gxp(Vm-Ex), where Ix represents the ion current of ion x, Gx represents the maximum conductance of ion x, Vm represents the transmembrane potential, Ex represents the equilibrium potential of ion x, and p represents the open probability coefficient of the ion channel. Ion channels are voltage-gated, that is, the opening and closing of ion channels are influenced by the transmembrane potential on both sides of the membrane.

[0065] In the tissue dimension, electrophysiological parameters include conductivity, electrical signal propagation rate and pacing stimulation parameters of different cardiac regions. It should be noted that the conductivity and electrical signal propagation rate of Purkinje fiber cells in normal areas are different from those in abnormal areas. Pacing stimulation parameters can be set according to the clinical requirements of the patient. In some embodiments, the pacing stimulation parameters correspond to pacing stimulation, and the pacing stimulation includes a stimulation signal applied to the His bundle. For example, in order to simulate normal sinus rhythm, a stimulation signal simulating a normal heart pacing signal is applied to the His bundle. The location of the stimulation point can be the starting point of the His bundle, that is, the location of the atrioventricular node. In order to simulate abnormal heart rhythms, such as arrhythmias, a stimulation signal simulating an abnormal heart pacing signal is applied to the His bundle. The location of the stimulation point can be the position corresponding to any node in the ventricular conduction network.

[0066] Based on the above content, the electrophysiological parameter simulation module 140 can simulate the conduction process of the cardiac action potential in the ventricle. On this basis, the dynamic simulation module 150 can simulate the cardiac electrical signal according to the conduction process of the cardiac action potential in the ventricle to obtain the simulation result. The dynamic simulation module 150 can visualize the simulation result.

[0067] Specifically, in one embodiment, the dynamic simulation module 150 simulates the cardiac electrical signal based on the Reaction-Diffusion diffusion process, and the simulation process includes: Step S310: Taking the transmembrane point position and reset voltage on the time-space evolution scale as the contraction variables u, v and the nonlinear response functions f, g, satisfying equations (5) and (6): (5) (6) in, and are the coefficients corresponding to the shrinkage variables u and v, ∇ 2 is the Laplace operator, More specifically, D1 and D2 are used to characterize the conductivity of the corresponding diffusion process in the transmembrane current and the slow local recovery current in the ion channel model.

[0068] It should be noted that cardiac electrical activity in a single cell involves the coordinated transport of a large number of ions through various biological channels. Electrical waves also propagate from cells to the entire heart, combining excitation with contraction and blood discharge. Some simplifying assumptions and rules, such as cellular automata models, are limited in their ability to simulate cardiac electrical activity, especially at the level of the entire heart. The reaction-diffusion model describes the distribution changes of dynamic variables in space and time, which includes two processes: (1) reaction process: dynamic variables interact to transform, and (2) diffusion process: dynamic variables diffuse in space. The potential propagation process determined by the reaction-diffusion model is reflected in the time-space evolution as a continuously diffusing contour map boundary ∂Ω. Therefore, the reaction-diffusion model can more realistically simulate the electrical activity of the entire heart.

[0069] Step S320: Discretize equations (5) and (6) in step S310 in the time dimension, set t=1,2,…,T, and record the grid point sequence i=1,2,…,N in the ventricular conduction network, and obtain the following equation: (7) (8) Step S330: Write the equation in step S320 into the following matrix: (9) in, , ; Similarly, the matrix forms of B1, B2, F, and G can be determined. Among them, , B1 and B2 are the corresponding coefficient matrices. The specific parameters of this matrix need to be determined by the finite element form of the Laplacian operator on the corresponding mesh. For a triangular mesh, the Laplacian operator acts on a variable u. ,in Yes 2 M is called the Massmatrix, and L is the Laplacian matrix.

[0070]

[0071] where θ ij and The mass matrix M is a diagonal matrix related to the area of ​​the finite element triangle where each grid point is located. , in, , find the area of ​​the triangle adjacent to i by cross product of the measured coordinates. At this time, the coefficients of formula (9) can be determined and satisfy the form of Ax=b, so it can be solved.

[0072] Step S340: Use an optimization method to solve the matrix in step S330 to obtain U t and V t .

[0073] The solution can be obtained by using an optimization method commonly used in the art, and this application does not limit the specific optimization method.

[0074] In one embodiment, in order to simulate the dynamic process in time and space, a nonlinear reaction-diffusion model is used. Specifically, in step S310, the Fitzhugh-Nagumo model is used to change the functions f and g (giving the functions f and g a specific form) to obtain: (10) (11) Formula (10) and formula (11) correspond to functions f and g, respectively. Among them, C1 and C2 are parameters related to the curve shape of function f, 1 / b is the average time constant of the slow current passing through the ion channel, a is a parameter related to the resting voltage, and d is the ratio of the transmembrane current and the slow local recovery current in the ion channel. Parameters a, b, C1, C2, and d are all related to the specific ion channel model, and their actual values ​​need to be determined by the shape of the action potential curve of the model. According to the functions f and g obtained from the above formulas (10) and (11), the diffusion equations of the variables u and v shown in equations (5) and (6) satisfy: .

[0075] In an embodiment using the Stewart ion channel model, the correlation coefficients may be set as follows: D1=1, D2=0, a=0.13, b=0.026, C1=0.52, C2=0.1, d=1.

[0076] like Figure 1 As shown, in some embodiments, the cardiac electrophysiological simulation system 100 of the present application may further include a fiber handedness calculation module 160 .

[0077] like Figure 1 As shown, in some embodiments, the three-dimensional grid reconstruction module 120 of the cardiac electrophysiological simulation system 100 of the present application is also used to mark the ablation points of multiple chest images, and obtain the cardiac three-dimensional grid by the finite element method, and the ablation points include the estimated ablation points to be ablated, and / or the actual ablation points that have been ablated. It should be noted that the cardiac three-dimensional grid includes the ventricular three-dimensional grid described above. In addition, the cardiac electrophysiological simulation system 100 of the present application also includes a fiber rotation direction calculation module 160, which is used to calculate the myocardial fiber rotation direction according to the cardiac three-dimensional grid to obtain the direction vector of the myocardial fiber rotation direction corresponding to each second grid point on the cardiac three-dimensional grid. In these embodiments, the electrophysiological parameter simulation module 140 is also used to simulate the cardiac action potential excitation process according to the geometric position of the second grid point, the fiber rotation direction corresponding to the second grid point, and the electrophysiological parameters, wherein the electrophysiological parameters include cell level parameters and tissue level parameters, the cell level parameters include the current parameters of the ion channel, and the tissue level parameters include the conductivity of different cardiac regions, pacing stimulation parameters, and the propagation rate of the electrical signal set according to the direction vector of the myocardial fiber rotation direction. The three-dimensional mesh reconstruction module 120, fiber rotation direction calculation module 160 and electrophysiological parameter simulation module 140 can be specifically implemented as the three-dimensional mesh reconstruction module, fiber rotation direction calculation module and electrophysiological parameter simulation module in patent CN119028528A. Therefore, the relevant content can refer to the content recorded in patent CN119028528A and will not be repeated here.

[0078] In one embodiment of the present application, the electrophysiological parameter simulation module 140 obtains the current parameters of the ion channel corresponding to each first grid point on the ventricular conduction network based on the first ion channel model, and obtains the current parameters of the ion channel corresponding to each second grid point on the three-dimensional grid of the heart based on the second ion channel model, and the first ion channel model and the second ion channel model are different.

[0079] In some embodiments, the first grid point and the second grid point share a grid point cloud, the end of the ventricular conduction network is connected to the end of the heart three-dimensional grid, and the electrical signal can be conducted from the ventricular conduction network to the heart three-dimensional grid. The grid point cloud may include coordinate data corresponding to all coordinate positions of the entire heart. The first grid point and the second grid point may share the grid point cloud, but the corresponding parameters are different. Among them, the heart three-dimensional grid is used to simulate ordinary myocardial cells, and the parameters corresponding to the second grid point are the relevant parameters of ordinary myocardial cells; the ventricular conduction network is used to simulate the His bundle and Purkinje fiber network, and the parameters corresponding to the first grid point are the relevant parameters of the His bundle and Purkinje fiber network. Among them, when the pacing stimulus is applied via the His bundle, the electrical signal can be conducted from the end of the ventricular conduction network to the heart three-dimensional grid, thereby realizing the linkage simulation of the two networks.

[0080] like Figure 1 As shown, in some embodiments, the cardiac electrophysiological simulation system 100 of the present application further includes an evaluation module 170. The evaluation module 170 is used to provide an evaluation result based on the dynamic simulation result. For example, when evaluating a cardiac ablation plan, the evaluation result includes whether to change the ablation point and whether to use the electrophysiological parameter simulation module 140 for simulation again. The evaluation module 170 can be specifically implemented as the evaluation module in patent CN119028528A, and the contents recorded in patent CN119028528A can be referred to, and no further description is given.

[0081] The present application uses specific words to describe the embodiments of the present application. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or multiple times in different positions in this specification does not necessarily refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present application can be appropriately combined.

[0082] Some aspects of the present application may be performed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". The processor may be one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. In addition, various aspects of the present application may be represented as computer products located in one or more computer-readable media, which include computer-readable program codes. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, tapes ...), optical disks (e.g., compact disks CDs, digital versatile disks DVDs ...), smart cards, and flash memory devices (e.g., cards, sticks, key drives ...).

[0083] A computer-readable medium may include a propagated data signal containing computer program code, such as in baseband or as part of a carrier wave. The propagated signal may have a variety of manifestations, including electromagnetic, optical, etc., or a suitable combination. A computer-readable medium may be any computer-readable medium other than a computer-readable storage medium, which may be connected to an instruction execution system, device or apparatus to communicate, propagate or transmit a program for use. The program code on the computer-readable medium may be propagated via any suitable medium, including radio, cable, fiber optic cable, radio frequency signal, or similar medium, or any combination of the above mediums.

[0084] Similarly, it should be noted that in order to simplify the description of the disclosure of this application and thus help understand one or more embodiments of the invention, in the above description of the embodiments of the present application, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the subject of the present application requires more features than the features mentioned. In fact, the features of the embodiment are less than all the features of the single embodiment disclosed above.

[0085] In some embodiments, the numbers describing the number of components and attributes are used. It should be understood that such numbers used for the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers allow a change of ±20%. Accordingly, in some embodiments, the numerical parameters used in this application are approximate values, which can be changed according to the required characteristics of individual embodiments. In some embodiments, the numerical parameters should consider the specified significant digits and adopt the method of general digit retention. Although the numerical domains and parameters used to confirm the breadth of the range in some embodiments of the present application are approximate values, in a specific embodiment, the setting of such numerical values ​​is as accurate as possible within the feasible range.

Claims

1. A cardiac electrophysiological simulation system, characterized in that: include: An image acquisition module, used for acquiring a plurality of chest images, wherein the chest images include ventricle images; A three-dimensional mesh reconstruction module, used for obtaining a three-dimensional mesh of the ventricle by a finite element method according to the plurality of chest images; A ventricular conduction network construction module, used to generate a ventricular conduction network according to the ventricular three-dimensional grid to simulate the conduction of cardiac action potentials in the ventricles, wherein the ventricular conduction network includes a His bundle and a Purkinje fiber network, and the ventricular conduction network includes a plurality of first grid points, and the geometric position of each first grid point shares the point cloud of the ventricular three-dimensional grid; an electrophysiological parameter simulation module, configured to simulate the conduction process of the cardiac action potential in the ventricle according to the geometric positions and electrophysiological parameters of the first grid points, wherein the electrophysiological parameters include cell-level parameters and tissue-level parameters, the cell-level parameters include current parameters of ion channels, and the tissue-level parameters include conductivity, electrical signal propagation rate, and pacing stimulation parameters; and The dynamic simulation module is used to simulate the cardiac electrical signal according to the conduction process of the cardiac action potential in the ventricle to obtain a dynamic simulation result.

2. The cardiac electrophysiological simulation system according to claim 1, characterized in that: The ventricular conduction network construction module is configured to simulate and generate the ventricular conduction network using the following method: A fractal method is used to form a two-dimensional fractal network; Projecting the two-dimensional fractal network onto an endocardial surface to generate a three-dimensional fractal network, wherein the endocardial surface is a non-smooth surface; and The three-dimensional fractal network is used as the ventricular conduction network.

3. The cardiac electrophysiological simulation system according to claim 2, characterized in that: The method of forming a two-dimensional fractal network by using a fractal method comprises: Using a fractal method to create initial nodes and initial branches of the two-dimensional fractal network, wherein the initial branches have an initial growth direction; A plurality of new branches are created from the ends of the initial branches, and the next generation of new branches are iteratively created from the new branches to generate the two-dimensional fractal network, wherein during the iteration, the fractal motion parameters are set according to the geometric structure of the ventricle, and the fractal motion parameters include: branch length, branch angle and repulsion parameter.

4. The cardiac electrophysiological simulation system according to claim 3, characterized in that: Each branch includes n line segments and n+1 nodes, and the n+1 nodes mutually exclude each other to generate a curve, wherein the direction vector of each node is determined by the direction vector of the previous node and the distance gradient, and n is a natural number.

5. The cardiac electrophysiological simulation system according to claim 4, characterized in that: The step of projecting the two-dimensional fractal network onto the endocardial surface to generate a three-dimensional fractal network comprises: Obtaining a vertex normal of a current node, wherein the vertex normal is a weighted sum of all normals of adjacent fractal grids of the current node; projecting the current node onto a surface defined by a fractal mesh via the vertex normal; Determine whether the projection result of the current node is located within the fractal grid; If the projection result of the current node is not located in the fractal grid, the projection result is projected onto the surface through the surface normal of the grid unit.

6. The cardiac electrophysiological simulation system according to claim 5, characterized in that: The projecting the projection result onto the surface by the surface normal of the grid unit comprises: Calculate the direction vectors on all k-1 nodes before the current k-th node, where k is a positive integer; Projecting the kth node onto the surface according to the direction vector and the lengths of the branch line segments of all k-1 nodes; If the k-th node after projection is located in the fractal grid, or the length of the node line segment is greater than or equal to a preset range, then continue to project the next node, otherwise stop the iteration process.

7. The cardiac electrophysiological simulation system according to claim 6, characterized in that: The distance gradient is calculated using the following formula: : ， Among them, ϵ is a preset constant, e i represents a Cartesian basis vector, k represents the serial number of the current node on the ventricular conduction network, i represents a component x, y, z of the three-dimensional coordinate, g represents the distance gradient, p k represents the length of the line segment of the kth node on the 3D grid of the ventricle, dist cp Represents a function that returns the distance from node k to the nearest node in the network.

8. The cardiac electrophysiological simulation system according to claim 7, characterized in that: The direction vector d of the kth node is calculated using the following formula: k : ， Among them, w represents the repulsion parameter of the fractal structure, d k-1 represents the direction vector of the k-1th node, represents the distance gradient of the k-1th node; According to the direction vector d, the following formula is used: k And the branch line segment lengths of all k-1 nodes project the kth node onto the surface: 。 9. The cardiac electrophysiological simulation system according to claim 7, characterized in that: Initialize the direction vector using the following formula: ， Among them, d 0 Represents the initial direction vector of the initial node, n 0 represents the initial normal vector of the initial node, and α represents the single-step change angle of the branch angle.

10. The cardiac electrophysiological simulation system according to claim 3, characterized in that: The fractal method includes a kd-tree method.

11. The cardiac electrophysiological simulation system according to claim 1, characterized in that: The pacing stimulation parameters correspond to a pacing stimulation including a stimulation signal applied to the His bundle.

12. The cardiac electrophysiological simulation system according to claim 1, characterized in that: The three-dimensional grid reconstruction module is also used to mark ablation points on the multiple chest images and obtain a three-dimensional grid of the heart by a finite element method, wherein the ablation points include estimated ablation points to be ablated and / or actual ablation points where ablation has been performed; The cardiac electrophysiological simulation system further comprises: a fiber handedness calculation module, which is used to calculate the handedness of myocardial fibers according to the cardiac three-dimensional grid to obtain a direction vector of the handedness of myocardial fibers corresponding to each second grid point on the cardiac three-dimensional grid; The electrophysiological parameter simulation module is also used to simulate the cardiac action potential excitation process according to the geometric position of the second grid point, the fiber rotation direction corresponding to the second grid point and the electrophysiological parameters, wherein the electrophysiological parameters include cell level parameters and tissue level parameters, the cell level parameters include the current parameters of the ion channel, the tissue level parameters include the conductivity of different heart regions, pacing stimulation parameters and the propagation rate of the electrical signal set according to the direction vector of the myocardial fiber rotation direction.

13. The cardiac electrophysiological simulation system according to claim 12, characterized in that: The electrophysiological parameter simulation module obtains the current parameters of the ion channels corresponding to each first grid point on the ventricular conduction network based on a first ion channel model, and obtains the current parameters of the ion channels corresponding to each second grid point on the three-dimensional grid of the heart based on a second ion channel model, and the first ion channel model and the second ion channel model are different.

14. The cardiac electrophysiological simulation system according to claim 13, characterized in that: The first grid point and the second grid point share the point cloud of the ventricular three-dimensional grid, the end of the ventricular conduction network is connected to the end of the cardiac three-dimensional grid, and the electrical signal can be conducted from the ventricular conduction network to the cardiac three-dimensional grid.

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