Personalized virtual heart myocardial electrical conductivity anisotropy ratio setting method

Abstract

The invention discloses a method for setting the anisotropy ratio of electrical conductivity in a personalized heart model. The method specifically comprises the four steps of data preprocessing and personalized three-dimensional heart model reconstruction, model single cell and tissue electrical parameter setting, myocardial electrical conductivity anisotropy ratio selection and comparison simulation to obtain a proper electrical conductivity anisotropy ratio. The method comprises the following steps: fitting a conduction velocity into a corresponding electrical conductivity, then carrying out statistical analysis on electrical conductivity data by using a violin chart, selecting a section of interval corresponding to a 25th percentile and a 75th percentile as a reasonable interval, selecting multiple groups of instances with different electrical conductivity anisotropy ratios from the reasonable interval, and calculating the anisotropy ratio of the electrical conductivity according to the instances. The method is applied to personalized heart modeling of a patient, stimulation point simulation is carried out, and ventricular tachycardia of the patient is simulated. According to the method, the conduction velocity of the personalized virtual heart is closer to the real situation of the patient, and the accuracy of the personalized heart model is further improved.

Description

Technical Field

[0001] The invention relates to the field of cardiac electrophysiological simulation, and in particular to a method for setting a personalized virtual cardiac myocardial electrical conductivity anisotropy ratio. Background Art

[0002] Malignant ventricular arrhythmias are one of the main causes of sudden cardiac death. Changes in myocardial conduction velocity after myocardial tissue infarction provide a key basis for the occurrence of arrhythmias. The slowing of conduction velocity and changes in various anisotropies increase the probability of reentrant arrhythmias. The heterogeneity of myocardial electrical properties leads to different conduction velocities in tissues in different regions, which causes discontinuous propagation of excitement and ultimately leads to the formation of reentry. Therefore, changes in conduction velocity after myocardial tissue infarction play a key role in the generation and maintenance of reentrant arrhythmias. With the rapid development of computer technology, virtual hearts based on delayed enhancement cardiac magnetic resonance imaging (CMR-LGE) have become a powerful platform for non-invasive arrhythmia risk assessment in patients with cardiomyopathy, and the tissue electrical parameters set therein, such as electrical conductivity and anisotropy ratio, are important parameters for describing the conduction velocity of electrical signals in the ventricles.

[0003] Due to the lack of a unified standard for the conductivity anisotropy ratio, the conductivity used in different regions of the personalized virtual heart in most studies varies greatly, and its accuracy cannot be guaranteed. The conductivity anisotropy ratio has been shown to be very sensitive to cell geometry and gap junction properties, and is highly dependent on assumptions about cell radius and gap junction distribution, which may change under disease conditions and are subject to uncertainty. Summary of the invention

[0004] In view of this, the present invention provides a personalized virtual heart myocardial electrical conductivity anisotropy ratio setting method, which can improve the simulation accuracy and certainty of the electrical conductivity anisotropy ratio.

[0005] In order to solve the above technical problems, the present invention provides a personalized virtual heart myocardial electrical conductivity anisotropy ratio setting method, comprising the following steps:

[0006] S1, selection of anisotropy ratio of myocardial electrical conductivity;

[0007] S11. Obtain two sets of data. The first set of data is the myocardial conduction velocity measured in human experiments and animal experiments, including longitudinal conduction velocity and transverse conduction velocity; the second set of data is the anisotropy ratio of myocardial electrical conductivity measured in animal experiments;

[0008] S12. Calculate the equivalent harmonic conductivity and anisotropy ratio;

[0009] The experimental results of the second group of data in S11 were screened. If any of the four electrical conductivities was missing in each experimental result, it should be excluded. The four electrical conductivities are the longitudinal electrical conductivity σ in the intracellular region of the myocardial cell, il and the transverse conductivity σ it , the longitudinal electrical conductivity of the extracellular region of the myocardium el and the transverse conductivity σ et ; For other experimental results that meet the conditions, the corresponding harmonic conductivity, σ m is the harmonic mean conductivity equivalent to the two-domain model:

[0010] σ m =σ i σ e (σ i +σ e ) -1 ;

[0011] Among them, σ i is the electrical conductivity of the area within the myocardial cell, σ e is the electrical conductivity of the area outside the myocardial cells.

[0012] S13. Obtain electrical conductivity and its anisotropy ratio based on the conduction velocity iteration strategy; process the experimental results of the first set of data in S11:

[0013] Assuming that the plane wave surface propagates continuously along a given direction ζ, the conduction velocity CV is derived ζ and conductivity σ mζ The proportional relationship between them:

[0014]

[0015] Using an iterative scheme for conduction velocity tuning, based on the conduction velocity given by the first set of data in S11, the conductivity value is dynamically adjusted through iteration until the CV error is less than the error threshold, thereby converting the conduction velocity in the first set of data into the required harmonic mean conductivity anisotropy ratio data;

[0016] S14. Obtaining the reasonable range of the anisotropy ratio of electrical conductivity;

[0017] The electrical conductivity anisotropy ratio data of the first group of data and the second group of data processed by S12 and S13 respectively were classified according to their corresponding detected tissue types, the classified electrical conductivity anisotropy ratio data were plotted as violin plots, and the intervals corresponding to the 25th percentile and the 75th percentile were selected as the reasonable intervals of the electrical conductivity anisotropy ratio.

[0018] Optionally, the iterative scheme for conduction velocity tuning is specifically implemented in the following steps:

[0019] (1) Known target CV ζ , given the initial value m = 0,

[0020] (2) Execute the following loop:

[0021] a) Obtain the current CV based on one-dimensional cable simulation ζ [m];

[0022] b) Get the current impact coefficient

[0023] c) Update the current electrical conductivity: σ i [m+1]=σ i [m] factor, σ e [m+1]=σ e [m]·factor;

[0024] d) m = m + 1;

[0025] e) Until That is, the CV error is less than the error threshold and the loop is jumped out;

[0026] (3) Obtaining the target electrical conductivity σ i [m-1], σ e [m-1];

[0027] (4) Calculate σ based on the above harmonic mean conductivity calculation formula m .

[0028] CV ζ : conduction velocity of continuous propagation along a given direction ζ; Initially, the electrical conductivity of the corresponding intracellular region is selected; Initially, the electrical conductivity of the extracellular area of ​​the selected myocardium; CV ζ [m]: According to σ i [m], σ e [m] The corresponding conduction velocity obtained by the conductivity inside and outside the myocardial cell; factor: the current influence coefficient, that is, the difference between the current conduction velocity and the target conduction velocity, which is used to correct the value of the conductivity so that the conduction velocity obtained by the conductivity is close to the target conduction velocity; stop tol : The set error threshold; σ i [m-1]: electrical conductivity of the target myocardial cell region; σ e [m-1]: Electrical conductivity of the area outside the target myocardial cell.

[0029] Optionally, the present invention further comprises the following steps:

[0030] S2. Reconstruction of personalized three-dimensional heart model; by establishing a personalized ventricular infarction model based on clinical data to verify the accuracy of the electrical conductivity anisotropy ratio;

[0031] S21. Reconstruct a high-resolution three-dimensional biventricular cavity model; manually segment the ventricular boundaries on the CMR-LGE image and classify them into normal tissue and infarct tissue; then perform finite element meshing on the cardiac anatomical model to obtain a high-resolution finite element mesh biventricular model with an average side length of approximately 400 mm;

[0032] S22, constructing a single cell action potential model; using the ten Tusscher human ventricular myocyte model as the ventricular myocyte model;

[0033] S23. Establish multiple groups of electrical conductivity anisotropy ratio model instances; combine the reasonable interval obtained in S14 and the anisotropy ratio data in the experiment, and select multiple groups of different electrical conductivity anisotropy ratio instances so that they meet the reasonable interval range and match the distribution of specific experimental data.

[0034] S24. Stimulation scheme: In the induction of ventricular tachycardia, we adopted an induction method similar to that in clinical practice, and performed continuous electrical stimulation on the selected key points to simulate the stimulation activities of clinically induced ventricular tachycardia.

[0035] Optionally, the present invention further comprises the following steps:

[0036] S3. Comparison and verification of clinical results of experimental model; verify the matching degree of electrical conductivity anisotropy ratio parameters by comparing the reentry state recorded by clinical data with the simulation results of personalized ventricular model;

[0037] S31, detecting the matching degree of conduction velocity; in order to calculate the conduction velocity corresponding to the normal myocardium and the infarcted myocardium after applying different electrical conductivities, simulation is performed based on the wedge block model, by setting the tissue type of the wedge block, selecting multiple detection points, calculating the corresponding conduction velocity according to the activation time and the distance between the detection points, and averaging these results;

[0038] Based on the first set of data in S11, a corresponding violin plot was made to determine whether the conduction velocity of the model was consistent with the clinical mapping;

[0039] S32. Detect the matching degree of the reentry position and the induced ratio; simulate the occurrence of ventricular tachycardia according to the clinical stimulation scheme, and summarize the ratio of the number of induced points in each model to multiple stimulation points; divide the left ventricle into 17 areas, and record the area where the reentry position is located in each simulation; detect the degree of good matching between the reentry position and the induced ratio of the model after applying different conduction rates and the clinical mapping.

[0040] S33, detecting the matching degree of the reentry cycle length; in order to determine whether the reentry cycle length matches the clinical mapping well, the selection of the measurement point of the action potential length is a key step; and in order to ensure the accuracy of the reentry cycle length at the reentry position, when analyzing the simulation results, we need to select multiple measurement points and average their action potential lengths;

[0041] S34. Based on the detection results of S31, S32, and S33, select one group, multiple groups, or a range of conductivity anisotropy ratios that perform well for personalized heart modeling and simulation.

[0042] The invention method has the following advantages compared with the prior art: the invention proposes a method for setting the anisotropy ratio of electrical conductivity in a personalized heart model, which obtains a large amount of data on conduction velocity, electrical conductivity and other data of different tissue types measured clinically and in the laboratory, and then pre-processes the conduction velocity based on methods such as iterative fitting, fits the conduction velocity to the corresponding electrical conductivity, and then uses a violin plot to perform statistical analysis on these electrical conductivity data, selects a section corresponding to the 25th percentile and the 75th percentile as a reasonable interval, and selects multiple groups of different examples of anisotropy ratio of electrical conductivity, which are respectively applied to the personalized heart modeling of patients, and simulates the stimulation point to simulate the occurrence of ventricular tachycardia in patients. By comparing the matching degree between the simulation results and clinical records between different examples, the following aspects are included: 1. Detecting whether the conduction velocity of the model after applying different electrical conductivity is consistent with the clinical mapping; 2. Detecting whether the reentry position and induced ratio of the model after applying different electrical conductivity are matched with the clinical mapping; 3. Detecting whether the reentry cycle length (Cycle Length) of the model after applying different electrical conductivity is matched with the clinical mapping. And the conductivity anisotropy ratio with good performance is screened out.

[0043] Based on existing animal experiment literature and combined with clinical comparative simulation experiments, the present invention screens out the best electrical conductivity and anisotropy ratio in patient heart simulation. Specifically, it includes four steps: data preprocessing and personalized three-dimensional heart model reconstruction, model single cell and tissue electrical parameter setting, myocardial electrical conductivity anisotropy ratio selection, comparative simulation to obtain the appropriate electrical conductivity anisotropy ratio. This makes the conduction velocity of the personalized virtual heart closer to the actual situation of the patient, further improving the accuracy of the personalized heart model. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a flow chart of the method for setting the anisotropy ratio of myocardial electrical conductivity in a personalized heart model.

[0045] Figure 2 It is the distribution diagram of the anisotropy ratio of harmonic electrical conductivity in normal tissue and diseased tissue.

[0046] Figure 3 This is an example diagram of the selection of wedge blocks and conduction velocity detection points.

[0047] The red area in (a) is the location of facial stimulation, and three groups of conduction velocity detection points are listed in (b). DETAILED DESCRIPTION

[0048] The present invention is further described below by taking all currently acquired animal experimental data and human CMR-LGE images as examples and combining specific implementation steps. Figure 1 As shown, the method for setting the anisotropy ratio of myocardial electrical conductivity in the personalized heart model includes the following steps:

[0049] Step S1, selecting the anisotropy ratio of myocardial electrical conductivity.

[0050] S11. Summarize experimental data from animal experiments. Currently, there are two forms of experimental data sources: Form 1 is that the first data is the myocardial conduction velocity measured from human experiments and animal experiments, including longitudinal conduction velocity and transverse conduction velocity; Form 2 is that the second data is the anisotropy ratio of myocardial electrical conductivity measured in animal experiments.

[0051] S12. Calculate the equivalent harmonic conductivity.

[0052] The cardiac electrical excitation conduction model commonly used in our current computational simulation is the single-domain model, which simplifies the dual-domain model. It is known that in the single-domain equation, half of the harmonic mean between the intracellular and extracellular dual-domain conductivities is used as the single-domain conductivity, and the result is equivalent to the dual-domain equation.

[0053] Therefore, it is necessary to screen the experimental results of form 2 in S11. If any of the four electrical conductivities (the longitudinal electrical conductivity of the intracellular region of the myocardium, σ il and the transverse conductivity σ it , the longitudinal electrical conductivity of the extracellular region of the myocardium el and the transverse conductivity σ et ), need to be excluded. Otherwise, the corresponding harmonic conductivity cannot be obtained; the other experiments that meet the conditions need to calculate the corresponding harmonic conductivity and anisotropy ratio according to the formula. As shown in the following formula, σ m is the harmonic mean conductivity equivalent to the two-domain model and is calculated as follows:

[0054] σ m =σ i σ e (σ i +σ e ) -1 ;

[0055] Among them, σi is the electrical conductivity of the area within the myocardial cell, σ e is the electrical conductivity of the area outside the myocardial cells.

[0056] S13. Obtain electrical conductivity and its anisotropy ratio based on the conduction velocity iteration strategy. Although conduction velocity is a quantity that is easier, more robust and more accurately measured in vivo than tissue electrical conductivity. However, conduction velocity is not a parameter in a single-domain equation and cannot be parameterized, so the data in form 1 in S11 needs to be processed. By using an iterative scheme for conduction velocity tuning, based on the conduction velocity in form 1 in S11, the electrical conductivity value is dynamically adjusted through iteration until the conduction velocity error is less than the error threshold. The specific algorithm is as follows:

[0057] (1) Known target CV ζ , given the initial value m = 0,

[0058] (2) Execute the following loop:

[0059] a) Obtain the current CV based on one-dimensional cable simulation ζ [m]

[0060] b) Get the current impact coefficient

[0061] c) Update the current electrical conductivity: σ i [m+1]=σ i [m] factor, σ e [m+1]=σ e [m]·factor.

[0062] d)m=m+1.

[0063] e) Until That is, the CV error is less than the error threshold and the loop is exited.

[0064] (3) Obtaining the target electrical conductivity σ i [m-1], σ e [m-1];

[0065] (4) Calculate σ based on the above harmonic mean conductivity calculation formula m .

[0066] CV ζ : conduction velocity of continuous propagation along a given direction ζ; Initially, the electrical conductivity of the corresponding intracellular region is selected; Initially, the electrical conductivity of the extracellular area of ​​the selected myocardium; CV ζ [m]: According to σ i [m], σe [m] The corresponding conduction velocity obtained by the conductivity inside and outside the myocardial cell; factor: the current influence coefficient, that is, the difference between the current conduction velocity and the target conduction velocity, which is used to correct the value of the conductivity so that the conduction velocity obtained by the conductivity is close to the target conduction velocity; stop tol : The set error threshold; σ i [m-1]: electrical conductivity of the target myocardial cell region; σ e [m-1]: Electrical conductivity of the area outside the target myocardial cell.

[0067] According to this strategy, the conduction velocity in Form 1 is converted into the desired electrical conductivity anisotropy ratio data.

[0068] S14, the reasonable interval of the electrical conductivity anisotropy ratio is obtained. The electrical conductivity anisotropy ratio data of form 2 and form 1 processed by S12 and S13 respectively are classified according to the corresponding tissue types (healthy tissue and infarcted tissue) detected. The classified electrical conductivity anisotropy ratio data are plotted as violin plots. The intervals corresponding to the 25th percentile and the 75th percentile are selected as reasonable intervals, such as Figure 2 shown.

[0069] Among them, the 25th percentile of normal tissue was 4.01 and the 75th percentile was 8.20; the 25th percentile of infarcted tissue was 3.15 and the 75th percentile was 12.67.

[0070] Step S2: Reconstructing a personalized three-dimensional heart model.

[0071] S21. Reconstruct a high-resolution three-dimensional biventricular cavity model. The boundaries of the left and right ventricles' endocardium and epicardium were manually segmented on the CMR-LGE images, and the left ventricular myocardial tissue was segmented into normal tissue and infarcted tissue; then the cardiac anatomical model was meshed, and the average side length of the mesh target was about 400 mm. Therefore, the biventricular model consisted of 4 to 6 million nodes and 20 to 40 million tetrahedral units.

[0072] S22. Construct a single-cell action potential model. The most widely used human ventricular myocyte model was used as the normal ventricular myocyte model. The action potential remodeling of hemi-infarcted tissue is specifically manifested as follows: the characteristics of fast delayed rectifier potassium channels, delayed rectifier potassium channels, L-type calcium channels, and sodium channels have changed. Therefore, we change the corresponding current, that is, I Kr ,I Ks ,I CaL and I Na, the peak values ​​were reduced to 30%, 20%, 31% and 38% of the normal values ​​of the ten Tusscher ventricular myocyte model, respectively.

[0073] S23, establish multiple groups of electrical conductivity anisotropy ratio model examples. Select multiple groups of different electrical conductivity anisotropy ratio examples from the reasonable interval obtained in S14. The conductivity anisotropy ratios selected for normal tissues are 5.18, 6.51, 7.84, 8.28, and 9.17, respectively. The conductivity anisotropy ratios selected for diseased tissues are 2.56, 3.18, 3.79, 4.00, 4.41, 9.87, and 80.08, respectively. They are used as parameters for the electrical conductivity anisotropy ratios in normal tissues and diseased tissues in S22, respectively.

[0074] S24, Stimulation scheme: In terms of ventricular tachycardia induction, we use an induction method similar to clinical practice. According to the standards of the American Heart Association, 19 key points in the left and right ventricles of the heart are automatically selected, and then these points are continuously electrically stimulated. The application of this induction method can provide a simulation environment that is closer to clinical practice and helps to more accurately simulate the occurrence and characteristics of ventricular tachycardia.

[0075] Step 3: Comparative verification of clinical results of experimental models.

[0076] S31. Detect the matching degree of conduction velocity. In order to calculate the conduction velocity of normal myocardium and infarcted myocardium after applying different electrical conductivity, we simulated based on the wedge block model, such as Figure 3 By setting the tissue type of the wedge block, 20 detection points are selected and divided into 10 groups in pairs. The two points in the group need to be parallel to the x-axis, as shown in Figure 3 Then, the surface is stimulated in the x direction, as shown in (b). Figure 3 As shown in the red area in (a), the conduction velocity was calculated based on the activation time difference of the detection points in each group and the distance between the detection points, and the results were averaged. The long-axis conduction velocity of normal tissue was distributed between 39.4-41.5 cm / s, and the short-axis conduction velocity was distributed between 19.2-25.9 cm / s; the long-axis conduction velocity of infarcted tissue was distributed between 30.7-34.3 cm / s, and the short-axis conduction velocity was distributed between 10.2-23.9 cm / s, which matched the distribution of clinical mapping data of form 1 in S21.

[0077] S32. Detect the matching degree of reentry position and induced ratio. Simulate the occurrence of ventricular tachycardia according to the clinical stimulation scheme, and summarize the ratio of the number of induced points in each model to the 19 stimulation points; and divide the left ventricle into 17 areas according to the standards of the American Heart Association, and record the area where the reentry position is located in each simulation. Detect the degree to which the reentry position and induced ratio of the model after applying different conduction rates match the clinical mapping.

[0078] S33, detecting the matching degree of the return cycle length.

[0079] In order to determine whether the reentry cycle length (Cycle Length) matches the clinical mapping well, the selection of the measurement point of the action potential length is a key step; and to ensure the accuracy of the reentry cycle length at the reentry position, when analyzing the simulation results, we select multiple measurement points and average their action potential lengths.

[0080] S34. Based on the detection results of S31, S32, and S33, select one group, multiple groups, or a range of conductivity anisotropy ratios that perform well for use in personalized cardiac modeling and simulation.

Claims

1. A personalized virtual heart myocardial electrical conductivity anisotropy ratio setting method, characterized by: The following steps are involved: S1, selection of anisotropy ratio of myocardial electrical conductivity; S11. Obtain two sets of data. The first set of data is the myocardial conduction velocity measured in human experiments and animal experiments, including longitudinal conduction velocity and transverse conduction velocity; the second set of data is the anisotropy ratio of myocardial electrical conductivity measured in animal experiments; S12. Calculate the equivalent harmonic conductivity and anisotropy ratio; The experimental results of the second group of data in S11 were screened. If any of the four electrical conductivities was missing in each experimental result, it should be excluded. The four electrical conductivities are the longitudinal electrical conductivity σ in the intracellular region of the myocardial cell, il and the transverse conductivity σ it , the longitudinal electrical conductivity of the extracellular region of the myocardium el and the transverse conductivity σ et ; For other experimental results that meet the conditions, the corresponding harmonic conductivity, σ m is the harmonic mean conductivity equivalent to the two-domain model: s m =s i s e (s i +s e ) -1 ; Among them, σ i is the electrical conductivity of the area within the myocardial cell, σ e is the electrical conductivity of the area outside the myocardial cells. S13. Obtain electrical conductivity and its anisotropy ratio based on the conduction velocity iteration strategy; process the experimental results of the first set of data in S11: Assuming that the plane wave surface propagates continuously along a given direction ζ, the conduction velocity CV is derived ζ and conductivity σ mζ The proportional relationship between them: CV ζ ∝√σ mζ ; Using an iterative scheme for conduction velocity tuning, based on the conduction velocity given by the first set of data in S11, the conductivity value is dynamically adjusted through iteration until the CV error is less than the error threshold, thereby converting the conduction velocity in the first set of data into the required harmonic mean conductivity anisotropy ratio data; S14. Obtaining the reasonable range of the anisotropy ratio of electrical conductivity; The electrical conductivity anisotropy ratio data of the first group of data and the second group of data processed by S12 and S13 respectively were classified according to their corresponding detected tissue types, the classified electrical conductivity anisotropy ratio data were plotted as violin plots, and the intervals corresponding to the 25th percentile and the 75th percentile were selected as the reasonable intervals of the electrical conductivity anisotropy ratio.

2. The method for setting the personalized virtual cardiac myocardial electrical conductivity anisotropy ratio according to claim 1, characterized in that: The specific execution steps of the iterative scheme for conduction velocity tuning are as follows: (1) Known target CV ζ , given the initial value m = 0, (2) Execute the following loop: a) Obtain the current CV based on one-dimensional cable simulation ζ [m]; b) Get the current impact coefficient c) Update the current electrical conductivity: σ i [m+1]=σ i [m] factor, σ e [m+1]=σ e [m]·factor; d) m = m + 1; e) Until That is, the CV error is less than the error threshold and the loop is jumped out; (3) Obtaining the target electrical conductivity σ i [m-1], σ e [m-1]; (4) Based on the above harmonic mean conductivity calculation formula, σ is calculated. m ; CV ζ : conduction velocity of continuous propagation along a given direction ζ; Initially, the electrical conductivity of the corresponding intracellular region is selected; Initially, the electrical conductivity of the extracellular area of ​​the selected myocardium; CV ζ [m]: According to σ i [m], σ e [m] The corresponding conduction velocity obtained by the conductivity inside and outside the myocardial cell; factor: current influence coefficient, that is, the difference between the current conduction velocity and the target conduction velocity, which is used to correct the value of the conductivity so that the conduction velocity obtained by the conductivity is close to the target conduction velocity; stop tol : The set error threshold; σ i [m-1]: electrical conductivity of the target myocardial cell region; σ e [m-1]: Electrical conductivity of the area outside the target myocardial cell.

3. The method for setting the personalized virtual cardiac myocardial electrical conductivity anisotropy ratio according to claim 1, characterized in that: The following steps are also included: S2. Reconstruction of personalized three-dimensional heart model; by establishing a personalized ventricular infarction model based on clinical data to verify the accuracy of the electrical conductivity anisotropy ratio; S21. Reconstruct a high-resolution three-dimensional biventricular cavity model; manually segment the ventricular boundaries on the CMR-LGE image and classify them into normal tissue and infarct tissue; then perform finite element meshing on the cardiac anatomical model to obtain a high-resolution finite element mesh biventricular model with an average side length of approximately 400 mm; S22, constructing a single cell action potential model; using the ten Tusscher human ventricular myocyte model as the ventricular myocyte model; S23. Establish multiple groups of electrical conductivity anisotropy ratio model instances; combine the reasonable interval obtained in S14 and the anisotropy ratio data in the experiment, and select multiple groups of different electrical conductivity anisotropy ratio instances so that they meet the reasonable interval range and match the distribution of specific experimental data. S24. Stimulation scheme: In the induction of ventricular tachycardia, we adopted an induction method similar to that in clinical practice, and performed continuous electrical stimulation on the selected key points to simulate the stimulation activities of clinically induced ventricular tachycardia.

4. The method for setting the personalized virtual cardiac myocardial electrical conductivity anisotropy ratio according to claim 1, characterized in that: The following steps are also included: S3, comparative verification of clinical results of experimental models; The matching degree of the electrical conductivity anisotropy ratio parameter was verified by comparing the reentry state recorded by clinical data with the simulation results of the personalized ventricular model; S31, detecting the matching degree of conduction velocity; in order to calculate the conduction velocity corresponding to the normal myocardium and the infarcted myocardium after applying different electrical conductivities, simulation is performed based on the wedge block model, by setting the tissue type of the wedge block, selecting multiple detection points, calculating the corresponding conduction velocity according to the activation time and the distance between the detection points, and averaging these results; Based on the first set of data in S11, a corresponding violin plot was made to determine whether the conduction velocity of the model was consistent with the clinical mapping; S32, detecting the reentry position and the matching degree of the induced ratio; Simulate ventricular tachycardia according to clinical stimulation schemes and summarize the ratio of the number of inducing points in each model to multiple stimulation points; The left ventricle was divided into 17 regions, and the region where the reentry position was located in each simulation was recorded; The extent to which the locations and proportions of reentry in the model matched clinical mapping was examined using different conductivities. S33, detecting the matching degree of the reentry cycle length; in order to determine whether the reentry cycle length matches the clinical mapping well, the selection of the measurement point of the action potential length is a key step; and in order to ensure the accuracy of the reentry cycle length at the reentry position, when analyzing the simulation results, multiple measurement points are selected and their action potential lengths are averaged; S34. Based on the detection results of S31, S32, and S33, select one group, multiple groups, or a range of conductivity anisotropy ratios that perform well for personalized heart modeling and simulation.

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