CN119028528B - Simulation system for evaluating cardiac ablation plans - Google Patents
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Abstract
The application provides a simulation system for evaluating a cardiac ablation scheme, which comprises an image acquisition module, a three-dimensional grid reconstruction module, a fiber rotation direction calculation module, an electrophysiology parameter simulation module and a dynamic simulation module, wherein the image acquisition module is used for acquiring a plurality of thoracic images, the three-dimensional grid reconstruction module is used for marking ablation points of the plurality of thoracic images and acquiring a cardiac three-dimensional grid through a finite element method, the fiber rotation direction calculation module is used for calculating myocardial fiber rotation directions according to the cardiac three-dimensional grid and acquiring a direction vector of myocardial fiber rotation directions corresponding to each grid point on the cardiac three-dimensional grid, the electrophysiology parameter simulation module is used for simulating a cardiac action potential activation process according to electrophysiology parameters, geometric positions of the grid points and fiber rotation directions corresponding to the grid points, and the dynamic simulation module is used for simulating cardiac electrical signals according to the cardiac action potential activation process and obtaining a dynamic simulation result. The simulation result is more real through the anisotropy introduced by the fiber rotation direction.
Description
Technical Field
The application mainly relates to the field of biomedical engineering simulation, in particular to a simulation system for cardiac ablation scheme evaluation.
Background
Certain types of arrhythmias are caused by areas of local abnormalities in the cardiac electrical system, which can be commonly intervened by radio frequency ablation to eliminate the arrhythmia. In order to determine the ablation site, pacing stimulation is typically performed using an invasive electrocardiograph (ecg) instrument, which detects the electrophysiological signal and then determines the ablation site from the electrophysiological signal. At present, due to the limitations of technology and principles, uncertainty often exists in the effect of ablation, and arrhythmia has a small recurrence rate. For recurrent patients, the aforementioned invasive pacing and detection needs to be performed once again, which is undoubtedly painful for the patient. Currently, there are some technological paths of non-invasive electrophysiology, usually by collecting multi-lead electrocardiosignals on the trunk surface through a relatively large number of electrodes, and then reversely pushing epicardial action potential phase diagram distribution in the form of an electrocardiographic inverse problem through a conducting matrix, so as to evaluate focus and ablation schemes.
However, the related art of the electrocardiographic inverse problem faces difficulties in principle and accuracy. In principle, the electrocardiographic inverse problem relies on a boundary element method to calculate a conduction matrix between epicardial and torso-body surface geometric meshes to establish a relationship between potentials on the corresponding meshes. The calculation of the conduction matrix is sensitive to the accuracy of the geometric grid and is interfered by physiological parameters of other organs such as the chest and the lung of the patient, so that the obtained conduction matrix has limited accuracy. Furthermore, the equation solved by the inverse problem is a severely underdetermined equation, which makes the numerical solution severely unstable at the time of calculation. The accuracy and number of electrodes on the torso body surface as input parameters is not always the accuracy required to eliminate this instability for the under-determined equation.
Therefore, the accuracy that can be satisfied by the solution to the inverse problem is very limited. If the arrhythmia focus point is predicted in this way, the accuracy is not reliable, so the scheme of noninvasively evaluating the ablation point cannot accurately obtain the focus position.
Disclosure of Invention
Aiming at the technical problems, the application provides a simulation system capable of more accurately simulating the actual myocardial fiber electrophysiological activity.
The application provides a simulation system for evaluating a cardiac ablation scheme, which comprises an image acquisition module, a three-dimensional grid reconstruction module, a fiber rotation direction calculation module and an electrophysiological parameter simulation module, wherein the image acquisition module is used for acquiring a plurality of chest images, the chest images contain cardiac angiography images, the three-dimensional grid reconstruction module is used for marking ablation points of the chest images and obtaining a cardiac three-dimensional grid through a finite element method, the ablation points comprise estimated ablation points to be ablated and/or actual ablation points after ablation is carried out, the fiber rotation direction calculation module is used for calculating myocardial fiber rotation directions according to the cardiac three-dimensional grid, a direction vector of myocardial fiber rotation directions corresponding to each grid point on the cardiac three-dimensional grid is obtained, the electrophysiological parameter simulation module is used for simulating a cardiac action potential excitation process according to electrophysiological parameters, geometric positions of the grid points and fiber rotation directions corresponding to the grid points, the cell level parameters comprise current parameters of ion channels, the tissue level parameters comprise electrical conductivity of different cardiac areas, pacing stimulation parameters and electrical signal rotation direction vectors, and the simulation result is used for obtaining a dynamic action potential excitation process according to the simulation result.
In one embodiment of the application, the thoracic image comprises an LGE-MRI enhanced image.
In an embodiment of the present application, the three-dimensional mesh reconstruction module is further configured to segment the plurality of thoracic images, and a boundary of the segmentation includes a left ventricular endocardium, a right ventricular endocardium, and an epicardium.
In one embodiment of the application, the fiber rotation direction calculation module calculates myocardial fiber rotation directions according to the heart three-dimensional grid based on an LD-RB algorithm.
In an embodiment of the application, the electrophysiology parameter simulation module obtains a current parameter of an ion channel corresponding to each grid point on the three-dimensional grid of the heart based on an ion channel model.
In an embodiment of the present application, the electrophysiology parameter simulation module determines the electrical conductivity of different regions in the three-dimensional grid of the heart according to the segmented thoracic image, wherein the electrical conductivity corresponding to the ablation points is different from the electrical conductivity corresponding to normal cardiomyocytes.
In an embodiment of the present application, the electrical conductivity corresponding to the ablation point is 0.
In an embodiment of the present application, the pacing stimulation parameters include parameters corresponding to a pre-procedural stimulation protocol configured to include:
Step 1, selecting the position of a stimulation point;
Step 2, using S1S2 stimulation, wherein a stimulation sequence comprises 6 times of continuous stimulation at a stimulation point by pacing stimulation S1 with a period length of T1, applying an S2 stimulation after the last time of S1 stimulation, wherein the period length of the S2 stimulation is T2, and if no abnormality is induced after the S2 stimulation, decrementing the period length T2 of the S2 stimulation according to a preset step length, and circularly applying the S2 stimulation until the abnormality is induced;
step 3, if S2 stimulation cannot induce abnormality, S3 stimulation is applied, the period length T3 of the S2 stimulation is decreased according to a preset step length, and S3 stimulation is circularly applied until abnormality is induced;
step 4, if the S3 stimulation cannot induce the abnormality, applying the S4 stimulation, and decreasing the period length T4 of the S4 stimulation according to a preset step length, and circularly applying the S4 stimulation until the abnormality is induced;
and 5, if the S4 stimulation cannot induce abnormality, the stimulation point is considered to be incapable of inducing the required arrhythmia.
In an embodiment of the present application, the dynamic simulation module simulates the cardiac electrical signal based on a Reaction-Diffusion process, where the simulation process includes:
step 10, taking transmembrane points and reset voltage on a time-space evolution scale as contraction variables u and v and nonlinear reaction functions f and g, and satisfying the equation:
Wherein D 1 and D 2 are coefficients corresponding to the contraction variables u, v, Is a laplace operator and,
Step 20 of discretizing the equation in step 10 in the time dimension, letting t=1, 2..and T, and recording the grid point sequence number i=1, 2..and N in the three-dimensional grid of the heart, to obtain the following equation:
step 30, writing the equation in the step 20 into the following matrix:
Wherein,
And 40, solving the matrix in the step 30 by adopting an optimization method to obtain U t and V t.
In one embodiment of the present application, the Fitzhugh-Nagumo model is used in step 10 such that:
f(u,v)=C1u(1-u)(u-a)-C2uv
g(u,v)=b(u-dv)
Wherein, C 1 and C 2 are parameters related to the curve shape of the function f, 1/b is the average time constant of slow current passing in the ion channel, a is a parameter related to the rest voltage, and d is the ratio of the membrane permeation current and the slow local recovery current in the ion channel.
In one embodiment of the application, the system further comprises an evaluation module for evaluating the cardiac ablation scheme according to the dynamic simulation result, wherein the evaluation result comprises whether to change the ablation point.
The simulation system constructs a heart three-dimensional grid through the image, calculates the myocardial fiber rotation direction, obtains the heart action potential exciting process with fiber rotation direction anisotropy, introduces the anisotropic heart potential diffusion process into the dynamic simulation module to perform simulation calculation, simulates the actual myocardial fiber electrophysiological property, greatly improves the numerical precision, simultaneously avoids the instability of the result obtained by the boundary element method, avoids the defect of the electrocardiographic inverse problem, and can more finely simulate the actual case characteristics.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the accompanying drawings:
FIG. 1 is a block diagram of a simulation system for cardiac ablation protocol evaluation of the present application;
FIG. 2 is an exemplary flow chart for cardiac ablation protocol evaluation employing a simulation system of an embodiment of the present application.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some examples or embodiments of the present application, and it is apparent to those of ordinary skill in the art that the present application may be applied to other similar situations according to the drawings without inventive effort. Unless otherwise apparent from the context of the language or otherwise specified, like reference numerals in the figures refer to like structures or operations.
As used herein, the terms "a," "an," "the," and/or "the" are not specific to the singular, but may include the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.
The relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present application unless it is specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description. Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any specific values should be construed as merely illustrative, and not a limitation. Thus, other examples of the exemplary embodiments may have different values. It should be noted that like reference numerals and letters refer to like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
In addition, the terms "first", "second", etc. are used to define the components, and are only for convenience of distinguishing the corresponding components, and the terms have no special meaning unless otherwise stated, and therefore should not be construed as limiting the scope of the present application. Furthermore, although terms used in the present application are selected from publicly known and commonly used terms, some terms mentioned in the present specification may be selected by the applicant at his or her discretion, the detailed meanings of which are described in relevant parts of the description herein. Furthermore, it is required that the present application is understood, not simply by the actual terms used but by the meaning of each term lying within.
The simulation system for cardiac ablation scheme evaluation can be used for preoperative evaluation of ablation operation, guides formulation of ablation scheme, and can evaluate actual rhythm effect of the heart after the ablation operation is implemented. The simulation system of the present application can be used for simulating arrhythmia diseases such as ventricular fibrillation, atrial fibrillation, tachycardia, etc., but is not limited thereto.
FIG. 1 is a block diagram of a simulation system for cardiac ablation protocol evaluation of the present application. Referring to fig. 1, the simulation system 100 includes an image acquisition module 110, a three-dimensional mesh reconstruction module 120, a fiber rotation direction calculation module 130, an electrophysiology parameter simulation module 140, and a dynamic simulation module 150. The image acquisition module 110 is configured to acquire a plurality of chest images, wherein the chest images include cardiac angiography images, the three-dimensional grid reconstruction module 120 is configured to label ablation points of the plurality of chest images, obtain a cardiac three-dimensional grid by a finite element method, the ablation points include estimated ablation points to be ablated and/or actual ablation points to be ablated, the fiber direction calculation module 130 is configured to calculate myocardial fiber directions according to the cardiac three-dimensional grid, obtain a direction vector of myocardial fiber directions corresponding to each grid point on the cardiac three-dimensional grid, and the electrophysiology parameter simulation module 140 is configured to simulate a cardiac action potential activation process according to electrophysiology parameters, geometric positions of the grid points, and fiber directions corresponding to the grid points, wherein the electrophysiology parameters include cell-level parameters and tissue-level parameters, the cell-level parameters include current parameters of ion channels, the tissue-level parameters include electrical conductivities of different heart regions, pacing stimulation parameters, and propagation rates of electrical signals set according to the direction vectors of myocardial fiber directions, and the dynamic simulation module 150 is configured to simulate cardiac electrical signals according to the cardiac action potential activation process, so as to obtain dynamic simulation results.
The following expansion describes the various modules in the simulation system 100.
The thoracic images that can be acquired by the image acquisition module 110 are images including cardiac angiography images. Preferably, normal and abnormal regions can be clearly distinguished from the thoracic image. The normal region refers to a region including normal cells. The abnormal region is, for example, a region including an abnormal condition such as a cell infarction, scar tissue, or fibrosis injury. The plurality of chest images means 2 or more images. It will be appreciated that in order to obtain a three-dimensional grid of the heart, a three-dimensional model is built with as many images as possible. In order to achieve high-precision simulation results, the obtained original image should have high resolution and high definition.
The application is not limited as to how the chest images are obtained.
In some embodiments, the image acquisition module 110 is embodied as an MRI device, more particularly, an LGE-MRI device, for obtaining an LGE-MRI enhanced magnetic resonance image.
Delayed gadolinium enhanced nuclear magnetic resonance LGE (Late Gadolinium Enhancement) -MRI uses gadolinium-binding macromolecules as contrast agents, which can more clearly distinguish infarcted areas from normal cells due to the different amounts of aggregates in different areas of the heart after contrast agents are applied. After the contrast agent is used for 10-30 minutes for a patient, the intrinsic signals of the contrast agent are counteracted by applying inversion pulses to the cardiac muscle after a certain time, and meanwhile, the signals of infarcted tissues are brighter, depending on the reduction of the T1 relaxation time and different area distribution modes of the gadolinium-based contrast agent in the extracellular space of the cardiac muscle. For myocardial infarction, the extracellular space is increased due to collagen deposition caused by myocardial infarction, so that the content of gadolinium contrast agent is obviously different, and the areas of delayed gadolinium enhancement signals of MRI after weighted imaging reveal damaged areas such as cellular infarction, scar tissue, fibrosis and the like. LGE-MRI can assess myocardial scarring and regional myocardial fibrosis. Clinically, LGE-MRI is used to detect and characterize a variety of myocardial diseases, including myocardial infarction, myocarditis, cardiac sarcoidosis, and cardiac amyloidosis.
The three-dimensional mesh reconstruction module 120 obtains the desired plurality of thoracic images from the image acquisition module 110. In some embodiments, segmentation of the plurality of chest axial enhancement MRI slice images into the left ventricular endocardium, the right ventricular endocardium, and the epicardium corresponds to labeling boundaries for the left ventricular endocardium, the right ventricular endocardium, and the epicardium on each chest image. For other embodiments, the outer surfaces of the left atrium, right atrium, and atrium may be labeled using the same procedure, for example, for atrial regions. Meanwhile, abnormal areas on the MRI slice images can be marked through finite element software. The abnormal region includes ablation points including pre-estimated ablation points at which ablation is to be performed and/or actual ablation points at which ablation has been performed.
For pre-operative evaluation, the ablation points are estimated ablation points at which ablation is to be performed.
For post-operative evaluation, the ablation points are the actual ablation points where ablation has been performed.
In some cases, assuming that an abnormality in the electrophysiological signal of the patient having undergone the ablation procedure may require a secondary ablation procedure, the ablation points may include both the predicted ablation point at which the secondary ablation procedure is to be performed and the actual ablation point at which the ablation has been performed. Therefore, the actual ablation point which is ablated and the estimated ablation point which is to be ablated can be considered simultaneously in simulation, and the simulation method is closer to the actual situation.
The present application is not limited to how the three-dimensional mesh reconstruction module 120 performs the annotation of the ablation points. The three-dimensional mesh reconstruction module 120 may provide algorithms for labeling, or a graphical user interface may be provided for manual labeling.
It should be noted that the three-dimensional mesh reconstruction module 120 obtains a three-dimensional mesh of the heart by a finite element method, which corresponds to the whole heart and includes a plurality of mesh points. The application does not limit the grid form, and can be triangular grids, tetrahedral grids, hexahedral grids and the like. The finite element method used is a common method in the art and will not be described here.
The myocardial fiber rotation direction has close relation with the propagation of electrocardiosignals. The fiber rotation direction calculating module 130 is configured to calculate a myocardial fiber rotation direction corresponding to each grid point based on the reconstructed heart three-dimensional grid, and take a direction vector of the myocardial fiber rotation direction as a parameter of the grid point.
In one embodiment, the fiber rotation direction calculation module 130 calculates myocardial fiber rotation directions from a three-dimensional grid of the heart based on the LD-RB algorithm. Specifically, a Laplace-Dirichlet algorithm, namely an LD-RB (Laplace-DIRICHLET RULED-based) algorithm, is based on human myocardial fiber rotation direction data obtained by heart physiological basic research, a statistical myocardial fiber distribution rule is obtained, and parameters of the distribution rule are determined by a heart three-dimensional grid, so that fiber rotation directions meeting relevant rules are obtained. This calculation does not require acquisition of patient-specific physiological measurement data.
The LD-RB algorithm adopted in the application follows the following fiber rotation direction distribution rule:
1. The longitudinal fiber direction on the ventricular wall is parallel to the inner and outer membrane surfaces.
2. Alpha is the helix angle seen from the base towards the apex of the heart in a counterclockwise circumferential direction with respect to the heart, and there will be a continuous change in the ventricular transmural longitudinal fiber direction from endocardium (-alpha) to epicardium (+alpha). In one embodiment, α is 60 °.
3. The transverse and longitudinal fiber directions are perpendicular to each other, characterized by an angle β, where β is defined as the angle of the ventricle relative to the outer transmural axis.
4. The transverse direction and the longitudinal direction of the fiber are perpendicular to the normal line of the sheet.
5. The fibrous handedness of the ventricular septum is continuous with the ventricular wall.
Given the above 5 rules, the LDRB algorithm defined above for ventricular muscle fiber rotation requires four functions as inputs representing the required alpha and beta angles within the ventricular wall (w) and the ventricular septum(s), respectively. Where α and β are in degrees, h represents the transmural depth, and the size is between 0 and 1, 0 represents the inner surface of the ventricle, and 1 represents the outer surface of the ventricle. Epi stands for epicardium and Endo stands for endocardium. The four functions are specifically as follows:
αs(h)＝αendo(1-h)-αendo*h (1)
αw(h)＝αendo(1-h)+αepi*h (2)
βs(h)＝βendo(1-h)-βendo*h (3)
βw(h)＝βendo(1-h)+βepi*h (4)
As boundary conditions, each angle requires setting the values α w(0)＝αs(0)＝-αs (1) modulo 180℃on the inner and outer film, and β w(0)＝βs(0)＝-βs (1) modulo 180 ℃. In the four functions (1) - (4), the parameters except alpha and beta are known, and can be obtained from a heart three-dimensional grid model. Alpha and beta can thus be solved as the rotation angle of the corresponding myocardial fiber direction at each three-dimensional grid point.
The heart three-dimensional grid is positioned under global coordinates, wherein epicardium, left and right endocardium, ventricular basal plane and apex position are marked, and the direction vector of myocardial fiber rotation direction on each grid point can be obtained according to local coordinates through coordinate transformation.
The electrophysiology parameter simulation module 140 can obtain the desired electrophysiology parameters, the geometric positions of the grid points, and the fiber handedness corresponding to the grid points. For example, the electrophysiology parameter simulation module 140, the three-dimensional grid reconstruction module 120 and the fiber rotation direction calculation module 130 are all in communication connection, so that the geometric positions of grid points can be directly obtained from the three-dimensional grid reconstruction module 120, and the fiber rotation directions corresponding to the grid points can be obtained from the fiber rotation direction calculation module 130. The electrophysiological parameters can be built into the electrophysiological parameter simulation module 140 or set by the user by means of a graphical user interface.
In the cellular dimension, the electrophysiological parameters include the current parameters of the ion channel. Specifically, in one embodiment, the electrophysiology parameter simulation module 140 obtains the current parameters of the ion channels corresponding to each grid point on the three-dimensional grid of the heart based on the ion channel model. More specifically, in one embodiment, the ion channel model is a TP06 model. The transmembrane domain of the ion channel forms an aqueous channel through which ions pass smoothly, which allows only specific ions to pass, and controls the transmembrane flow of specific ions by opening and closing a "gate". Many different types of ion channels are commonly found on the myocardial cell membrane, with sodium (na+), potassium (k+) and calcium (ca2+) channels being the predominant ion channel types. The application is not limited to the type of ion channel. The ion current satisfies the basic ohm's law, I x＝Gxp(Vm-Ex), where I x represents the ion current of ion x, G x represents the maximum conductance of ion x, V m represents the transmembrane potential, E x represents the equilibrium potential of ion x, and p represents the open probability coefficient of ion channel. The ion channels are voltage controlled, i.e. the opening and closing of the ion channels is influenced by the transmembrane potential across the membrane.
In the tissue dimension, the electrophysiological parameters include the electrical conductivity of the different cardiac regions. The conductivity of cardiomyocytes in the normal region was different from that in the abnormal region. In one embodiment, the electrical conductivity of different regions in the three-dimensional grid of the heart may be determined from the segmented thoracic image, wherein the electrical conductivity corresponding to ablation points is different from the electrical conductivity corresponding to normal cardiomyocytes. As previously described, the LGE-MRI image clearly distinguishes infarct areas from normal cells. The infarcted area can be identified by the images in turn. Fibrotic scars in the infarcted area are mainly composed of extracellular matrix composed of collagen fibers, are inactive to electrophysiological properties and are therefore generally regarded as insulators, i.e. have a conductivity of approximately 0. In order to simplify the calculation process, the conductivity at the ablation point is set to 0. Accordingly, the electrical conductivity of normal cells may also be set to an equal value, for example, an average value of the actual electrical conductivities.
In the border region of the fibrotic stromal scar, cells remain active, but the action potential of the border region cardiomyocytes is distinguishable from the action potential response of normal cardiomyocytes, the rate and height of potential rise is reduced upon depolarization, and APD (Action Potential Duration ) time is prolonged. The regional point location caused by ablation can be regarded as an insulating region as well, so that the setting of the electrophysiological information parameters is also applicable to the scar or the ablation result.
In the tissue dimension, the electrophysiological parameters further include the propagation rate of the electrical signal set according to the direction vector of the myocardial fiber direction calculated by the fiber direction calculation module 130. In some embodiments, the propagation rate is also set with an average value. For different grid points, due to the anisotropic characteristic of fiber rotation directions, the propagation speeds corresponding to the different grid points are the same but the directions are different.
In the tissue dimension, the electrophysiological parameters also include pacing stimulation parameters. In particular, the pacing stimulus parameters may be set according to the clinical requirements of the patient. The pacing stimulation parameters vary according to the stimulation protocol. The programmed action potential stimulation scheme can be considered to try a plurality of designs, and twin and resculpting are carried out on the illness state of a patient in simulation, so that for the purpose of individuation for the patient, several different types of designs can be applied:
1. And (3) step-by-step incremental stimulation, namely pacing at a frequency which is 10-20 times/min faster than the basic heart rate of the tested person, and pacing for 30-60 s each time. The frequency is increased by 10-20 times per minute at intervals of 1-2 minutes, and the next cycle is carried out until an effective refractory period or the longest sinus node recovery time appears at a certain part of the heart.
2. Continuous incremental stimulation, pacing at a lower frequency, followed by a gradual increase in pacing frequency, maintaining 1:1 pacing capture until the effective refractory period is reached at a site in the heart. This stimulation reduces the effects of overspeed inhibition and is commonly used in refractory period assays.
3. Short-matrix rapid stimulation, namely rapid pacing for 10-20 times at a rate 30 times/min faster than the heart rate of the examined person, is used for stopping tachyarrhythmia.
4. Serial stimulation consists of several groups of short, rapid stimulation pulses.
After considering the different types of design factors, a pre-procedural stimulation scheme can be used based on physician consensus to attempt to induce a corresponding condition during simulation in an effort to achieve patient personalization. The pre-procedural stimulation is an isolated single or multiple premature (extra-procedural) stimulation in either a self-rhythm or basal pacing rhythm.
The pre-procedural stimulation protocol employed by the present application is configured to include the steps of:
Step 1, selecting the position of a stimulation point;
Step 2, using S1S2 stimulation, wherein the stimulation sequence comprises 6 times of continuous stimulation at a stimulation point by pacing stimulation S1 with a period length of T1, applying an S2 stimulation after the last time of S1 stimulation, wherein the period length of the S2 stimulation is T2, and if no abnormality is induced after the S2 stimulation, decrementing the period length T2 of the S2 stimulation according to a preset step length, and circularly applying the S2 stimulation until the abnormality is induced, wherein in some cases, T1=600 ms, the initial value of T2 is 250ms, and the decrementing step length is 10ms.
And 3, if the S2 stimulation cannot induce the abnormality, applying the S3 stimulation, and decreasing the period length T3 of the S2 stimulation according to a preset step length, and circularly applying the S3 stimulation until the abnormality is induced.
The reason why abnormality cannot be induced may be because the myocardial tissue at the stimulation point is still in refractory period. In some cases, a threshold is set for T2 of S2, and when the threshold is reached and no abnormality can be induced, the S2 stimulus is stopped and the S3 stimulus is applied instead. For example, when decrementing to T2<150ms, the S2 stimulus is stopped.
Step 4, if the S3 stimulation cannot induce the abnormality, applying the S4 stimulation, and decreasing the period length T4 of the S4 stimulation according to a preset step length, and circularly applying the S4 stimulation until the abnormality is induced;
And 5, if the S4 stimulation cannot induce abnormality, the stimulation point is considered to be incapable of inducing the required arrhythmia. In this case, a new round of stimulation may be performed after the stimulation points are replaced.
The application does not limit the position of the stimulation point, the stimulation intensity and the like, and can be determined by doctors according to the standard.
Based on the foregoing, the electrophysiology parameter simulation module 140 can simulate and program the cardiac action potential activation process. Based on this, the dynamic simulation module 150 can simulate the cardiac electrical signal according to the cardiac action potential activation process, so as to obtain a simulation result. The dynamic simulation module 150 may visually present the simulation results.
Specifically, in one embodiment, the dynamic simulation module 150 simulates the cardiac electrical signal based on a Reaction-Diffusion process, where the simulation process includes:
Step 10, taking transmembrane points and reset voltage on a time-space evolution scale as contraction variables u and v and nonlinear reaction functions f and g, and satisfying equations (5) and (6):
Wherein D 1 and D 2 are coefficients corresponding to the contraction variables u, v, Is a laplace operator and, More specifically, D 1 and D 2 are used to characterize the conductivity of the corresponding diffusion process in the permeant and slow local recovery currents in the ion channel model.
Note that cardiac electrical activity in a single cell involves coordinated transport of large numbers of ions through various biological pathways. The electrical waves also propagate from the cells to the whole heart, combining excitation with contraction and blood drainage. Some simplified assumptions and rules, such as cellular automaton models, are limited in their ability to simulate cardiac electrical activity, and in particular, in their ability to simulate at the full cardiac level. The reactive Diffusion (Reaction-Diffusion) model describes the spatial and temporal distribution of dynamic variables, which includes two processes, (1) a reactive (Reaction) process in which dynamic variables interact to transform, and (2) a diffuse (Diffusion) process in which dynamic variables diffuse in space. The potential propagation process determined by the reaction diffusion model is embodied in a contour map boundary which is continuously diffused in time-space evolutionThus, the reactive diffusion model can more realistically simulate the electrical activity of the whole heart. But the reactive diffusion model is more difficult to implement on complex geometries and is computationally expensive. The application has the advantages that the anisotropism introduced by the fiber rotation direction does not increase the complexity of a reaction diffusion model, and the calculation result can be more real.
Step 20: discretizing equations (5) and (6) in step 10 in the time dimension, let t=1, 2,.. and recording the grid point number i=1, 2 in the three-dimensional grid of the heart, N, resulting in the following equation:
Step 30, writing the equation in step 20 into the following matrix:
Wherein, Similarly, the matrix form of B 1、B2, F, G may be determined. Wherein, B 1、B2 is a corresponding coefficient matrix whose specific parameters need to be determined by the finite element form of the Laplacian operator on the corresponding grid. For a triangular mesh, the Laplacian operator acts on a variable u, Wherein delta isIn short, M is called a quality matrix (Mass matrix) and L is a Laplacian matrix.
Wherein θ ij andIn the two triangles of the line segment, two inner angles of the line are connected relatively to ij. The quality matrix M is a diagonal matrix related to the triangular area of the finite element where each grid point is locatedWherein the method comprises the steps ofThe triangle area is obtained by cross multiplication of the mapping coordinates, and after fiber rotation direction is calculated, the fiber rotation direction can be used as a local coordinate basis vector for adding anisotropy of electrocardiosignal propagation, so that the local coordinates are obtained by multiplying the original mapping coordinates by a degree gauge. Metric matrixWherein the basis vectorIs the longitudinal direction along the fiber direction,Is transverse to the direction of the fibers,Which is the normal to the plane formed by the direction vectors in the two fiber directions. Thus, the vector represented by the coordinates is mappedWill be expressed in local coordinates asThe coefficients in equation (9) can be determined at this time and satisfy the form of ax=b, and thus can be solved.
And 40, solving the matrix in the step 30 by adopting an optimization method to obtain U t and V t.
The solution can be performed by adopting an optimization method common in the field, and the application does not limit the specific optimization method.
In one embodiment, to simulate a dynamic process over time, a nonlinear reactive diffusion model is employed. Specifically, in step 10, using the Fitzhugh-Nagumo model, the function f, g is changed (giving the function f, g a specific form), to obtain:
f(u,v)=C1u(1-u)(u-a)-C2uv (10)
g(u,v)=b(u-dv) (11)
Equation (10) and equation (11) correspond to functions f, g, respectively. Wherein, C 1 and C 2 are parameters related to the curve shape of the function f, 1/b is an average time constant of slow current passing in the ion channel, a is a parameter related to resting voltage, d is a ratio of the magnitudes of the membrane permeation current and the slow local recovery current in the ion channel, a, b, C 1,C2 and d are all related to the specific ion channel model, and the actual value thereof needs to be determined by the action potential curve shape of the model. The diffusion equation of the variables u, v shown in equations (5) and (6) according to the functions f, g obtained in the above equation (10) and equation (11) satisfies:
In an embodiment using a TP06 ion channel model, the correlation coefficient may be set as D 1＝1,D2＝0,a＝0.13,b＝0.013,C1＝0.26,C2 =0.1, d=1.
The fiber rotation direction will determine the Laplace operatorThe numerical solution at each step of discretization, in turn, represents the anisotropy of the electrical signal propagating along the fiber spin direction at each step of the simulation. In general diffusion equations, anisotropy is brought about by the conductivity D1 as a tensor matrix. The application resorts the anisotropy to the Laplace operator instead of the conductivity tensor, and the fiber rotation direction determines which direction the nearest neighbor of each space grid point is in during the space discretization, and changes the degree gauge of the local coordinates so as to change the anisotropy of the Laplace operator in the numerical calculation. The anisotropic method is introduced in this way, and the calculation difficulty of the reaction diffusion equations (5) and (6) is not increased. Further, considering the anisotropy of the speed of the electric signal in different directions, the anisotropy brought by the fiber rotation direction also represents the propagation speed of the electric signal between each pair of nearest neighbor points. Therefore, the simulation result obtained by the simulation system provided by the application is easier to approach the propagation process of the actual electrophysiological signal, the authenticity of the simulation result is improved, and the simulation system can be more effectively applied to judgment of electrophysiology in clinic.
As shown in FIG. 1, in some embodiments, the simulation system 100 of the present application may also include an evaluation module 160. The evaluation module 160 is configured to evaluate the cardiac ablation scheme according to the dynamic simulation result, where the evaluation result includes whether to change the ablation point. Specifically, for a patient planning to perform ablation, the simulation system 100 may obtain a thoracic image of the patient, obtain a dynamic simulation result for the patient, and the evaluation module 160 may compare the dynamic simulation result with a normal cardiac electrophysiology process, and evaluate the actual influence of the lesion point or the estimated ablation point of the ablation scheme, so as to assist a doctor in determining whether the ablation point needs to be changed. If the ablation points need to be changed, the evaluation module 160 transmits the evaluation result to the three-dimensional grid reconstruction module 120, the three-dimensional grid reconstruction module 120 needs to remark the ablation points, and the fiber rotation direction calculation module 130, the electrophysiology parameter simulation module 140 and the dynamic simulation module 150 simulate the changed ablation points in sequence to obtain a new simulation result, and then the new simulation result is evaluated.
FIG. 2 is an exemplary flow chart for cardiac ablation protocol evaluation employing a simulation system of an embodiment of the present application. As shown in fig. 2, the process includes the steps of:
and S210, obtaining an estimated ablation point.
And step 220, obtaining an actual ablation point.
It should be noted that, step S210 and step S220 are performed according to actual needs. If the patient to be evaluated is about to perform an ablation operation, the estimated ablation points in the ablation scheme are obtained, and the ablation scheme is evaluated. If the patient to be evaluated has already undergone an ablation procedure, the actual ablation point is obtained and the ablation scheme that has already been performed is evaluated. For a patient needing secondary ablation, the estimated ablation point and the actual ablation point can be obtained simultaneously.
Step S230, performing simulation by using the simulation system 100 described above.
And step 240, evaluating according to the simulation result. For the estimation scheme estimation, if the estimation result is that the ablation point needs to be modified, the estimation scheme is modified and then simulated.
In step S250, if the simulation result indicates that the ablation plan is feasible, a personalized ablation plan for the patient may be obtained.
Fig. 2 is only one application manner of the simulation system 100 of the present application, and is not intended to limit the specific application scenario of the simulation system 100.
According to the simulation system 100, a heart three-dimensional grid is constructed through images, the myocardial fiber rotation direction is calculated, and the heart action potential exciting process with fiber rotation direction anisotropy is obtained, so that the anisotropic heart potential diffusion process is introduced into the RD diffusion model to perform simulation calculation, the actual myocardial fiber electrophysiological property is simulated, the numerical precision is greatly improved, meanwhile, the instability of a result obtained by a boundary element method is avoided, the defect of the electrocardiographic inverse problem is avoided, and the actual case characteristics can be simulated more finely. In addition, in the RD diffusion model, known physiological parameters can be conveniently applied, related parameters can be flexibly regulated in simulation calculation, and the evolution process of the disease of the target patient can be simulated more truly. The application applies the anisotropy of the fiber rotation direction to the relevant parameters of the diffusion model, improves the reality degree of simulation, ensures that the simulation result is not only qualitatively displayed, but also has the precision of digital twin quantitative research on diseases.
While the basic concepts have been described above, it will be apparent to those skilled in the art that the foregoing application disclosure is by way of example only and is not intended to be limiting. Although not explicitly described herein, various modifications, improvements and adaptations of the application may occur to one skilled in the art. Such modifications, improvements, and modifications are intended to be suggested within the present disclosure, and therefore, such modifications, improvements, and adaptations are intended to be within the spirit and scope of the exemplary embodiments of the present disclosure.
Meanwhile, the present application uses specific words to describe embodiments of the present application. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic is associated with at least one embodiment of the application. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the application may be combined as suitable.
Some aspects of the application may be performed entirely by hardware, entirely by software (including firmware, resident software, micro-code, etc.) or by a combination of hardware and software. The above hardware or software may be referred to as a "data block," module, "" engine, "" unit, "" component, "or" system. 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 a combination thereof. Furthermore, aspects of the application may take the form of a computer product, comprising computer-readable program code, embodied in one or more computer-readable media. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disk, floppy disk, magnetic cassettes, etc.), optical disks (e.g., compact disk, digital versatile disk, dvd, etc.), smart cards, and flash memory devices (e.g., cards, sticks, key drives, etc.).
The computer readable medium may comprise a propagated data signal with the computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take on a variety of forms, including electro-magnetic, optical, etc., or any suitable combination thereof. A computer readable medium can be any computer readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer readable medium may be propagated through any suitable medium, including radio, cable, fiber optic cable, radio frequency signals, or the like, or a combination of any of the foregoing.
Similarly, it should be noted that in order to simplify the description of the present disclosure and thereby aid in understanding one or more inventive embodiments, various features are sometimes grouped together in a single embodiment, figure, or description thereof. This method of disclosure does not imply that more features than are mentioned are required for the object of the application. Indeed, less than all of the features of a single embodiment disclosed above.
In some embodiments, numbers describing the components, number of attributes are used, it being understood that such numbers being used in the description of embodiments are modified in some examples by the modifier "about," approximately, "or" substantially. Unless otherwise indicated, "about," "approximately," or "substantially" indicate that the number allows for a 20% variation. Accordingly, in some embodiments, the numerical parameters employed in the present application are approximations that may vary depending upon the desired properties sought to be obtained by the individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and employ a method for preserving the general number of digits. Although the numerical ranges and parameters set forth herein are approximations in some embodiments for use in determining the breadth of the range, in particular embodiments, the numerical values set forth herein are as precisely as possible.
While the application has been described with reference to the specific embodiments presently, it will be appreciated by those skilled in the art that the foregoing embodiments are merely illustrative of the application, and various equivalent changes and substitutions may be made without departing from the spirit of the application, and therefore, all changes and modifications that come within the spirit of the application are desired to be protected.
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