Method for simulating stress distribution of heart valve and perivalvular tissue by guide wire

Abstract

The invention relates to the technical field of medical instruments, and discloses a method for simulating stress distribution of a heart valve and a perivalvular tissue by a guide wire, which comprises the following steps: acquiring image data of the heart valve and the perivalvular tissue of a patient before an operation, and acquiring the dependent variable of each structure; constructing a material constitutive equation of the heart valve and the perivalvular tissue to determine a stress-strain relationship of each structure under different stress conditions; determining a first stress distribution condition of the heart valve and the perivalvular tissue according to the dependent variable of each structure in the heart valve and the perivalvular tissue and a stress-strain relationship of each structure under different stress conditions; acquiring a second stress distribution condition of the guide wire when the guide wire is in different morphological positions in the heart valve; and according to the first stress distribution condition and the second stress distribution condition, determining a third stress distribution condition of the guide wire to the heart valve and the perivalvular tissue when the guide wire is in different morphological positions in the heart valve so as to accurately perform intraoperative navigation of the guide wire.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and particularly to a method, device, equipment and medium for simulating the stress distribution of a guide wire on heart valves and perivalvular tissues. Background Art

[0002] With the aggravation of population aging in China, the incidence of heart valve diseases has shown a rapid growth trend. As a new technology for diagnosing and treating heart valve diseases, transcatheter heart valve intervention has gradually become the preferred treatment option for treating heart valve diseases in clinical practice due to its advantages such as less trauma and low risk. However, limited by the possible lack of experience and operation errors of operators, as well as the non-intuitive anatomical structures of individual patients' heart valves and perivalvular tissues, surgical complications such as vascular wall injury, valve displacement, and conduction block are still highly prevalent, and in severe cases, they can endanger the lives of patients. Therefore, intraoperative navigation and risk warning are very important.

[0003] Among them, the precise manipulation of the guide wire and the real-time stress state analysis during transcatheter heart valve intervention are crucial for reducing complications. However, in most current transcatheter heart valve interventions, such as Transcatheter Aortic Valve Implantation (TAVI), only the experience of doctors and the guidance of two-dimensional images are relied on during the operation, lacking real-time and intuitive feedback of the guide wire stress information, resulting in poor navigation effects of the guide wire. Summary of the Invention

[0004] The purpose of the present invention is to provide a method, system, equipment and medium for simulating the stress distribution of a guide wire on heart valves and perivalvular tissues, which can solve the technical problem that during transcatheter heart valve intervention, only the experience of doctors and the guidance of two-dimensional images are relied on, lacking real-time and intuitive feedback of the guide wire stress information, resulting in poor navigation effects of the guide wire.

[0005] To solve the above technical problem, an embodiment of the present invention provides a method for simulating the stress distribution of a guide wire on heart valves and perivalvular tissues, including the following steps: Obtain the preoperative image data of the patient's heart valves and perivalvular tissues; Obtain the strain of each structure in the heart valves and perivalvular tissues according to the image data, and construct the material constitutive equation of the heart valves and perivalvular tissues through the strains of all structures to determine the stress-strain relationship of each structure under different stress conditions; Determine the first stress distribution of the heart valves and perivalvular tissues according to the strain of each structure in the heart valves and perivalvular tissues and the stress-strain relationship of each structure under different stress conditions; According to the three-dimensional model of the heart valve and the perivalvular tissue and the three-dimensional model of the guide wire, simulate the insertion of the guide wire into the heart valve to obtain the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve; According to the first stress distribution and the second stress distribution, determine the third stress distribution of the guide wire on the heart valve and the perivalvular tissue when the guide wire is in different morphological positions in the heart valve.

[0006] Optionally, the obtaining the strain of each structure in the heart valve and the perivalvular tissue according to the image data and constructing the material constitutive equation of the heart valve and the perivalvular tissue through the strains of all structures includes: Establish a three-dimensional model of the patient's heart valve and perivalvular tissue at different times according to the image data, and obtain the pressure and strain of each structure in the heart valve and perivalvular tissue at different times through the three-dimensional model; Obtain the volume and pressure of each structure in the patient's heart valve and perivalvular tissue at different times according to the image data; Extract the pressure, strain and volume of each structure in the heart valve and perivalvular tissue at equal intervals, and use the Latin hypercube sampling method to construct a pressure-volume data set and a pressure-strain data set; According to the pressure-volume data set, the pressure-strain data set and the preset exponential relationship between the volume and pressure of the heart valve and the perivalvular tissue, combine the Holzapfel–Ogden model to construct the material constitutive equation.

[0007] Optionally, the Holzapfel–Ogden model is: ; In the formula, , is the matrix response parameter, , is the myocardial fiber material parameter, , is the proportion of myocardial fiber material, , represents the shear effect, , is the right Cauchy-Green tensor, is the deformation gradient, and are the invariants along the myocardial cell direction in the reference configuration respectively, is the coupling invariant.

[0008] Optionally, the simulating the insertion of the guide wire into the heart valve according to the three-dimensional model of the heart valve and the perivalvular tissue and the three-dimensional model of the guide wire to obtain the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve includes: Using 3D printing technology, a three-dimensional model of the patient's heart valve and perivalvular tissue is established, and guide wire models corresponding to multiple guide wires with different morphological positions are established respectively; The guide wire models corresponding to multiple guide wires with different morphological positions are respectively placed into the three-dimensional model of the patient's heart valve and perivalvular tissue to simulate the heart valve and perivalvular tissue of the patient after the guide wires are placed during the operation; Using the finite element analysis method, according to the simulated heart valve and perivalvular tissue after the guide wires are placed, the second stress distribution of the guide wires when the guide wires are in different morphological positions in the heart valve is obtained.

[0009] An embodiment of the present invention also provides a simulation device for the stress distribution of a guide wire on a heart valve and perivalvular tissue, including: A heart image acquisition module for acquiring image data of the patient's heart valve and perivalvular tissue before surgery; A stress and strain acquisition and construction module for obtaining the strain of each structure in the heart valve and perivalvular tissue according to the image data, and constructing a material constitutive equation of the heart valve and perivalvular tissue through the strains of all structures to determine the stress-strain relationship of each structure under different stress conditions; A first stress detection module for determining the first stress distribution of the heart valve and perivalvular tissue according to the strain of each structure in the heart valve and perivalvular tissue and the stress-strain relationship of each structure under different stress conditions; A second stress detection module for simulating the placement of a guide wire in the heart valve according to the three-dimensional model of the heart valve and perivalvular tissue and the three-dimensional model of the guide wire to obtain the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve; A third stress detection module for determining the third stress distribution of the guide wire on the heart valve and perivalvular tissue when the guide wire is in different morphological positions in the heart valve according to the first stress distribution and the second stress distribution;

[0010] An embodiment of the present invention also provides a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, instructions executable by the at least one processor are stored in the memory, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the above-mentioned simulation method for the stress distribution of a guide wire on a heart valve and perivalvular tissue.

[0011] An embodiment of the present invention also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above-mentioned simulation method for the stress distribution of a guide wire on a heart valve and perivalvular tissue is implemented.

[0012] The simulation method of the stress distribution of the guide wire on the heart valve and perivalvular tissue provided by the present invention has the following beneficial effects: Through the image data of the patient's heart valve and perivalvular tissue before surgery, the strain of each structure in the heart valve and perivalvular tissue can be obtained. According to this strain, the material constitutive equation of the heart valve and perivalvular tissue is constructed, and the stress-strain relationship of each structure in the heart valve and perivalvular tissue under different forces is obtained, so as to obtain the first stress distribution of the heart valve and perivalvular tissue. Then, after inserting the guide wire into the simulated heart valve, the second stress distribution of the guide wire when it is in different morphological positions in the heart valve can be determined. Furthermore, according to the first stress distribution and the second stress distribution, the third stress distribution of the guide wire on the heart valve and perivalvular tissue when the guide wire is in different morphological positions in the heart valve can be determined.

[0013] That is to say, the present invention obtains the third stress distribution of the guide wire on the heart valve and perivalvular tissue when the guide wire is in each morphological position during the patient's operation through simulation. Then, the mapping relationship between the guide wire morphological position and the third stress distribution can assist in judging the real-time stress distribution of the guide wire on the heart valve and perivalvular tissue according to the real-time morphological position of the guide wire during the heart valve interventional surgery, obtaining the real-time stress state of the guide wire, and using it for the intraoperative navigation of the guide wire, which can achieve precise control of the guide wire during the heart valve interventional surgery, thereby improving the success rate of the surgery. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] One or more embodiments are illustrated by way of example in the accompanying drawings, and these exemplary illustrations do not limit the embodiments.

[0015] Figure 1 is a flowchart of a simulation method of the stress distribution of a guide wire on a heart valve and perivalvular tissue according to an embodiment of the present invention Figure 1 ; Figure 2 is a parameter prediction diagram of a material constitutive equation according to an embodiment of the present invention; Figure 3 is a flowchart of a simulation method of the stress distribution of a guide wire on a heart valve and perivalvular tissue according to an embodiment of the present invention Figure 2 . DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will elaborate on each embodiment of the present invention in detail with reference to the accompanying drawings. However, those of ordinary skill in the art can understand that in each embodiment of the present invention, many technical details are provided to help readers better understand the present invention. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions claimed in the present invention can still be implemented. The division of the following embodiments is for convenience of description and should not constitute any limitation on the specific implementation of the present invention. The various embodiments can be combined and cross-referenced with each other on the premise of not being contradictory.

[0017] An embodiment of the present invention relates to a method for simulating the stress distribution of a guide wire on a heart valve and perivalvular tissue. The following will specifically describe the implementation details of the method for simulating the stress distribution of the guide wire on the heart valve and perivalvular tissue in this embodiment. The following content is only implementation details provided for convenience of understanding and is not necessary for implementing this solution.

[0018] The specific process of the method for simulating the stress distribution of the guide wire on the heart valve and perivalvular tissue in this embodiment can be as Figure 1 shown and includes: Step 101: Obtain the image data of the patient's heart valve and perivalvular tissue before surgery.

[0019] Among them, the image data includes medical image data such as Computed Tomography Angiography (CTA), Magnetic Resonance Imaging (MRI), and ultrasound of the patient's heart valve and perivalvular tissue before surgery.

[0020] Step 102: Obtain the strain of each structure in the heart valve and perivalvular tissue according to the image data, and construct the material constitutive equation of the heart valve and perivalvular tissue through the strains of all structures to determine the stress-strain relationship of each structure under different forces.

[0021] Specifically, a three-dimensional model of the patient's heart valve and perivalvular tissue at different times is established based on the imaging data, and the pressure and strain of each structure in the heart valve and perivalvular tissue at different times are obtained through the three-dimensional model; the volume and pressure of each structure in the patient's heart valve and perivalvular tissue at different times are obtained from the imaging data; the pressure, strain, and volume of each structure in the heart valve and perivalvular tissue are sampled at equal intervals, and the pressure-volume dataset and pressure-strain dataset are constructed using the Latin hypercube sampling method; according to the pressure-volume dataset and pressure-strain dataset and the preset exponential relationship between the volume and pressure of the heart valve and perivalvular tissue, a material constitutive equation is constructed in combination with the Holzapfel–Ogden (HO) model for hyperelastic right heart mechanics research.

[0022] Among them, the HO model is expressed as: ; In the formula, , is the matrix response parameter, , is the myocardial fiber material parameter, , is the proportion of myocardial fiber material, , represents the shear effect, , is the right Cauchy-Green tensor, is the deformation gradient, and are the invariants along the myocardial cell direction in the reference configuration, is the coupling invariant and needs to be further determined.

[0023] Since the 8 material parameters of the HO model (i.e., , , , , , , , ) have strong correlations, the parameter dimensionality reduction can be performed according to the following formula: ; Since different myocardial structures of the patient have different material parameters, in the formula, , , , are the correction factors of the patient's actual heart model and need to be fitted through iterative calculations, , , , , , , , are the empirical reference values for a healthy heart model.

[0024] Therefore, in this embodiment, it is necessary to determine the correction factors , , , in the HO model, and then construct the material constitutive equations of the heart valve and the tissue around the valve.

[0025] In a specific implementation, an XGBoost machine learning model is constructed. As Figure 2 shown, input , , , , , , given an initial , , , , with a value range of [0.1, 5] 4 , and through iterative training, output , , , , to achieve rapid prediction of individual material constitutive parameters at different positions of the patient's heart model, such as the ventricle, aorta and other parts.

[0026] Step 103: Determine the first stress distribution of the heart valve and the tissue around the valve according to the strain of each structure in the heart valve and the tissue around the valve and the stress-strain relationship of each structure under different forces. Step 104: According to the three-dimensional model of the heart valve and the tissue around the valve and the three-dimensional model of the guide wire, simulate inserting the guide wire into the heart valve to obtain the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve.

[0027] Specifically, 3D printing technology is used to establish a three-dimensional model of the patient's heart valve and the tissue around the valve, and establish guide wire models corresponding to multiple guide wires with different morphological positions respectively; insert the guide wire models corresponding to multiple guide wires with different morphological positions into the three-dimensional model of the patient's heart valve and the tissue around the valve respectively to simulate the heart valve and the tissue around the valve after the guide wire is inserted during the operation; use the finite element analysis method to obtain the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve according to the simulated heart valve and the tissue around the valve after the guide wire is inserted.

[0028] Step 105: According to the first stress distribution and the second stress distribution, determine the third stress distribution of the guide wire on the heart valve and the perivalvular tissue when the guide wire is in different morphological positions in the heart valve.

[0029] In a specific implementation, a patient model based on material constitutive is constructed according to 3D printing technology. A guide wire is inserted so that it has different morphological position distributions in the patient model. Then, a guide wire beam element model is constructed, and the stress distributions of the guide wire at different morphological positions (i.e., the second stress distribution) and the stress of the guide wire on the model (i.e., the third stress distribution) are obtained based on experimental methods and finite element analysis.

[0030] First, set up an experimental bench, including a three-dimensional model of the patient's heart valve and perivalvular tissue printed by 3D printing, a guide wire instrument for cardiac valve intervention surgery, an in-vivo environment simulation system, and a parameter detection device. Among them, the patient individualized model (i.e., the three-dimensional model of the heart valve and perivalvular tissue) is printed by 3D printing technology, using materials such as hydrogel, and has the real material constitutive properties of the patient. The in-vivo environment simulation system is used to simulate the real boundary conditions in the patient's cardiovascular system. The parameter detection device includes a flow sensor, a pressure sensor, a strain sensor, a temperature sensor, etc., which can monitor the changes in parameters such as pressure, strain, and temperature in real time during the experiment. During the experiment, by operating the guide wire instrument for cardiac valve intervention surgery, it has different morphological position distributions in the patient model, and at the same time, the real-time pushing force changes measured on the instrument are obtained. The required parameter changes are obtained by the parameter detection device, and the corresponding stress distributions are calculated. In finite element calculation, the guide wire is set as a beam element model, and it is set in finite element analysis software such as ABAQUS according to the material properties of the guide wire. The constraints and boundary conditions correspond one by one to the guide wire in different morphological positions in the experiment, and the stress distribution of the guide wire and the stress of the guide wire on the model are calculated.

[0031] In this embodiment, through the imaging data of the patient's heart valve and perivalvular tissue before surgery, the strain of each structure in the heart valve and perivalvular tissue can be obtained. According to this strain, the material constitutive equation of the heart valve and perivalvular tissue is constructed, and the stress-strain relationship of each structure in the heart valve and perivalvular tissue under different force conditions is obtained, so as to obtain the first stress distribution of the heart valve and perivalvular tissue. Then, after inserting the guide wire into the simulated heart valve, the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve can be determined. Furthermore, according to the first stress distribution and the second stress distribution, the third stress distribution of the guide wire on the heart valve and the perivalvular tissue when the guide wire is in different morphological positions in the heart valve can be determined.

[0032] That is to say, in this embodiment, by simulation, when the guide wire is in each morphological position during the operation of the patient, the third stress distribution of the guide wire on the heart valve and the tissue around the valve is obtained. Then, the mapping relationship between the morphological position of the guide wire and the third stress distribution can assist in judging the real-time stress distribution of the guide wire on the heart valve and the tissue around the valve according to the real-time morphological position of the guide wire during the cardiac valve interventional surgery, obtaining the real-time stress state of the guide wire, and using it for the intraoperative navigation of the guide wire, so as to achieve precise control of the guide wire during the cardiac valve interventional surgery, thereby improving the success rate of the surgery.

[0033] Among them, when performing intraoperative navigation of the guide wire according to the third stress distribution, the third stress distribution of the guide wire on the heart valve and the tissue around the valve when the guide wire is in different morphological positions in the heart valve and the real-time morphological position of the guide wire during the operation of the patient can be combined to determine the real-time stress distribution of the guide wire on the heart valve and the tissue around the valve during the operation, so as to perform intraoperative navigation of the guide wire through the real-time stress distribution of the guide wire on the heart valve and the tissue around the valve.

[0034] Specifically, according to the first stress distribution, the second stress distribution, and the third stress distribution, a stress distribution prediction model of the heart valve and the tissue around the valve is established; according to the image data of the patient's heart valve and the tissue around the valve at each moment after the guide wire is implanted during the operation, the morphological position of the guide wire at each moment during the operation is obtained to determine the second stress distribution of the guide wire at each moment during the operation; the first stress distribution and the second stress distribution of the guide wire at each moment are input into the stress distribution prediction model to obtain the third stress distribution of the guide wire on the heart valve and the tissue around the valve at each moment during the operation as the real-time stress distribution; according to the real-time stress distribution, with the goal of reducing the stress distribution of the guide wire on the heart valve and the tissue around the valve during the operation, a movement path is planned for the guide wire during the operation to complete the intraoperative navigation of the guide wire.

[0035] In a specific implementation, the first stress distribution of the heart valve and the tissue around the valve, the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve, and the third stress distribution of the guide wire on the heart valve and the tissue around the valve can be used as a data set to construct a stress distribution prediction model of the guide wire-patient three-dimensional model based on deep learning. By obtaining multiple two-dimensional perspective views of different angles of the heart valve and the tissue around the valve after the guide wire is implanted into the patient's heart valve and using the image registration method according to the multiple two-dimensional perspective views of different angles, the morphological position of the guide wire in the heart valve can be located. Based on this, the three-dimensional model of the guide wire can be quickly reconstructed and placed into the patient's individualized model to achieve intraoperative tracking of the guide wire, and then based on the stress distribution prediction model of the guide wire-patient three-dimensional model, the stress distribution of the guide wire and the patient's individualized model can be automatically and quickly obtained.

[0036] Among them, intraoperative multi-modal image data such as two-dimensional perspective views of the patient from multiple angles are input in real time, and three-dimensional cloud maps of the stress field and two-dimensional perspective views including the patient model and the guide wire are quickly output. The constructed deep learning model includes, but is not limited to, deep learning models such as UNet and VNet. Image registration methods include, but are not limited to, 2D image-3D model registration methods such as LCD, 2D-3D MatchNet, triplet loss function, and VGG-Net.

[0037] In one example, when obtaining the morphological position of the guide wire at each moment during the operation based on the image data of the patient's heart valve and perivalvular tissue at each moment after the guide wire is inserted during the operation, preoperative two-dimensional images of the heart valve and perivalvular tissue at three angles, namely the coronal plane, sagittal plane, and horizontal plane, are obtained based on the preoperative image data of the patient's heart valve and perivalvular tissue; intraoperative two-dimensional images of the heart valve and perivalvular tissue at three angles, namely the coronal plane, sagittal plane, and horizontal plane, are obtained based on the image data of the patient's heart valve and perivalvular tissue after the guide wire is inserted during the operation; the intraoperative two-dimensional images at each angle are registered with the preoperative two-dimensional images at the corresponding angle to determine the angle with the highest registration degree; and the morphological position of the guide wire during the operation is obtained based on the intraoperative two-dimensional image corresponding to the angle with the highest registration degree.

[0038] In one example, according to the various morphological positions of the guide wire in the patient during the operation, the movement process of the guide wire in the patient during the operation can be determined. Then, in combination with the movement process of the guide wire in the patient during the operation, as well as the second stress distribution of the guide wire and the third stress distribution of the guide wire on the heart valve and perivalvular tissue when the guide wire is in each morphological position, intraoperative navigation of the guide wire can be performed.

[0039] For example, AR software and wearable devices are used to visually display the position and movement of the guide wire in real time, dynamically track the movement and stress field of the guide wire in the three-dimensional model of the patient's heart valve and perivalvular tissue during the operation, and predict the risk of mechanical-related complications. Among them, the AR immersive visualization interface can be displayed in real time through a holographic display, a head-mounted display, etc., and includes, but is not limited to, three-dimensional image stereo information such as a three-dimensional model of the aortic valve and perivalvular tissue of the intraoperative patient including an artificial valve, the mechanical field of the heart valve and perivalvular tissue, the position of the guide wire model and its real-time movement, etc., and can also provide complication prediction and warning information during the operation.

[0040] The following uses a specific embodiment to illustrate the specific process of realizing the intraoperative navigation method of the guide wire for heart valve intervention surgery by using the method for simulating the stress distribution of the heart valve and perivalvular tissue by the guide wire of the present invention, as Figure 2 shown, including: 1. Obtain preoperative multi-modal image data of the patient; 2. Process the preoperative multimodal imaging data of the patient using machine learning methods to obtain the strain of structures such as the vessel wall and myocardium, construct the constitutive equations of the patient's individualized blood vessels and myocardium, calculate the stress distribution using finite element analysis, and construct a stress distribution dataset for the three-dimensional model of the patient's heart valve and perivalvular tissue; 3. Construct a patient model based on the material constitutive using 3D printing technology, insert a guide wire, and make it have different morphological position distributions in the patient model. Construct a beam element model of the guide wire, and obtain the stress distribution of the guide wire in different morphological positions and the stress of the guide wire on the model based on experimental methods and finite element analysis to construct a deep learning dataset;

[0041] 4. Combine the datasets obtained in the above two steps to construct a stress distribution prediction model for the guide wire-patient three-dimensional model based on deep learning; 5. Obtain multimodal imaging data such as multi-angle two-dimensional perspective views of the patient during the operation; 6. Use the image registration method to locate the position of the guide wire in the patient's individualized model, quickly reconstruct the three-dimensional model of the guide wire and insert it into the patient's individualized model to achieve intraoperative tracking of the guide wire; 7. Based on the stress distribution prediction model of the guide wire-patient three-dimensional model, automatically and quickly obtain the stress distribution of the guide wire and the patient's individualized model; 8. Use AR software and wearable devices to visually display the position and movement of the guide wire in real time, dynamically track the movement and stress field of the guide wire in the three-dimensional model of the patient's heart valve and perivalvular tissue during the operation, and predict the risk of mechanical complications.

[0042] This embodiment can achieve real-time positioning, force analysis, and precise manipulation of the guide wire during the operation, which has important clinical significance for reducing the complications of TAVR surgery, improving the success rate of the operation, and ultimately improving the prognosis of the patient.

[0043] Use experimental and finite element analysis methods to measure and calculate the stress distribution of the guide wire, the force and stress distribution in the contact area between the guide wire and the patient, and obtain the respective stress fields of guide wires of different shapes, which can more accurately help the subsequent constructed deep learning model to more accurately describe the morphological changes of the guide wire in the complex vascular environment and improve the accuracy and reliability of navigation.

[0044] The deep learning model can quickly and accurately analyze the real-time imaging data obtained during the operation, and extract key information such as the position, shape, stress of the guide wire, and the stress distribution of the patient affected by the guide wire, which has high accuracy and generalization ability and can effectively assist clinicians in precise guide wire manipulation.

[0045] Visualizing the key information during the operation using VR technology can intuitively display the three-dimensional model, position, stress field of the guide wire, as well as the structure and stress distribution of the surrounding blood vessels and tissues, thereby helping clinicians better understand the surgical environment and improving the efficiency and safety of surgical operations.

[0046] The step division of the above various methods is only for clear description. When implemented, they can be combined into one step or some steps can be split into multiple steps. As long as the same logical relationship is included, it is within the protection scope of the present invention; adding insignificant modifications or introducing insignificant designs to the algorithm or process, but not changing the core design of its algorithm and process, is within the protection scope of the invention.

[0047] Another embodiment of the present invention relates to a simulation device for the stress distribution of a guide wire on a heart valve and perivalvular tissue. The implementation details of the simulation device for the stress distribution of the guide wire on the heart valve and perivalvular tissue in this embodiment will be specifically described below. The following content is only the implementation details provided for convenient understanding and is not necessary for implementing this solution. The simulation device for the stress distribution of the guide wire on the heart valve and perivalvular tissue in this embodiment includes: A cardiac image acquisition module for acquiring the image data of the patient's heart valve and perivalvular tissue before the operation.

[0048] A constitutive equation construction module for obtaining the strain of each structure in the heart valve and perivalvular tissue according to the image data, and constructing the material constitutive equation of the heart valve and perivalvular tissue through the strains of all structures to determine the stress-strain relationship of each structure under different forces.

[0049] A first stress detection module for determining the first stress distribution of the heart valve and perivalvular tissue according to the strain of each structure in the heart valve and perivalvular tissue and the stress-strain relationship of each structure under different forces.

[0050] A second stress detection module for simulating the implantation of the guide wire in the heart valve according to the three-dimensional model of the heart valve and perivalvular tissue and the three-dimensional model of the guide wire to obtain the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve.

[0051] A third stress detection module for determining the third stress distribution of the guide wire on the heart valve and perivalvular tissue when the guide wire is in different morphological positions in the heart valve according to the first stress distribution and the second stress distribution.

[0052] It is not difficult to find that this embodiment is a device embodiment corresponding to the above method embodiment, and this embodiment can be implemented in cooperation with the above method embodiment. The relevant technical details and technical effects mentioned in the above embodiments are still valid in this embodiment. To avoid repetition, they will not be elaborated here. Correspondingly, the relevant technical details mentioned in this embodiment can also be applied to the above embodiments.

[0053] It is worth mentioning that each module involved in this embodiment is a logical module. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, to highlight the innovative part of the present invention, units that are not closely related to solving the technical problems proposed by the present invention are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.

[0054] Another embodiment of the present invention relates to a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method for simulating the stress distribution of a guide wire on a heart valve and perivalvular tissue in the above embodiments.

[0055] Among them, the memory and the processor are connected by a bus. The bus can include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and the memory together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, so they will not be further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be an element or multiple elements, such as multiple receivers and transmitters, and provides a unit for communicating with various other devices on the transmission medium. The data processed by the processor is transmitted over the wireless medium through the antenna. Further, the antenna also receives data and transmits the data to the processor.

[0056] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interface, voltage regulation, power management, and other control functions. The memory can be used to store the data used by the processor when executing operations.

[0057] Another embodiment of the present invention relates to a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the above method embodiments are implemented.

[0058] That is, those skilled in the art can understand that all or part of the steps in the methods of the above embodiments can be completed by instructing relevant hardware through a program. The program is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0059] Those of ordinary skill in the art can understand that the above embodiments are specific embodiments for implementing the present invention, and in actual applications, various changes can be made to them in form and details without departing from the spirit and scope of the present invention.

Claims

1. A simulation method for the stress distribution of a guide wire on a heart valve and perivalvular tissue, characterized in that, The method includes: Obtaining the image data of the patient's heart valve and perivalvular tissue before surgery; Obtaining the strain of each structure in the heart valve and perivalvular tissue according to the image data, and constructing the material constitutive equation of the heart valve and perivalvular tissue through the strains of all structures to determine the stress-strain relationship of each structure under different forces; Determining the first stress distribution of the heart valve and perivalvular tissue according to the strain of each structure in the heart valve and perivalvular tissue and the stress-strain relationship of each structure under different forces; According to the three-dimensional model of the heart valve and perivalvular tissue and the three-dimensional model of the guide wire, simulating the placement of the guide wire in the heart valve to obtain the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve; Determining the third stress distribution of the guide wire on the heart valve and perivalvular tissue when the guide wire is in different morphological positions in the heart valve according to the first stress distribution and the second stress distribution; 2. The simulation method of the stress distribution of the guide wire on the heart valve and the tissue around the valve according to claim 1, characterized in that, The obtaining the strain of each structure in the heart valve and perivalvular tissue according to the image data, and constructing the material constitutive equation of the heart valve and perivalvular tissue through the strains of all structures includes: Establishing three-dimensional models of the patient's heart valve and perivalvular tissue at different times according to the image data, and obtaining the pressure and strain of each structure in the heart valve and perivalvular tissue at different times through the three-dimensional models; Obtaining the volume and pressure of each structure in the patient's heart valve and perivalvular tissue at different times according to the image data; Equally spaced sampling of the pressure, strain and volume of each structure in the heart valve and perivalvular tissue, and constructing a pressure-volume data set and a pressure-strain data set by using the Latin hypercube sampling method; Constructing a material constitutive equation according to the pressure-volume data set, the pressure-strain data set and the preset exponential relationship between the volume and pressure of the heart valve and perivalvular tissue, and combining with the Holzapfel–Ogden model.

3. The method for simulating the stress distribution of a heart valve and perivalvular tissue by a guide wire according to claim 2, wherein The Holzapfel–Ogden model is: ； In the formula, , is the matrix response parameter, , is the myocardial fiber material parameter, , is the proportion of myocardial fiber material, , represents the shear effect, , is the right Cauchy-Green tensor, is the deformation gradient, and are the invariants along the direction of myocardial cells in the reference configuration respectively, is the coupling invariant.

4. The simulation method of the stress distribution of the guide wire on the heart valve and the perivalvular tissue according to claim 1, wherein The according to the three-dimensional model of the heart valve and perivalvular tissue and the three-dimensional model of the guide wire, simulating the placement of the guide wire in the heart valve to obtain the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve includes: Using 3D printing technology to establish a three-dimensional model of the patient's heart valve and perivalvular tissue, and establishing guide wire models corresponding to multiple guide wires with different morphological positions respectively; Respectively placing the guide wire models corresponding to multiple guide wires with different morphological positions into the three-dimensional model of the patient's heart valve and perivalvular tissue to simulate the heart valve and perivalvular tissue of the patient after the guide wire is placed during the operation; Using the finite element analysis method, according to the simulated heart valve and perivalvular tissue after the guide wire is placed, obtaining the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve.

5. A simulation device for the stress distribution of a guide wire on a heart valve and perivalvular tissue, characterized in that Including: A heart image acquisition module for obtaining the image data of the patient's heart valve and perivalvular tissue before surgery; A stress-strain acquisition building block is used to obtain the strain of each structure in the heart valve and perivalvular tissue according to the image data, and construct a material constitutive equation of the heart valve and perivalvular tissue through the strains of all structures to determine the stress-strain relationship of each structure under different forces; A first stress detection module is used to determine the first stress distribution of the heart valve and perivalvular tissue according to the strain of each structure in the heart valve and perivalvular tissue and the stress-strain relationship of each structure under different forces; A second stress detection module is used to simulate the insertion of a guide wire into the heart valve according to the three-dimensional model of the heart valve and perivalvular tissue and the three-dimensional model of the guide wire, so as to obtain the second stress distribution of the guide wire when the guide wire is in different morphological positions in the heart valve; A third stress detection module is used to determine the third stress distribution of the guide wire on the heart valve and perivalvular tissue when the guide wire is in different morphological positions in the heart valve according to the first stress distribution and the second stress distribution; 6. A computer device, characterized in that, Including: At least one processor; And a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the simulation method of the stress distribution of the guide wire on the heart valve and perivalvular tissue according to any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, the simulation method of the stress distribution of the guide wire on the heart valve and perivalvular tissue according to any one of claims 1 to 4 is implemented.

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