A method for simulating aneurysm virtual stent implantation based on spring analogy

Abstract

The present invention discloses a method for simulating aneurysm virtual stent implantation based on a spring analogy method. The method comprises: reconstructing a three-dimensional model of the preoperative parent vessel and the parent vessel after aneurysm restoration based on clinical imaging data; extracting the centerline of the first vessel to construct a virtual stent initialization model; deploying the virtual stent initialization model using a spring analogy virtual stent fast algorithm to determine the three-dimensional model of the virtual stent after deployment in the individualized vessel; and calculating efficacy evaluation parameters using a fast algorithm based on the arc surface porosity of the virtual stent neck. The present invention can simulate the actual motion of stent deployment and significantly shorten the simulation calculation time and efficacy evaluation time of simulated stent deployment within a vessel, thereby achieving real-time guidance during virtual aneurysm intervention.

Description

Technical Field

[0001] The present application relates to the field of biomedical engineering and computer science, and more specifically, to a method for simulating aneurysm virtual stent implantation based on a spring analogy method. Background Art

[0002] Intracranial aneurysms are vascular diseases characterized by abnormal, localized dilation of the intracranial arterial wall, resulting in a cerebral aneurysm-like protrusion. Subarachnoid hemorrhage (SAH) caused by rupture is associated with high mortality and disability rates. According to statistics, the global prevalence of unruptured SAH in people aged around 50 years is approximately 3%. Rupture of an intracranial aneurysm is the leading cause of spontaneous SAH, with a global incidence of approximately 6.1 cases per 100,000 person-years. Most patients suffer significant neurological impairment, severely impacting their quality of life.

[0003] Blood flow redirection devices have a high occlusion rate for aneurysm treatment, helping doctors precisely guide treatment equipment to the aneurysm site, ensuring accurate and effective treatment. Virtual stents effectively simulate the morphology of blood flow redirection devices within the parent vessel. This simulation analyzes the improvement in blood flow within the vessel, helping doctors assess the postoperative efficacy. Summary of the Invention

[0004] In view of the above problems, the purpose of the present invention is to provide an aneurysm virtual stent implantation simulation method based on the spring analogy method, which is dedicated to promoting advanced aneurysm virtual stent technology and bringing important innovations to the medical industry. By integrating computer graphics and medical imaging technology, a new surgical simulation and program planning tool is provided to improve the accuracy and safety of surgery. By using a virtual stent fast algorithm and the Simplex grid method, shear and bending forces are reasonably applied through spring analogy, making the simulation more realistic and closer to the actual shape of the stent after deployment. This virtual stent technology not only has advantages in preoperative planning, but also can provide real-time guidance to doctors to ensure the best results during surgery.

[0005] A first aspect of the present invention provides a method for simulating aneurysm virtual stent implantation based on a spring analogy method, comprising:

[0006] Acquiring clinical imaging data; the clinical imaging data at least includes the patient's preoperative vascular imaging data;

[0007] Reconstructing a three-dimensional model of the preoperative parent vessel and the mother vessel after aneurysm reduction based on analysis of the clinical imaging data; the three-dimensional model of the preoperative parent vessel and the mother vessel after aneurysm reduction includes a three-dimensional model of the preoperative parent vessel and a three-dimensional model of the mother vessel after aneurysm reduction;

[0008] extracting the centerline of the first blood vessel through the three-dimensional model of the parent blood vessel after the aneurysm is restored;

[0009] Constructing a virtual stent initialization model based on the centerline of the first blood vessel;

[0010] Based on a fast algorithm of a spring analogy virtual support, the virtual support initialization model is expanded to determine a three-dimensional model of the virtual support;

[0011] An analysis is performed based on the preoperative three-dimensional model of the tumor-bearing main vessel and the three-dimensional model of the virtual stent, and therapeutic effect evaluation parameters are calculated using a fast algorithm based on the porosity of the neck arc surface of the virtual stent.

[0012] In this solution, the analysis based on the clinical imaging data is performed to reconstruct a three-dimensional model of the preoperative parent vessel and the parent vessel after aneurysm reduction, including:

[0013] By analyzing the clinical imaging data, a three-dimensional model of the main tumor-bearing vessels before surgery is reconstructed;

[0014] preprocessing the preoperative three-dimensional model of the tumor-bearing main blood vessel;

[0015] generating a second vessel centerline based on a preprocessed preoperative three-dimensional model of the parent vessel, truncating the parent vessels at both ends of the aneurysm in the preprocessed preoperative three-dimensional model of the parent vessel, fitting a centerline segment of the aneurysm region based on the second vessel centerlines of the parent vessels at both ends of the aneurysm, and performing discretization on the centerline segment;

[0016] Obtain the lumen contour of the parent vessel end close to the aneurysm;

[0017] The lumen contour is fitted and transitioned by discrete points obtained through discretization processing to obtain a three-dimensional model of the parent blood vessel after aneurysm restoration.

[0018] In this solution, the pre-processing of the three-dimensional model of the tumor-bearing main vessel before surgery includes:

[0019] Reconstructing the mesh of the preoperative three-dimensional model of the tumor-bearing main blood vessel;

[0020] The triangular mesh of the reconstructed preoperative tumor-bearing main vessel 3D model was converted into a Simplex mesh.

[0021] In this solution, the step of constructing a virtual stent initialization model based on the first blood vessel centerline includes:

[0022] Determine a plurality of first nodes on the centerline of the first blood vessel; the number of the first nodes is determined according to the curvature of the stent wire;

[0023] Analyzing the centerline of the first blood vessel to determine the tangent direction of each first node on the centerline of the first blood vessel;

[0024] Make a circle with a preset initial radius and perpendicular to the corresponding tangent direction with each first node as the center;

[0025] Determine the number of second nodes on each circle based on the total number of stent filaments of the virtual stent, and uniformly discretize the second nodes on each circle; the number of the second nodes is determined according to the number of stent filaments;

[0026] A virtual support initialization model is constructed by performing forward and reverse spiral sorting on the second nodes on the adjacent circles, and the second nodes are determined as support nodes;

[0027] The diamond mesh of the virtual support initialization model is converted into a Simplex mesh.

[0028] In this solution, the spring analogy-based virtual support fast algorithm expands the virtual support initialization model to determine the virtual support three-dimensional model, including:

[0029] The expansion force of the stent itself is defined as the internal force, and the resistance encountered by the stent when it expands and contacts the inner wall of the blood vessel is defined as the external force;

[0030] The stent nodes are assumed to be point masses that follow the laws of physics, and the point masses of the stent nodes are set. The weighting factors of the internal and external forces are obtained through tensile tests of the stent and intracranial vascular tissue. The weighting factors of the internal and external forces are used to determine the ratio of the internal and external forces acting on the stent nodes.

[0031] Iteratively expand the virtual support based on the motion trajectory and internal and external forces of the support node. When the internal and external forces of the support node reach a balanced state, the expansion of the support node in the direction perpendicular to the tangent is terminated accordingly.

[0032] The stent deployment is assumed to be the overall movement of multiple springs of the same material and model with positive and negative helices. Through mechanical analysis of the physical stent, the torque and axial force acting on a single stent wire are determined.

[0033] The stent is compared to a spring to conduct spring mechanical property experiments on the stent and a single stent wire, and the bending moment and torque of the microelement stent wire are calculated using the microelement method.

[0034] Applying the bending moment and torque of the microelement stent wire to the stent nodes of the virtual stent in the form of force to determine the stent tangential force;

[0035] The virtual stent is unfolded by the internal and external forces perpendicular to the tangential direction and the tangential force of the stent analogous to the spring, and the three-dimensional model of the virtual stent is determined.

[0036] This plan also includes:

[0037] The multiple ratio of the bracket tangential force is determined according to the distance from the bracket node to the center line end point, and the bracket tangential force is adjusted.

[0038] In this solution, the virtual support is iteratively expanded based on the motion trajectory of the support node and the internal and external forces. When the internal and external forces of the support node reach a balanced state, the expansion of the support node in the direction perpendicular to the tangent is terminated accordingly, including:

[0039] Stent deployment includes two stages, namely, a non-wall-touching stage and a wall-touching stage.

[0040] After each iterative expansion, the distance between the current position of the stent node and the position of the nearest Simplex grid node of the main tumor-bearing vessel before surgery is calculated;

[0041] When the distance is greater than or equal to a preset distance threshold, the expansion of the support node is in a non-wall-touching stage, and the support node expands outwards under the action of internal force;

[0042] When the distance is less than a preset distance threshold, the expansion of the support node enters the wall-touching stage, and the support node expands outward under the combined action of internal and external forces;

[0043] When the internal force is balanced with the external force, the stent node stops expanding.

[0044] This plan also includes:

[0045] The maximum and minimum values ​​of the distance between the nodes of the stent when the solid stent is only subjected to axial pressure and perpendicular to the axial pressure are set as the distance limit conditions between the nodes of the stent; the distance between the nodes of the stent includes the distance between the nodes of the stent wire and the distance between the nodes of the stent segment;

[0046] When the support nodes of the virtual support meet the distance restriction condition between the support nodes, determining that the support nodes reach the equilibrium position;

[0047] When all the stent nodes reach the equilibrium position, the final placement of the virtual stent is determined.

[0048] In this solution, the analysis is performed based on the preoperative three-dimensional model of the tumor-bearing main vessel and the three-dimensional model of the virtual stent, and the efficacy evaluation parameters are calculated using a fast algorithm based on the porosity of the neck arc of the virtual stent, including:

[0049] The efficacy evaluation parameters include at least the neck arc surface porosity;

[0050] Dividing the tumor neck plane based on the preoperative three-dimensional model of the tumor-bearing main blood vessel and obtaining contour position data of the tumor neck plane;

[0051] Calculating the intersection of the contour position data and the stent wire, and determining the node formed by the gap between the arc surface of the tumor neck after the stent wire is projected based on the preset stent wire diameter;

[0052] Calculate the sum of the polygonal areas formed by each node to determine the area of ​​the arc surface gap at the neck of the tumor;

[0053] The closed surface is generated by forming nodes through the gaps in the tumor neck arc surface, and the area of ​​the closed surface is calculated to obtain the area of ​​the tumor neck arc surface;

[0054] Based on the virtual stent neck arc surface porosity fast algorithm, the neck arc surface porosity is calculated by the neck arc surface porosity area and the neck arc surface area;

[0055] The fast algorithm for the porosity of the virtual stent neck arc surface is expressed as follows:

[0056] ;

[0057] Among them, K is the porosity of the tumor neck arc surface, S1 is the area of ​​the tumor neck arc surface, and S2 is the porosity area of ​​the tumor neck arc surface.

[0058] The present invention discloses a method for simulating aneurysm virtual stent implantation based on a spring analogy method. The method comprises: reconstructing a three-dimensional model of the preoperative parent vessel and the parent vessel after aneurysm restoration based on clinical imaging data; extracting the centerline of the first vessel to construct a virtual stent initialization model; deploying the virtual stent initialization model using a spring analogy virtual stent fast algorithm to determine the virtual stent three-dimensional model; and calculating efficacy evaluation parameters using a fast algorithm based on the arc surface porosity of the virtual stent neck. This method can simulate the actual motion of stent deployment and significantly shorten the simulation calculation time and efficacy evaluation time of simulated stent deployment within a vessel, thus enabling real-time guidance during virtual aneurysm intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A flow chart of a method for simulating aneurysm virtual stent implantation based on a spring analogy method provided by the present invention is shown;

[0060] Figure 2 A flowchart of the method for constructing a virtual stent initialization model provided by the present invention is shown;

[0061] Figure 3 A flow chart of a method for deploying a virtual stent initialization model provided by the present invention is shown;

[0062] Figure 4 It shows a schematic structural diagram of a first blood vessel centerline and a second blood vessel centerline provided by the present invention;

[0063] Figure 5A schematic diagram of the local morphological structure of the virtual stent provided by the present invention after it is fully deployed is shown;

[0064] Figure 6 A schematic structural diagram of a three-dimensional stent model of a virtual stent provided by the present invention after full deployment in a virtual tumor-bearing blood vessel is shown;

[0065] Figure 7 A schematic diagram of the gap nodes of the tumor neck arc surface after projection of the virtual stent wire provided by the present invention is shown. DETAILED DESCRIPTION

[0066] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of the present application and the features therein can be combined with each other.

[0067] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0068] Figure 1 A flow chart of an aneurysm virtual stent implantation simulation method based on a spring analogy method provided by the present invention is shown.

[0069] like Figure 1 As shown, the present invention discloses a method for simulating aneurysm virtual stent implantation based on a spring analogy method, comprising:

[0070] S102, obtaining clinical imaging data; the clinical imaging data at least includes the patient's preoperative vascular imaging data;

[0071] S104, based on the analysis of clinical imaging data, reconstructing a three-dimensional model of the preoperative parent vessel and the mother vessel after aneurysm reduction; the three-dimensional model of the preoperative parent vessel and the mother vessel after aneurysm reduction includes the three-dimensional model of the preoperative parent vessel and the mother vessel after aneurysm reduction;

[0072] S106, extracting the centerline of the first blood vessel through the three-dimensional model of the parent blood vessel after aneurysm restoration;

[0073] S108, constructing a virtual stent initialization model based on the centerline of the first blood vessel;

[0074] S110, based on a fast algorithm of a spring analogy virtual support, unfolding the virtual support initialization model to determine a three-dimensional model of the virtual support;

[0075] S112, based on the preoperative three-dimensional model of the tumor-bearing main vessel and the three-dimensional model of the virtual stent, the efficacy evaluation parameters are calculated through a fast algorithm based on the porosity of the neck arc of the virtual stent.

[0076] According to an embodiment of the present invention, the main tumor-bearing vessel is extracted by obtaining clinical imaging data such as the patient's preoperative vascular imaging data from the hospital, reconstructing the preoperative three-dimensional model of the main tumor-bearing vessel, and generating a three-dimensional model of the mother vessel after aneurysm restoration through truncation fitting operations. To ensure the accuracy of the model, the image data can be subjected to image preprocessing such as noise filtering and image enhancement, and the preoperative three-dimensional model of the main tumor-bearing vessel can be meshed and reconstructed using the preprocessed image data to reduce the complexity of the model calculation. Then, based on the three-dimensional model of the mother vessel after aneurysm restoration, the centerline extraction function is used to generate a centerline model of the blood vessel, and the centerline model file is subjected to data processing to obtain the first blood vessel centerline. The first blood vessel centerline is as follows: Figure 4 As shown in the image on the right. The centerline of the first blood vessel is imported into the reconstructed preoperative three-dimensional model of the tumor-bearing main blood vessel for subsequent use. Among them, the purpose of extracting the centerline of the first blood vessel is to provide an accurate stent placement path in the subsequent stent implantation simulation, and to ensure that the stent contraction length can accurately adapt to the three-dimensional model of the tumor-bearing main blood vessel. Based on the preset initial radius, multiple first nodes are selected on the centerline of the first blood vessel to draw a circle, and multiple second nodes are determined on each circle in a uniform and discrete manner according to the total number of stent wires of the simulated stent. The second nodes on adjacent circles are sorted in positive and negative spirals to construct a virtual stent initialization model. The virtual stent initialization model is expanded based on the internal and external forces perpendicular to the tangent and the tangential force of the stent analogous to the spring. Combined with the distance restriction conditions between the stent nodes, the final placement of the virtual stent is determined to obtain a three-dimensional model of the virtual stent. The fully expanded structure of the virtual stent three-dimensional model in the virtual tumor-bearing blood vessel is shown as follows Figure 6 Its local morphological structure is shown in Figure 5 shown.

[0077] A fast algorithm for calculating the arc porosity of the virtual stent neck surface is initiated. The neck plane is divided and its contour position data is obtained. The point of intersection with the stent filament is determined. Combined with the preset stent filament diameter, the nodes that form the arc porosity of the neck surface after the stent filament projection are determined. The arc porosity of the neck surface is calculated by summing the mesh area and the polygonal area formed by each node, thus generating a parameter for efficacy evaluation.

[0078] Through the above-mentioned implementation steps, the aneurysm virtual stent technology of the present invention realizes the whole process from image data processing, virtual stent implantation to simulation result analysis. This technology not only improves the accuracy of preoperative planning, but also provides doctors with real-time guidance of virtual surgery, greatly improving the safety and success rate of surgery. The present invention aims to introduce this innovative technology to more medical institutions, promote the overall improvement of aneurysm treatment level, and provide aneurysm patients with more reliable and safer treatment options. The aneurysm virtual stent implantation simulation method based on the spring analogy method provided by the present invention is suitable for various aneurysm virtual stent implantation simulations, including intracranial aneurysms, thoracic aortic aneurysms, abdominal aortic aneurysms, limb aneurysms and visceral artery aneurysms.

[0079] According to an embodiment of the present invention, based on analysis of clinical imaging data, a three-dimensional model of the parent vessel before surgery and the parent vessel after aneurysm reduction is reconstructed, including:

[0080] By analyzing clinical imaging data, a three-dimensional model of the main tumor-bearing vessels before surgery was reconstructed;

[0081] Pre-process the three-dimensional model of the main tumor-bearing vessels before surgery;

[0082] generating a second vessel centerline based on a preprocessed preoperative three-dimensional model of the parent vessel, truncating the parent vessels at both ends of the aneurysm in the preprocessed preoperative three-dimensional model of the parent vessel, fitting a centerline segment of the aneurysm region based on the second vessel centerlines of the parent vessels at both ends of the aneurysm, and performing discretization on the centerline segment;

[0083] Obtain the lumen contour of the parent vessel end close to the aneurysm;

[0084] The lumen contour is fitted and transitioned by discrete points obtained through discretization processing to obtain a three-dimensional model of the parent blood vessel after aneurysm restoration.

[0085] It should be noted that the patient's intracranial imaging data (such as CT or MRI images) and other clinical imaging data are exported from the hospital's imaging database. After the main vessel image of the tumor is extracted based on the patient's intracranial imaging data, a virtual three-dimensional model of the main vessel of the tumor and the mother vessel after aneurysm restoration is reconstructed through 3D. The preprocessing of the preoperative three-dimensional model of the main vessel of the tumor includes mesh reconstruction of the preoperative three-dimensional model of the main vessel of the tumor, and the centerline extraction function is used to extract the centerline of the preprocessed three-dimensional model of the main vessel of the tumor, to obtain the centerline of the second vessel. The centerline of the second vessel is as follows: Figure 4 As shown in the image on the left, the centerline segment of the aneurysm region is obtained based on the centerline fitting of the second vessel. Discretization is performed on this centerline segment, and overfitting is performed on the lumen contour of the parent vessel near the aneurysm to obtain a 3D model of the parent vessel after aneurysm restoration.

[0086] Among them, the lumen contour of the parent vessel end close to the aneurysm is obtained through the pre-processed three-dimensional model of the main tumor-bearing vessel before surgery.

[0087] According to an embodiment of the present invention, preprocessing the three-dimensional model of the tumor-bearing main vessel before surgery includes:

[0088] Reconstruct the mesh of the three-dimensional model of the main tumor-bearing vessels before surgery;

[0089] The triangular mesh of the reconstructed preoperative tumor-bearing main vessel 3D model was converted into a Simplex mesh.

[0090] It should be noted that the quality and resolution of image data directly affect the accuracy of the 3D model. Therefore, image preprocessing, such as noise filtering and image enhancement, is required to ensure the accuracy of the reconstructed model.

[0091] The preoperative 3D model of the tumor-bearing main vessel was reconstructed using preprocessed impact data. The model was optimized using mesh processing, including denoising, smoothing, and refinement, and the resulting mesh was saved. The goal of mesh optimization is to reduce computational complexity while maintaining geometric accuracy, enabling more efficient subsequent simulations.

[0092] Using the system conversion algorithm, the triangle mesh of the tumor-bearing blood vessels before surgery was converted into a Simplex mesh through the code, and the converted Simplex mesh model was saved.

[0093] The use of Simplex mesh can improve the efficiency and accuracy of simulation calculations, especially when dealing with complex geometric structures and mechanical properties.

[0094] Figure 2 A flowchart of the method for constructing a virtual stent initialization model provided by the present invention is shown;

[0095] like Figure 2 As shown, according to an embodiment of the present invention, constructing a virtual stent initialization model based on the centerline of the first blood vessel includes:

[0096] S202, determining a plurality of first nodes on the centerline of the first blood vessel; the number of the first nodes is determined according to the curvature of the stent filament;

[0097] S204, analyzing the centerline of the first blood vessel to determine the tangent direction of each first node on the centerline of the first blood vessel;

[0098] S206, sequentially drawing a circle with a preset initial radius and perpendicular to the corresponding tangent direction with each first node as the center;

[0099] S208, determining the number of second nodes on each circle based on the total number of stent filaments of the virtual stent, and uniformly discretizing the second nodes on each circle; the number of second nodes is determined according to the number of stent filaments;

[0100] S210, constructing a virtual stent initialization model by performing forward and reverse spiral sorting on the second nodes on the adjacent circles, and determining the second nodes as stent nodes;

[0101] S212, converting the diamond mesh of the virtual support initialization model into a Simplex mesh.

[0102] It should be noted that after completing the mesh conversion of the preoperative tumor-bearing main vessel 3D model, the first vessel centerline is imported, and an algorithm is developed to calculate the tangent direction of each first node on the first vessel centerline. A circle perpendicular to the tangential direction is drawn with each first node on the first vessel centerline as the center, and a preset initial radius is set for each circle. The number of first nodes is determined by the curvature of the stent filament. The greater the curvature of the stent filament, the greater the number of corresponding first nodes. The final number of first nodes is set by those skilled in the art based on actual needs. The preset initial radius is the initial radius of the virtual stent. The initial value of the preset initial radius is 0.1 mm, and those skilled in the art can adjust it based on actual needs. Because the stent is not subject to external forces during the free expansion phase, the setting of the preset initial radius does not affect the simulation of the virtual stent. However, it must comply with the size limit of the stent within the blood flow guidance device catheter. The second nodes on the circle are uniformly discretized. The number of discrete second nodes depends on the total number of stent filaments in the simulated stent. The stent initialization model grid is constructed by sorting the second nodes in a forward and reverse spiral.

[0103] During this process, the geometric shape and size changes of blood vessels need to be taken into account to ensure that the stent can adapt to the vascular structure of different patients.

[0104] Convert the diamond mesh of the virtual support initialization model to a simplex mesh and import the support initialization model mesh generated in the above steps. Use the conversion algorithm to convert the diamond mesh to a simplex mesh and save the converted simplex mesh model.

[0105] Simplex mesh can better simulate the stress and deformation of the stent in the blood vessel, thereby improving the accuracy of the simulation.

[0106] Figure 3 A flow chart of a method for deploying a virtual stent initialization model provided by the present invention is shown;

[0107] like Figure 3 As shown, according to an embodiment of the present invention, based on a fast algorithm of a spring analogy virtual support, the virtual support initialization model is expanded to determine a three-dimensional model of the virtual support, including:

[0108] S302, determining the expansion force of the stent itself as the internal force, and determining the resistance encountered by the stent when it expands and contacts the inner wall of the blood vessel as the external force;

[0109] S304, assuming the stent nodes to be point masses that obey the laws of physics, setting the point masses of the stent nodes, and obtaining weighting factors of internal and external forces through tensile tests of the stent and intracranial vascular tissue. The weighting factors of internal and external forces are used to determine the ratio of internal and external forces acting on the stent nodes.

[0110] S306, iteratively expanding the virtual support based on the motion trajectory and internal and external forces of the support node. When the internal and external forces of the support node reach a balanced state, the expansion of the support node in the direction perpendicular to the tangent line is terminated accordingly;

[0111] S308, assuming that the stent deployment is the overall movement of multiple springs of the same material and model with positive and negative helices, and determining the torque and axial force acting on a single stent wire through mechanical analysis of the physical stent;

[0112] S310, analogizing the stent to a spring, conducts spring mechanical property experiments on the stent and a single stent wire, and calculates the bending moment and torque of the microelement stent wire using the microelement method;

[0113] S312, applying the bending moment and torque of the microelement stent wire to the stent nodes of the virtual stent in the form of force to determine the stent tangential force;

[0114] S314 , the virtual stent is unfolded by using internal and external forces perpendicular to the tangential direction and the stent tangential force analogous to a spring, to determine a three-dimensional model of the virtual stent.

[0115] It should be noted that the formula used to describe the movement of the grid nodes under the action of force is divided into internal and external forces perpendicular to the tangential direction and the tangential force of the stent analogous to a spring. The stent is in a compressed state when it is placed, so the stent itself has an expansion force (internal force). The resistance encountered when the expansion reaches the inner wall of the blood vessel and contacts the inner wall of the blood vessel is called external force. When the internal and external forces reach a balance, the stent stops expanding. The specific implementation is: use mechanical formulas to describe the movement of the grid nodes under the action of internal and external forces, simulate the initial expansion process of the stent nodes under the action of internal forces, determine whether the stent nodes contact the blood vessel wall, and if so, introduce external force. When the internal and external forces are balanced, the stent expansion process is terminated.

[0116] In addition, the mechanical properties of the scaffold material, such as elastic modulus and yield strength, need to be considered to ensure the authenticity of the simulation.

[0117] The deployment of the stent is regarded as the overall movement of multiple positive and negative helices of springs of the same material and model. Through the mechanical analysis of a single stent wire of the physical stent, the in vitro tensile test of the stent and the code calculation, the moment M0 and the tangential force F exerted on the single stent wire can be obtained. The bending moment and torque of the intercepted micro-element stent wire can be obtained by the micro-element method. The above bending moment and torque are applied to the virtual stent node in the form of force as the stent tangential force. The specific implementation is as follows: perform mechanical analysis on a single stent wire of the physical stent, obtain the parameter data of the moment M0 and the axial force F, use the micro-element method to calculate the bending moment and torque of the intercepted micro-element stent wire, apply the bending moment and torque in the form of force to the stent node of the virtual stent, determine the stent tangential force, set the distance from the stent node to the end point of the center line as a multiple of the stent tangential force, and adjust the multiple ratio according to clinical data.

[0118] During this process, a large amount of experiments and data analysis are required to ensure the accuracy and reliability of the model parameters.

[0119] According to an embodiment of the present invention, the further embodiment includes:

[0120] The multiple ratio of the bracket tangential force is determined according to the distance from the bracket node to the center line end point, and the bracket tangential force is adjusted.

[0121] It should be noted that the centerline end point is the first node corresponding to the stent node on the centerline of the first blood vessel. The distance from the stent node to the centerline end point is a multiple of the stent tangential force of the current stent node. The multiple ratio is set according to the clinical stent deployment length data. When the stent contracts, the force on the stent node is related to the distance from it to the centerline end point.

[0122] According to an embodiment of the present invention, the virtual support is iteratively expanded based on the motion trajectory and internal and external forces of the support node. When the internal and external forces of the support node reach a balanced state, the expansion of the support node in the direction perpendicular to the tangent is terminated accordingly, including:

[0123] Stent deployment includes two stages: the non-wall-touching stage and the wall-touching stage.

[0124] After each iterative expansion, the distance between the current position of the stent node and the position of the nearest Simplex grid node of the main tumor-bearing vessel before surgery is calculated;

[0125] When the distance is greater than or equal to the preset distance threshold, the expansion of the support node is in the stage of not touching the wall, and the support node expands outward under the action of internal force;

[0126] When the distance is less than the preset distance threshold, the expansion of the support node enters the wall-touching stage, and the support node expands outward under the combined action of internal and external forces;

[0127] When the internal and external forces are balanced, the stent node stops expanding.

[0128] It should be noted that in the non-touching the wall stage, the stent nodes only expand outward under the action of internal forces. It is necessary to calculate the distance between the current position of each stent node and the position of the nearest Simplex grid node of the main tumor-bearing vessel before surgery. When the distance is within the specified threshold, it is considered that the stent and the blood vessel wall are in contact. Among them, the preset distance threshold is set by those skilled in the art according to actual needs. After the stent node adheres to the wall, it enters the second stage (touching the wall stage). The stent node not only expands outward under the action of internal forces, but is also subject to the resistance of the blood vessel wall (external force). When the internal force and the external force are balanced, the stent expansion stops.

[0129] The implementation involves simulating the initial expansion of the stent node under the action of internal forces, calculating the distance between the stent node's current position and the previous iteration's position, and determining whether the stent node is in contact with the vessel wall. If so, external forces are introduced, and the second phase of simulation begins. The stent expansion process ends when the internal and external forces are balanced.

[0130] During the stent deployment phase, the actual mechanical environment of the stent within the blood vessel needs to be considered, including the dynamic effects of blood flow and the biomechanical properties of the blood vessel wall.

[0131] According to an embodiment of the present invention, the further embodiment includes:

[0132] The maximum and minimum values ​​of the distance between the nodes of the stent when the solid stent is only subjected to axial pressure and perpendicular to the axial pressure are set as the distance limit conditions between the nodes of the stent; the distance between the nodes of the stent includes the distance between the nodes of the stent wire and the distance between the nodes of the stent segment;

[0133] When the support nodes of the virtual support meet the distance restriction condition between the support nodes, it is determined that the support nodes reach the equilibrium position;

[0134] When all the stent nodes reach the equilibrium position, the final placement of the virtual stent is determined.

[0135] It should be noted that, based on the physical stent tensile test, the distance between the nodes of the physical stent under different pressure conditions (axial stretching and perpendicular to the axial stretching) is measured. The measured data is used as the constraint condition, the maximum and minimum distances between the stent nodes are set, and the constraint condition of the distance between the stent nodes is determined. The constraint condition of the distance between the stent nodes is introduced into the simulation, and the stent is simulated to reach the equilibrium position under the constraint condition to obtain the final implantation situation.

[0136] This step needs to ensure the rationality of the restriction conditions to avoid excessive expansion or compression of the stent during actual implantation.

[0137] According to an embodiment of the present invention, based on the preoperative three-dimensional model of the tumor-bearing main vessel and the three-dimensional model of the virtual stent, a fast algorithm based on the porosity of the neck arc of the virtual stent is used to calculate the efficacy evaluation parameters, including:

[0138] The evaluation parameters for efficacy assessment include at least the ratio of the arc surface clearance of the tumor neck;

[0139] The tumor neck plane is divided based on the preoperative 3D model of the main tumor-bearing vessel to obtain the contour position data of the tumor neck plane;

[0140] Calculate the intersection of the contour position data and the stent wire, and determine the node formed by the gap in the aneurysm neck arc after the stent wire is projected based on the preset stent wire diameter;

[0141] Calculate the sum of the polygonal areas formed by each node to determine the area of ​​the arc surface gap at the neck of the tumor;

[0142] The closed surface is generated by forming nodes through the gaps in the tumor neck arc surface, and the area of ​​the closed surface is calculated to obtain the area of ​​the tumor neck arc surface;

[0143] Based on the fast algorithm of the virtual stent neck arc surface porosity, the neck arc surface porosity is calculated by the neck arc surface porosity area and the neck arc surface area;

[0144] The fast algorithm for the porosity of the virtual stent neck arc surface is expressed as follows:

[0145] ;

[0146] Among them, K is the porosity of the tumor neck arc surface, S1 is the area of ​​the tumor neck arc surface, and S2 is the porosity area of ​​the tumor neck arc surface.

[0147] It should be noted that if Figure 7 As shown, based on the preoperative three-dimensional model of the tumor-bearing main vessel, the tumor neck plane is divided and its contour position data is obtained. The contour position data is imported into the virtual stent three-dimensional model for analysis, and the intersection point of the contour position data and the stent wire of the virtual stent is calculated. Combined with the preset stent wire diameter, the node of the tumor neck arc surface gap after the stent wire is projected is calculated. The porosity of the tumor neck arc surface is calculated using the virtual stent neck arc surface porosity fast algorithm. Among them, the closed surface is the total area of ​​the tumor neck arc surface, and the initial value of the preset stent wire diameter is 0.02mm. Those skilled in the art can adjust it according to actual needs.

[0148] The coverage effect of the stent in the tumor neck area is evaluated by the porosity of the virtual stent neck arc surface, thereby judging the success rate and risk of the operation.

[0149] The information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals (including but not limited to signals transmitted between user terminals and other devices, etc.) involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the "clinical imaging data" involved in this disclosure were all obtained with full authorization.

[0150] The present invention discloses a method for simulating aneurysm virtual stent implantation based on a spring analogy method. The method comprises: reconstructing a three-dimensional model of the preoperative parent vessel and the parent vessel after aneurysm restoration based on clinical imaging data; extracting the centerline of the first vessel to construct a virtual stent initialization model; deploying the virtual stent initialization model using a spring analogy virtual stent fast algorithm to determine the virtual stent three-dimensional model; and calculating efficacy evaluation parameters using a fast algorithm based on the arc surface porosity of the virtual stent neck. This method can simulate the actual motion of stent deployment and significantly shorten the simulation calculation time and efficacy evaluation time of simulated stent deployment within a vessel, thus enabling real-time guidance during virtual aneurysm intervention.

[0151] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0152] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0153] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0154] Those skilled in the art will appreciate that all or part of the steps of the above-mentioned method embodiments may be implemented by hardware associated with program instructions, and the aforementioned program may be stored in a computer-readable storage medium. When the program is executed, the program executes the steps of the above-mentioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0155] Alternatively, if the integrated units described above are implemented as software modules and sold or used as standalone products, they can also be stored on a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product, stored on a storage medium, includes instructions for enabling a computer device (such as a personal computer, server, or network device) to execute all or part of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as removable storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. A method for simulating aneurysm virtual stent implantation based on spring analogy, characterized in that: include: Acquisition of clinical imaging data; The clinical imaging data at least includes the patient's preoperative vascular imaging data; Reconstructing a three-dimensional model of the preoperative parent vessel and the mother vessel after aneurysm reduction based on analysis of the clinical imaging data; the three-dimensional model of the preoperative parent vessel and the mother vessel after aneurysm reduction includes a three-dimensional model of the preoperative parent vessel and a three-dimensional model of the mother vessel after aneurysm reduction; extracting the centerline of the first blood vessel through the three-dimensional model of the parent blood vessel after the aneurysm is restored; Constructing a virtual stent initialization model based on the centerline of the first blood vessel; Based on a fast algorithm of a spring analogy virtual support, the virtual support initialization model is expanded to determine a three-dimensional model of the virtual support; Analyze the preoperative three-dimensional model of the tumor-bearing main vessel and the three-dimensional model of the virtual stent, and calculate the efficacy evaluation parameters by a fast algorithm based on the arc surface porosity of the virtual stent neck; The constructing of a virtual stent initialization model based on the first blood vessel centerline includes: Determine a plurality of first nodes on the centerline of the first blood vessel; the number of the first nodes is determined according to the curvature of the stent wire; Analyzing the centerline of the first blood vessel to determine the tangent direction of each first node on the centerline of the first blood vessel; Make a circle with a preset initial radius and perpendicular to the corresponding tangent direction with each first node as the center; Determine the number of second nodes on each circle based on the total number of stent filaments of the virtual stent, and uniformly discretize the second nodes on each circle; the number of the second nodes is determined according to the number of stent filaments; A virtual support initialization model is constructed by performing forward and reverse spiral sorting on the second nodes on the adjacent circles, and the second nodes are determined as support nodes; Converting the diamond mesh of the virtual support initialization model into a Simplex mesh; The spring analogy-based virtual support fast algorithm expands the virtual support initialization model to determine the virtual support three-dimensional model, including: The expansion force of the stent itself is defined as the internal force, and the resistance encountered by the stent when it expands and contacts the inner wall of the blood vessel is defined as the external force; The stent nodes are assumed to be point masses that follow the laws of physics, and the point masses of the stent nodes are set. The weighting factors of the internal and external forces are obtained through tensile tests of the stent and intracranial vascular tissue. The weighting factors of the internal and external forces are used to determine the ratio of the internal and external forces acting on the stent nodes. Iteratively expand the virtual support based on the motion trajectory and internal and external forces of the support node. When the internal and external forces of the support node reach a balanced state, the expansion of the support node in the direction perpendicular to the tangent is terminated accordingly. The stent deployment is assumed to be the overall movement of multiple springs of the same material and model with positive and negative helices. Through mechanical analysis of the physical stent, the torque and axial force acting on a single stent wire are determined. The stent is compared to a spring to conduct spring mechanical property experiments on the stent and a single stent wire, and the bending moment and torque of the microelement stent wire are calculated using the microelement method. Applying the bending moment and torque of the microelement stent wire to the stent nodes of the virtual stent in the form of force to determine the stent tangential force; The virtual stent is unfolded by the internal and external forces perpendicular to the tangential direction and the tangential force of the stent analogous to the spring, and the three-dimensional model of the virtual stent is determined.

2. The aneurysm virtual stent implantation simulation method based on spring analogy according to claim 1, characterized in that: The analysis based on the clinical imaging data to reconstruct a three-dimensional model of the preoperative parent vessel and the parent vessel after aneurysm reduction includes: By analyzing the clinical imaging data, a three-dimensional model of the main tumor-bearing vessels before surgery is reconstructed; preprocessing the preoperative three-dimensional model of the tumor-bearing main blood vessel; generating a second vessel centerline based on a preprocessed preoperative three-dimensional model of the parent vessel, truncating the parent vessels at both ends of the aneurysm in the preprocessed preoperative three-dimensional model of the parent vessel, fitting a centerline segment of the aneurysm region based on the second vessel centerlines of the parent vessels at both ends of the aneurysm, and performing discretization on the centerline segment; Obtain the lumen contour of the parent vessel end close to the aneurysm; The lumen contour is fitted and transitioned by discrete points obtained through discretization processing to obtain a three-dimensional model of the parent blood vessel after aneurysm restoration.

3. The aneurysm virtual stent implantation simulation method based on spring analogy according to claim 2, characterized in that: The pre-processing of the three-dimensional model of the tumor-bearing main blood vessel before surgery includes: Reconstructing the mesh of the preoperative three-dimensional model of the tumor-bearing main blood vessel; The triangular mesh of the reconstructed preoperative tumor-bearing main vessel 3D model was converted into a Simplex mesh.

4. The aneurysm virtual stent implantation simulation method based on spring analogy according to claim 1, characterized in that: Also includes: The multiple ratio of the bracket tangential force is determined according to the distance from the bracket node to the center line end point, and the bracket tangential force is adjusted.

5. The aneurysm virtual stent implantation simulation method based on spring analogy according to claim 1, characterized in that: The iterative expansion of the virtual support based on the motion trajectory and internal and external forces of the support node, when the internal and external forces of the support node reach a balanced state, the expansion of the support node in the direction perpendicular to the tangent is terminated accordingly, including: Stent deployment includes two stages, namely, a non-wall-touching stage and a wall-touching stage. After each iterative expansion, the distance between the current position of the stent node and the position of the nearest Simplex grid node of the main tumor-bearing vessel before surgery is calculated; When the distance is greater than or equal to a preset distance threshold, the expansion of the support node is in a non-wall contact stage, and the support node expands outwards under the action of internal force; When the distance is less than a preset distance threshold, the expansion of the support node enters the wall-touching stage, and the support node expands outward under the combined action of internal and external forces; When the internal force is balanced with the external force, the stent node stops expanding.

6. The aneurysm virtual stent implantation simulation method based on spring analogy according to claim 1, characterized in that: Also includes: The maximum and minimum values ​​of the distance between the nodes of the stent when the solid stent is only subjected to axial pressure and perpendicular to the axial pressure are set as the distance limit conditions between the nodes of the stent; the distance between the nodes of the stent includes the distance between the nodes of the stent wire and the distance between the nodes of the stent segment; When the support nodes of the virtual support meet the distance restriction condition between the support nodes, determining that the support nodes reach the equilibrium position; When all the stent nodes reach the equilibrium position, the final placement of the virtual stent is determined.

7. The aneurysm virtual stent implantation simulation method based on spring analogy according to claim 1, characterized in that: The analysis is performed based on the preoperative three-dimensional model of the tumor-bearing main vessel and the three-dimensional model of the virtual stent, and the efficacy evaluation parameters are calculated by a fast algorithm based on the arc surface porosity of the virtual stent neck, including: The efficacy evaluation parameters include at least the neck arc surface porosity; Dividing the tumor neck plane based on the preoperative three-dimensional model of the tumor-bearing main blood vessel and obtaining contour position data of the tumor neck plane; Calculating the intersection of the contour position data and the stent wire, and determining the node formed by the gap between the arc surface of the tumor neck after the stent wire is projected based on the preset stent wire diameter; Calculate the sum of the polygonal areas formed by each node to determine the area of ​​the arc surface gap at the neck of the tumor; The closed surface is generated by forming nodes through the gaps in the tumor neck arc surface, and the area of ​​the closed surface is calculated to obtain the area of ​​the tumor neck arc surface; Based on the virtual stent neck arc surface porosity fast algorithm, the neck arc surface porosity is calculated by the neck arc surface porosity area and the neck arc surface area; The fast algorithm for the porosity of the virtual stent neck arc surface is expressed as follows: ； Among them, K is the porosity of the tumor neck arc surface, S1 is the area of ​​the tumor neck arc surface, and S2 is the porosity area of ​​the tumor neck arc surface.

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