Knee joint acl biomechanics simulation method, device and equipment based on facet model

Abstract

The application discloses a knee joint ACL biomechanics simulation method, device and equipment based on a facet model, which comprises the following steps: acquiring three-dimensional image original data of bone tissue in a knee joint of a target individual, reconstructing a bone tissue digital model, and performing finite element analysis to obtain an operable target knee joint digital model; selecting a group of corresponding points on the medial surface of the femoral condyle and the tibial condyle fossa of the model respectively, inserting intermediate points between the corresponding point sets, and generating a B-Spline surface of a double-variable tensor according to the grid points corresponding to the anterior medial bundle and the posterior lateral bundle to obtain a facet model of the anterior cruciate ligament of the knee joint and perform ligament material parameter optimization. The B-Spline surface is used as the facet model, the order of the B-Spline is determined, and the B-Spline has good smoothness, so that the complexity of calculation is low and the convergence is good. Compared with the line segment model, the facet model has more actual material characteristics.

Description

Technical Field

[0001] This invention belongs to the technical field of knee joint ACL, and particularly relates to a biomechanical simulation method, device and equipment for knee joint ACL based on patch model. Background Technology

[0002] The anterior cruciate ligament (ACL) is a crucial structure for stabilizing the knee joint. It is susceptible to injury under rapid changes in stress and can be repaired through ACL reconstruction. However, improper graft length leading to joint tightness or instability can cause postoperative complications such as articular cartilage damage or graft tearing. To reduce postoperative complications and improve treatment efficiency in ACL reconstruction, a more precise understanding of the ACL's biomechanical behavior is needed. Individualized ACL simulation numerical models can serve as a means of quantifying individual ligament function in vivo. Besides aiding in understanding individual characteristics, they can also help physicians select appropriate ACL surgical plans for patients requiring ACL reconstruction.

[0003] Currently, there are two commonly used models of the anterior cruciate ligament: the first is the volume model, and the second is the line segment model.

[0004] The volumetric model of a ligament is a three-dimensional ligament model. This ligament model is usually obtained using CT and MRI scans. Taking this cited paper as an example ([1] Zhao Yang. Finite element analysis of tunnel position assessment and graft stress after anterior cruciate ligament reconstruction based on dual-source CT [D]. Fourth Military Medical University, 2015.), the original data images of the anterior cruciate ligament were first obtained by dual-source CT tomography, and then reconstructed to obtain a three-dimensional digital model of the anterior cruciate ligament. The volumetric model reference figure is shown in the figure. Figure 1 .

[0005] The line segment model can be found in this paper ([2] F Péan, Goksel O. Surface-based Modeling of Muscles: Functional Simulation of the Shoulder[J]. Medical Engineering & Physics, 2020, 82.). This is a convenient and simple model that obtains line segments by defining pairs of points and uses the obtained line segments as ligament fiber elements to form a ligament model. The reference figure for the line segment model is shown in [Figure number missing]. Figure 2 .

[0006] The establishment of volumetric models has many drawbacks because it requires the use of ligament imaging scan data: (1) CT can obtain accurate bone models, but it is not sensitive to soft tissues such as ligaments. Therefore, when constructing a volumetric model, it is necessary to combine CT and MRI scanning imaging results. However, the imaging results of soft tissues are not only difficult to distinguish, but also lack precision. Therefore, the accuracy of the volumetric model is not high.

[0007] (2) Volumetric models require a large number of meshes in finite element software, and the high deformability of ligament soft tissues leads to high computational complexity. However, due to the low accuracy of the model itself, high-complexity calculations often fail to yield accurate results.

[0008] Line segment models suffer from insufficient geometric constraints (they often only capture radial forces, being insensitive to forces in the normal direction) and fail to reflect the anisotropy of ligament fibers. This results in line segment models often failing to accurately simulate the viscoelastic and mechanical properties of ACLs, deviating from some actual ACL characteristics. To correct these model biases, lateral line segment constraints are introduced to impose additional limitations on the model. A reference diagram is provided to illustrate this constraint process more clearly. Figure 3 However, the increased complexity brought about by this correction has created more trouble for model building, such as how many lateral constraint segments are needed, how to choose the direction of the constraints, etc., making it not worth the effort. Summary of the Invention

[0009] The purpose of this invention is to provide a biomechanical simulation method, device, and equipment for the anterior cruciate ligament (ACL) based on a patch model. By using a patch model to model the ACL, the defects of line segment models and volume models are overcome, and the viscoelastic physiological and material properties of the ACL are better simulated, thereby improving the accuracy of ACL modeling and providing better ACL surgical treatment options.

[0010] To solve the above problems, the technical solution of the present invention is as follows:

[0011] A biomechanical simulation method for the knee joint ACL based on a patch model includes:

[0012] Obtain raw three-dimensional image data of bone tissue in the knee joint of the target individual;

[0013] Based on the original 3D image data, a digital model of bone tissue is reconstructed using 3D reconstruction software to form a digital model of the target knee joint.

[0014] Finite element analysis was performed on the target knee joint digital model to obtain an operable target knee joint digital model. A set of corresponding points were selected on the medial surface of the lateral femoral condyle and the anterior tibial condyle fossa of the target knee joint digital model. Intermediate points were inserted between the corresponding point sets. Based on the grid points corresponding to the anteromedial and posterolateral bundles, a bivariate tensor B-Splines surface was generated to obtain the anterior cruciate ligament model of the knee joint.

[0015] The ligament material parameters of the anterior cruciate ligament model of the knee joint were optimized.

[0016] According to an embodiment of the present invention, the step of selecting a set of corresponding points on the medial surface of the lateral femoral condyle and the anterior tibial condyle fossa of the target knee joint digital model, and inserting intermediate points between the corresponding point sets, further includes:

[0017] Determine the origin and insertion points of the ACL (achondrial artery ligament) in the bone model of the target knee joint digital model, and select a set of corresponding points at each ACL origin and insertion point to obtain two point sets p. ori and p ins The midpoint interval r of the corresponding points is determined by the following formula:

[0018]

[0019]

[0020]

[0021] Where i is the i-th point in the point set, and n is the number of points in the point set;

[0022] Insert a midpoint based on the midpoint interval r.

[0023] According to an embodiment of the present invention, the B-Splines surface for generating bivariate tensors further includes:

[0024] The B-Splines surface S(u,v) of the bivariate tensor is generated using the following formula:

[0025]

[0026] in, and These are the two B-Spline base points of the B-Spline surface, P i，j It is a set of m×n control points, where m and n represent the scale of the entire ligament mesh.

[0027] According to one embodiment of the present invention, a force is applied to each control point of the B-Splines surface, and the force is along the direction of the normal vector of the bone model section at each point, so that the B-Splines surface is separated from the bone model, thereby obtaining a patch model of the anterior cruciate ligament of the knee joint.

[0028] According to one embodiment of the present invention, the femur, tibia and ligament in the facet model are respectively divided into volume meshes, and mesh sensitivity analysis is performed to determine the mesh type and mesh division degree in order to optimize the ligament material parameters of the facet model.

[0029] According to an embodiment of the present invention, the optimization of ligament material parameters for the anterior cruciate ligament model of the knee joint further includes:

[0030] A multi-angle drawer test was performed on the current in vivo knee joint to obtain the tension (Ten) of the ACL. Experiment ;

[0031] Preset ligament material parameters were input into the anterior cruciate ligament (ACL) model of the knee joint, and the same motion as the drawer test was performed to calculate the simulated ACL tension (Ten). Model The ligament material parameters include the ligament reference length, elastic coefficient, and strain constant.

[0032] Comparison Ten Model with Ten Experiment Based on the comparison results, the ligament material parameters were iterated until the entire drawer test was moved, Ten Model with Ten Experiment The motion tension curves are consistent, thus obtaining the target ligament material parameters;

[0033] Input the target ligament material parameters into the patch model of the anterior cruciate ligament of the knee joint.

[0034] A biomechanical simulation device for the knee joint ACL based on a patch model includes:

[0035] The data acquisition module is used to acquire raw three-dimensional image data of bone tissue in the knee joint of the target individual.

[0036] The knee joint modeling module is used to reconstruct a digital model of bone tissue based on the original 3D image data using 3D reconstruction software, thereby forming a digital model of the target knee joint.

[0037] The patch simulation module is used to perform finite element analysis on the target knee joint digital model to obtain an operable target knee joint digital model. A set of corresponding points are selected on the medial surface of the lateral femoral condyle and the anterior tibial condyle fossa of the target knee joint digital model, and intermediate points are inserted between the corresponding point sets. Based on the mesh points corresponding to the anteromedial and posterolateral bundles, a bivariate tensor B-Splines surface is generated to obtain the anterior cruciate ligament model of the knee joint.

[0038] The optimization module is used to optimize the ligament material parameters of the anterior cruciate ligament model of the knee joint.

[0039] A patch-model-based knee joint ACL biomechanical simulation device includes a memory and a processor. The memory stores computer-readable instructions, which, when executed by the processor, cause the processor to perform steps in the patch-model-based knee joint ACL biomechanical simulation method according to an embodiment of the present invention.

[0040] A storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform steps in a patch model-based knee joint ACL biomechanical simulation method according to an embodiment of the present invention.

[0041] Because the present invention adopts the above technical solution, it has the following advantages and positive effects compared with the prior art:

[0042] This invention discloses a patch-based biomechanical simulation method for the anterior cruciate ligament (ACL) of the knee joint. The method involves acquiring raw three-dimensional images of bone tissue in the knee joint of a target individual; reconstructing a digital model of the bone tissue using three-dimensional reconstruction software based on the raw three-dimensional images to form a digital model of the target knee joint; performing finite element analysis on the target knee joint digital model to obtain an operable model; selecting a set of corresponding points on the medial surface of the lateral femoral condyle and the anterior tibial condyle fossa of the target knee joint digital model, inserting intermediate points between the corresponding point sets, and generating a bivariate tensor B-Spline surface based on the mesh points corresponding to the anteromedial and posterolateral bundles to obtain a patch model of the ACL; and optimizing the ligament material parameters of the patch model. Using a patch model for ACL modeling effectively avoids the defects caused by imaging in volumetric models. Using a B-Spline surface as the patch model, due to the fixed order of the B-Spline and its excellent smoothness, results in lower computational complexity and better convergence, thus overcoming the problem of high computational complexity in volumetric models. Compared to line segment models, patch models have more realistic material properties and can be automatically generated using only the start and end points of the ligament, resulting in faster model generation. Attached Figure Description

[0043] Figure 1 A schematic diagram of the existing ACL volume model;

[0044] Figure 2 A schematic diagram of the existing ACL line segment model;

[0045] Figure 3 A schematic diagram of constraints added to an existing ACL segment model;

[0046] Figure 4 This is a flowchart of a biomechanical simulation method for knee joint ACL based on a patch model according to one embodiment of the present invention;

[0047] Figure 5 This is a CT scan image of the knee joint in one embodiment of the present invention;

[0048] Figure 6 This is an MRI scan image of the knee joint in one embodiment of the present invention;

[0049] Figure 7 This is a schematic diagram of finite element analysis of a target knee joint digital model in one embodiment of the present invention;

[0050] Figure 8 This is a schematic diagram illustrating the selection of the ACL start and end points in one embodiment of the present invention;

[0051] Figure 9 This is a schematic diagram of a patch model in one embodiment of the present invention;

[0052] Figure 10 This is a schematic diagram illustrating the separation of the facet model and the bone model in one embodiment of the present invention;

[0053] Figure 11 This is a block diagram of a knee joint ACL biomechanical simulation device based on a patch model according to an embodiment of the present invention.

[0054] Figure 12 This is a schematic diagram of a knee joint ACL biomechanical simulation device based on a patch model according to an embodiment of the present invention. Detailed Implementation

[0055] The following detailed description, in conjunction with the accompanying drawings and specific embodiments, provides a method, apparatus, and device for biomechanical simulation of the knee joint ACL based on a patch model, as proposed in this invention. The advantages and features of this invention will become clearer from the following description and claims.

[0056] Example 1

[0057] This embodiment addresses the problems of low accuracy and difficulty in accurately simulating the viscoelastic and mechanical properties of the ACL in existing ACL models. It provides a patch-based biomechanical simulation method for the knee ACL, effectively avoiding the limitations of volumetric models due to imaging limitations. Using a B-spline surface as the patch model, the computational complexity is lower and convergence is better due to the fixed order and smoothness of the B-spline, thus overcoming the high computational complexity of volumetric models. Compared to line segment models, patch models more closely reflect actual material properties and can be automatically generated using only the ligament's origin and insertion points, resulting in faster model generation.

[0058] Please refer to Figure 4 This biomechanical simulation method for the knee joint ACL based on patch models includes:

[0059] S1: Obtain raw three-dimensional image data of bone tissue in the knee joint of the target individual;

[0060] S2: Based on the original 3D image data, a digital model of bone tissue is reconstructed using 3D reconstruction software to form a digital model of the target knee joint;

[0061] S3: Perform finite element analysis on the target knee joint digital model to obtain an operable target knee joint digital model; select a set of corresponding points on the medial surface of the lateral femoral condyle and the anterior tibial condyle fossa of the target knee joint digital model, insert intermediate points between the corresponding point sets, and generate a bivariate tensor B-Splines surface based on the grid points corresponding to the anteromedial and posterolateral bundles to obtain the anterior cruciate ligament model of the knee joint;

[0062] S4: Optimize the ligament material parameters of the anterior cruciate ligament model of the knee joint.

[0063] Specifically, in step S1, CT and MRI scans are used to obtain raw three-dimensional images of the bone tissue in the knee joint of the target individual. Please refer to [link / reference]. Figure 5 and Figure 6 After acquiring the raw 3D image data of the target knee joint bone tissue, it is transferred to the computer used for modeling in DICOM format.

[0064] In step S2, based on the original 3D image data, 3D reconstruction software is used to reconstruct digital models of the bone tissue, forming a digital model of the target knee joint. In this step, the 3D reconstruction software can be Amira, but is not limited to Amira. Since a patch model will be used to automatically generate the digital model of the target knee joint's anterior cruciate ligament, the digital model here only needs to include the bone tissue model.

[0065] In step S3, a finite element analysis is performed on the target knee joint digital model. Please refer to [link / reference]. Figure 7 This yields an operable digital model of the target knee joint.

[0066] Select a set of corresponding points on the medial surface of the lateral femoral condyle and the anterior tibial condyle fossa of the target knee joint digital model (if the anteromedial and posterolateral bundles need to be constructed separately, two sets of corresponding points need to be selected here). The selection of the corresponding point set can be referred to Figure 8 Next, intermediate points are inserted between the corresponding point sets, and a bivariate tensor B-Splines surface is generated for the mesh points corresponding to the anterior medial and posterolateral bundles. Since the obtained surface may intersect and overlap with the skeleton, some constraints need to be added to the surface. The resulting patch model is the required anterior cruciate ligament model. The detailed operation and principle are as follows:

[0067] 1. In modeling and simulation, B-splines are used to represent the anterior cruciate ligament (ACL). B-splines are a generalization of Bézier curves and are linear combinations of B-spline basis functions. The B-spline basis functions are subdivided into many nodal intervals on their domain, and the degree of the basis function can be arbitrarily given. The basis function has different expressions in different intervals. Let the degree of the basis function be k, and the i-th k-th degree B-spline basis function be Bi. i,k (u).

[0068] The Cox-de-Boor recursive formula is defined as follows:

[0069]

[0070]

[0071] After obtaining the basis function expression, the following equation is used:

[0072]

[0073] The equation of the B-Splines curve can then be obtained, where P i These are weighted values.

[0074] 2. Using CT and MRI scans, the origin and insertion points of the ligaments on the bone can be identified. Two sets of corresponding points at the origin and insertion points are selected as the origin and insertion points of the patch model (note that the number of origin and insertion points should be the same). The selection of the two sets of corresponding points can refer to... Figure 8 Let them be defined as p respectively. ori and p ins Between these two sets of points, some intermediate points need to be inserted. The distance r between the intermediate points of each pair of corresponding points is different, and the formal definition of r is as follows:

[0075]

[0076]

[0077]

[0078] This definition ensures that the control point mesh of the surface remains nearly uniform.

[0079] 3. For the patch model, for each point on the surface, we need to know not only its tangent normal vector but also the forces acting on it. Therefore, a second-order tensor model is required. Thus, a bivariate tensor B-Splines surface is needed. To achieve this, we need to extend the B-Splines curve. A B-Splines surface consists of two B-Splines base points. and The parameter space generated by the tensor product is defined. Here, the patch surface S(u,v) is given by the following formula:

[0080]

[0081] Among them, P i，j It is a set of m×n control points, where m and n represent the scale of the entire ligament grid.

[0082] 4. By selecting the corresponding point set and the intermediate points generated above, and adding the surface expression, a preliminary patch model can be generated in the finite element software ABAQUS. (Refer to the illustration.) Figure 9 .

[0083] 5. The surface generated in this way alone is insufficient because the patch model may overlap with the skeleton. Further constraints need to be added to the patch model. Here, a simple operation is used for static simulation of the ligaments and skeleton: a force is applied to each control point of the patch model, along the direction of the normal vector of the skeleton model's cross-section, causing the patch model to move away from the skeleton. A schematic diagram of this process is shown below. Figure 10 After the patch model is completely separated from the skeletal model (except for the corresponding point set selected on the skeleton), the artificial external force is gradually removed, while the contact constraints between the bone surface and the muscle surface are enforced until the entire model reaches equilibrium. This generates the required ACL patch model.

[0084] Generally, Bézier curves are used instead of B-splines to create patch models. Like B-splines, the shape of a Bézier curve is determined by control points. However, unlike B-splines, the order of a Bézier curve cannot be definitively determined; that is, n+1 control points correspond to an nth-order Bézier curve, whose parametric equation is:

[0085]

[0086] Where P i It is one of the (n+1) vertices of the control polygon (a polygon composed of control points), B i,n (t) is called the Bernstein basis function. Since Bézier curves do not require piecewise fitting, using them saves a lot of time in model building. Furthermore, the geometric properties of the curve do not change with coordinates, and their smoothness is superior to B-Spline. However, in this embodiment, Bézier splines are not used. Because the ligament model serves the scenario of ligament changes during knee joint movement, the model must not overlap with the bone model; that is, the model is a ligament model based on the bone surface. To achieve this, some adjustments need to be made to the surface control points, which is the process described in point 5: moving the patch model away from the bone before removing the constraints on the ligament and bone. Because Bézier splines are global fitting (which makes local modifications impossible), each adjustment to the control points requires recalculation of the entire surface, causing significant modeling difficulties. B-Spline, on the other hand, is a local piecewise fitting; each adjustment to the control points only requires recalculation of a portion of the low-order curves, greatly reducing the workload during modeling. Meanwhile, the fact that the B-Spline curve can determine the order allows for better convergence results in subsequent model-based computational studies.

[0087] For the reasons mentioned above, this embodiment improves the existing patch model by using B-Spline curves instead of Bézier curves. Although this sacrifices some surface smoothness, it results in faster model building speed (although Bézier curves are superior to B-Spline curves in curve calculation, B-Spline curves are far superior to Bézier curves in subsequent control point adjustments) and better convergence of calculation results.

[0088] In step S4, after obtaining the required patch model, volume meshes are generated for the femur, tibia, and ligaments in the patch model, and mesh sensitivity analysis is performed to select appropriate mesh types and meshing levels. A multi-angle drawer test is then conducted on the in vivo knee joint to obtain the ACL tension (Ten). ExperimentNext, the material properties were given by reference values ​​in the literature (Zhang Yuanying, Wang Xuehui, Ying Hongliang, et al. Experimental study on viscoelastic properties of anterior cruciate ligament [J]. Chinese Journal of Biomedical Engineering, 2007, 26(2):5.) in the knee joint model. The material parameters were changed and the same motion as measured in the previous in vivo knee joint drawer test was set to calculate and obtain the simulation results of ACL tension Ten. Model .

[0089] Comparison Ten Model with Ten Experiment Based on the comparison results, the material parameters are iterated until the entire drawer experiment is moved, Ten Model with Ten Experiment The material parameters are consistent with the motion tension curve, and these are the optimal values ​​required. These are then used as the material parameters for the individualized ligament. The ligament reference length, elastic coefficient, and strain constant from these individualized ligament material parameters are imported into the ACL patch model in the finite element software ABAQUS.

[0090] The knee joint ACL biomechanical simulation method based on patch models provided in this embodiment uses patch models to model the anterior cruciate ligament, overcoming many shortcomings of line segment models and volumetric models. For example, although soft tissue obtained directly from CT and MRI scans is difficult to segment and lacks precision, for soft tissues like ligaments, the combined results of CT and MRI scans can accurately identify their origin and insertion points (CT can obtain a precise skeletal model, and the origin and insertion points of ligaments can be found through anatomical markers; while MRI can directly visualize the ligaments, and the origin and insertion points can be clearly identified through imaging results). Patch models precisely require the origin and insertion points of ligaments. Therefore, while using MRI and CT scan results, patch models effectively avoid the shortcomings of volumetric models caused by imaging limitations.

[0091] The patch model used in this embodiment is a B-Spline surface. Since the order of a B-Spline is fixed and it has good smoothness, the computational complexity is low and the convergence is good. This also overcomes the problem of high computational complexity of the volume model.

[0092] Compared to line segment models, patch models more closely resemble actual material properties (patch models can easily represent the anisotropy of materials, while line segment models require complex lateral constraints to represent the directionality of materials). Moreover, like line segment models, patch models can be automatically generated using only the start and end points of the ligament, resulting in faster model generation.

[0093] Ligaments are passive structures. Studies on the characteristics of the ACL (ligaments, tendons, and joints) typically involve placing them alongside a knee joint skeletal model. Changes in the ligaments during knee joint movement are measured and calculated to study ACL properties. However, different individuals have different skeletal morphologies, which also influence ligament changes during joint movement. Therefore, to obtain a more accurate experimental structure when studying ligament movement characteristics, a ligament patch model based on the bone surface is required, which is impossible with simple line segment models. Based on existing literature (Hoffmann, Marion, Haering, et al. Comparison between line and surface mesh models to represent the rotatorcuff muscle geometry in musculoskeletal models) demonstrating that patch models better reflect the various physiological and material properties of limb muscles than line models, and considering that both ligaments and limb muscles are soft tissues originating and inserting into bones and whose movement is influenced by bone morphology, bone surface models can achieve more accurate results. Therefore, ACL patch models can better simulate the viscoelastic physiological and material properties of the ACL, and show better performance in simulating the degree of ligament tearing under extreme conditions.

[0094] Example 2

[0095] This embodiment provides a patch-model-based knee joint ACL biomechanical simulation device to implement the patch-model-based knee joint ACL biomechanical simulation method in Embodiment 1. Please refer to... Figure 11 The knee joint ACL biomechanical simulation device based on patch model includes:

[0096] Data acquisition module 1 is used to acquire raw three-dimensional image data of bone tissue in the knee joint of the target individual;

[0097] Knee joint modeling module 2 is used to reconstruct a digital model of bone tissue based on the original three-dimensional image data using three-dimensional reconstruction software, thereby forming a target knee joint digital model;

[0098] The patch simulation module 3 is used to perform finite element analysis on the target knee joint digital model to obtain an operable target knee joint digital model. A set of corresponding points are selected on the medial surface of the lateral femoral condyle and the anterior tibial condyle fossa of the target knee joint digital model, and intermediate points are inserted between the corresponding point sets. Based on the mesh points corresponding to the anteromedial bundle and the posterolateral bundle, a bivariate tensor B-Splines surface is generated to obtain the anterior cruciate ligament model of the knee joint.

[0099] Optimization module 4 is used to optimize the ligament material parameters of the anterior cruciate ligament model of the knee joint.

[0100] The functions and implementation methods of the above-mentioned data acquisition module 1, knee joint modeling module 2, patch simulation module 3 and optimization module 4 are as described in Embodiment 1, and will not be repeated here.

[0101] Example 3

[0102] This embodiment provides a biomechanical simulation device for the knee joint ACL based on a patch model. Please refer to [link / reference]. Figure 12 The patch-model-based knee joint ACL biomechanical simulation device 500 can vary considerably depending on its configuration or performance. It may include one or more central processing units (CPUs) 510 (e.g., x86, ARM architecture processors, or FPGAs) and memory 520, and one or more storage media 530 (e.g., one or more mass storage devices) for storing application programs 533 or data 532. The memory 520 and storage media 530 can be temporary or persistent storage. The program stored in the storage media 530 may include one or more modules (not shown in the figure), each module including a series of instruction operations on the patch-model-based knee joint ACL biomechanical simulation device 500.

[0103] Furthermore, the processor 510 can be configured to communicate with the storage medium 530 and execute a series of instructions in the storage medium 530 on the patch model-based knee joint ACL biomechanical simulation device 500.

[0104] The knee joint ACL biomechanical simulation device 500 based on patch model may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input / output interfaces 560, and / or one or more operating systems 531, such as Windows Server, Vista, etc.

[0105] Those skilled in the art will understand that Figure 12 The structure of the patch model-based knee joint ACL biomechanical simulation device shown does not constitute a limitation on the patch model-based knee joint ACL biomechanical simulation device, which may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0106] Another embodiment of the present invention also provides a computer-readable storage medium.

[0107] The computer-readable storage medium can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of the method for a knee joint ACL biomechanical simulation device based on a patch model in Embodiment 1.

[0108] If the knee joint ACL biomechanical simulation method based on patch models is implemented in the form of program instructions and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in software form. This computer software is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0109] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific identification content executed by the system and device described above can be referred to the corresponding process in the foregoing method embodiments.

[0110] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments. Even if various changes are made to the present invention, if these changes fall within the scope of the claims of the present invention and their equivalents, they shall still fall within the protection scope of the present invention.

Claims

1. A biomechanical simulation method for the knee joint ACL based on a patch model, characterized in that, include: Obtain raw three-dimensional image data of bone tissue in the knee joint of the target individual; Based on the original 3D image data, a digital model of bone tissue is reconstructed using 3D reconstruction software to form a digital model of the target knee joint. Finite element analysis was performed on the target knee joint digital model to obtain an operable target knee joint digital model. A set of corresponding points was selected on the medial surface of the lateral femoral condyle and the anterior tibial condyle fossa of the target knee joint digital model. Intermediate points were inserted between the corresponding point sets, and bivariate tensors were generated based on the mesh points corresponding to the anteromedial and posterolateral bundles. The curved surface is used to obtain a model of the anterior cruciate ligament of the knee joint; Optimize the ligament material parameters of the anterior cruciate ligament model of the knee joint; The step of selecting a set of corresponding points on the medial surface of the lateral femoral condyle and the anterior tibial condyle fossa of the target knee joint digital model, and inserting intermediate points between the corresponding point sets, further includes: Determine the origin and insertion points of the ACL (achondrial artery ligament) in the bone model of the target knee joint digital model, and select a set of corresponding points at each ACL origin and insertion point to obtain two sets of points. and The midpoint interval r of the corresponding points is determined by the following formula: Where i is the i-th point in the point set, and n is the number of points in the point set; Insert intermediate points based on the intermediate point interval r; right A force is applied to each control point of the curved surface, and the force is along the direction of the normal vector of the bone model section at each point, so that... The curved surface is separated from the bone model to obtain a patch model of the anterior cruciate ligament of the knee joint; Further optimization of ligament material parameters in the anterior cruciate ligament model of the knee joint includes: A multi-angle drawer test was performed on the current in vivo knee joint to obtain the ACL tension. ; Preset ligament material parameters were input into the anterior cruciate ligament (ACL) model of the knee joint, and the same motion as the drawer test was performed to calculate the simulation results of ACL tension. The ligament material parameters include the ligament reference length, elastic coefficient, and strain constant. Compare and Based on the comparison results, the ligament material parameters are iterated until the entire drawer test is moved. and The motion tension curves are consistent, thus obtaining the target ligament material parameters; Input the target ligament material parameters into the patch model of the anterior cruciate ligament of the knee joint.

2. The knee joint ACL biomechanical simulation method based on patch model as described in claim 1, characterized in that, The generation of bivariate tensors The surface further includes: Generate a bivariate tensor using the following formula. curved surface : in, and These are the two B-Spline base points of the B-Spline surface. It is a group The control points are m and n, which represent the scale of the entire ligament mesh.

3. The knee joint ACL biomechanical simulation method based on patch model as described in claim 1, characterized in that, Volume meshes were generated for the femur, tibia, and ligaments in the facet model, and mesh sensitivity analysis was performed to determine the mesh type and mesh generation degree in order to optimize the ligament material parameters of the facet model.

4. A biomechanical simulation device for the knee joint ACL based on a patch model, characterized in that, include: The data acquisition module is used to acquire raw three-dimensional image data of bone tissue in the knee joint of the target individual. The knee joint modeling module is used to reconstruct a digital model of bone tissue based on the original 3D image data using 3D reconstruction software, thereby forming a digital model of the target knee joint. The patch simulation module is used to perform finite element analysis on the target knee joint digital model to obtain an operable target knee joint digital model. A set of corresponding points are selected on the medial surface of the lateral femoral condyle and the anterior tibial condyle fossa of the target knee joint digital model, and intermediate points are inserted between the corresponding point sets. Based on the mesh points corresponding to the anteromedial and posterolateral bundles, a surface of bivariate tensors B-Splines is generated to obtain the anterior cruciate ligament model of the knee joint. The optimization module is used to optimize the ligament material parameters of the anterior cruciate ligament model of the knee joint. The patch simulation module further includes: Determine the origin and insertion points of the ACL (achondrial artery ligament) in the bone model of the target knee joint digital model, and select a set of corresponding points at each ACL origin and insertion point to obtain two sets of points. The midpoint interval r of the corresponding points is determined by the following formula: Where i is the i-th point in the point set, and n is the number of points in the point set; Insert intermediate points based on the intermediate point interval r; right A force is applied to each control point of the curved surface, and the force is along the direction of the normal vector of the bone model section at each point, so that... The curved surface is separated from the bone model to obtain a patch model of the anterior cruciate ligament of the knee joint; The optimization module further includes: A multi-angle drawer test was performed on the current in vivo knee joint to obtain the ACL tension. ; Preset ligament material parameters were input into the anterior cruciate ligament (ACL) model of the knee joint, and the same motion as the drawer test was performed to calculate the simulation results of ACL tension. The ligament material parameters include the ligament reference length, elastic coefficient, and strain constant. Compare and Based on the comparison results, the ligament material parameters are iterated until the entire drawer test is moved. and The motion tension curve is consistent with the target ligament material parameters; the target ligament material parameters are then input into the patch model of the anterior cruciate ligament of the knee joint.

5. A biomechanical simulation device for the knee joint ACL based on a patch model, characterized in that, include: A memory and a processor, wherein the memory stores computer-readable instructions that, when executed by the processor, cause the processor to perform the steps in the patch model-based knee joint ACL biomechanical simulation method as described in any one of claims 1 to 3.

6. A storage medium storing computer-readable instructions, characterized in that, When the computer-readable instructions are executed by one or more processors, the one or more processors perform the steps in the patch model-based knee joint ACL biomechanical simulation method as described in any one of claims 1 to 3.

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