Filling modified screw mechanical analysis method based on finite element analysis model

Abstract

The invention belongs to the field of simulation, and provides a finite element analysis model-based filling modified screw mechanical analysis method, which comprises the following steps of: acquiring three-dimensional medical image data of a target bone tissue area, and constructing a finite element analysis model of a microcosmic bone trabecula structure and a macroscopic pelvis structure on the basis of the three-dimensional medical image data; introducing a filling modified screw structure into the finite element analysis model; constructing a response regulation factor field which is used for representing the local adaptation capability of each position in the filling structure, and automatically updating the distribution of the factor field according to the stress state change; based on a global error minimization principle, iteratively optimizing the factor field distribution to enable the overall stress distribution of the filling modified screw in the bone tissue to tend to a target state; and outputting stress response distribution, strain distribution and a mechanical adaptation area of the filling modified screw in the bone tissue to evaluate the fixing performance of the filling modified screw under the osteoporosis condition.

Description

Technical Field

[0001] The present invention belongs to the field of simulation, and in particular relates to a mechanical analysis method for a filled and modified screw based on a finite element analysis model. Background Art

[0002] With the aging of the population, osteoporosis is becoming increasingly prevalent among the elderly, and the brittle fractures caused by osteoporosis have become a major challenge in clinical treatment. In the repair of brittle fractures, screws are a common internal fixation method and are widely used for reconstruction and stabilization of the pelvis, spine, and other parts of the body. However, after being implanted into osteoporosis patients, traditional metal screw structures often suffer from problems such as pull-out failure, loosening failure, or local fractures due to insufficient bone tissue strength, resulting in an increased surgical failure rate and seriously affecting patient recovery.

[0003] Prior art methods for improving the fixation of screws in osteoporotic bone tissue typically include increasing the screw diameter, employing thread reinforcement designs, applying bone cement to enhance fixation, and surface roughening. These methods improve the initial fixation force of the screw to a certain extent, but due to the fixed properties of the screw material itself, it cannot adapt to changes in the local mechanical environment at different locations after implantation. Consequently, problems such as stress concentration, bone crushing, and insufficient long-term fixation stability still exist.

[0004] The main drawback of the existing technology is that it fails to achieve dynamic adaptation between the internal material properties of the screw and the local mechanical state of the bone tissue. After implantation, the screw structure cannot adjust its own stiffness or plasticity according to the stress distribution, resulting in widespread problems of local excessive rigidity or excessive softness, which in turn causes overall performance degradation or early failure of the fixation system, limiting the widespread application of screws in high-risk osteoporosis patients. Summary of the Invention

[0005] In order to solve the problems in the prior art, the present invention provides a mechanical analysis method for a filled and modified screw based on a finite element analysis model, which is characterized by comprising:

[0006] Acquiring three-dimensional medical imaging data of a target bone tissue region, and constructing a finite element analysis model of a microscopic trabecular bone structure and a macroscopic pelvic structure based on the three-dimensional medical imaging data;

[0007] Introducing a filling-modified screw structure into the finite element analysis model, wherein the screw includes an internal filling structure with stress response adjustment capability, wherein the filling structure is composed of a responsive material and can dynamically adjust its material performance parameters according to the stress distribution around the screw;

[0008] Constructing a response regulation factor field to characterize the local adaptability of each position in the filling structure, and automatically updating the distribution of the factor field according to changes in the stress state;

[0009] Based on the principle of global error minimization, the factor field distribution is iteratively optimized so that the overall stress distribution of the filled modified screw in the bone tissue approaches the target state;

[0010] The stress response distribution, strain distribution and mechanical adaptation area of ​​the filled modified screw in the bone tissue are output to evaluate its fixation performance under osteoporosis conditions.

[0011] Furthermore, the step of acquiring three-dimensional medical imaging data of the target bone tissue area includes:

[0012] Continuous tomographic scanning of the target pelvic area is performed using multi-slice spiral CT or high-resolution MRI equipment to acquire complete three-dimensional image data covering the sacroiliac joint, acetabulum, and pubic symphysis area. The acquired image data is saved as a DICOM format file, and image noise removal processing is performed on the DICOM format image data to eliminate artifacts. Grayscale normalization processing is performed to standardize the density range of data from different devices, and bilinear interpolation or cubic spline interpolation method is used to resample the image to unify the isotropic resolution.

[0013] Furthermore, constructing a finite element analysis model of the microscopic trabecular structure and the macroscopic pelvic structure based on the three-dimensional medical imaging data includes:

[0014] A density threshold segmentation method was used to extract bone tissue areas. The threshold range was set to adapt to the different density characteristics of trabeculae and cortical bone. The trabecular bone area and the overall pelvic contour were extracted separately. Voxelized modeling was used for the trabecular bone area to generate a microscopic finite element mesh with a voxel unit size less than or equal to 100 microns. Surface reconstruction and meshing were used for the overall pelvic area. Local mesh encryption was performed in the sacroiliac joint and pubic symphysis connection area to make the unit size less than half of the surrounding area.

[0015] Furthermore, the introducing of the filling-modified screw structure into the finite element analysis model includes:

[0016] Design hollow cavities or partitioned filling areas inside the screw body, and place the filling material at the screw axis, thread root, or force-sensitive locations on the screw head;

[0017] In the finite element software, the material type of the filling area is defined as a nonlinear material model with stress response adjustment function;

[0018] The contact relationship between the outer surface of the screw and the bone tissue model is defined in the finite element model. The contact type is set to friction contact or bonding contact. The contact friction coefficient or bonding strength is set according to the screw implantation depth and bone density. The friction contact model allows relative slippage at the interface.

[0019] According to the patient's actual physiological load or standard mechanical loading conditions, vertical pressure, shear force or torsional load is applied to the screw and bone tissue finite element model, and the material response mechanism of the filling area is activated at the same time. The material performance parameters are dynamically adjusted as the local stress field changes and updated to the new mechanical state.

[0020] Furthermore, constructing the response regulatory factor field includes:

[0021] A factor variable is defined at each finite element node in the filling area and initialized;

[0022] Dynamically adjust the response control factor based on the deviation between the stress field obtained by the current simulation step of the screw and bone tissue and the preset target stress;

[0023] After each iteration of the simulation loading, the current stress of all unit nodes inside the filling structure is extracted and the deviation from the target stress is calculated;

[0024] Iteratively update the response control factor field according to the update rule, and perform a smoothing process on the updated factor field;

[0025] Based on the latest response control factor field, the material performance parameters of each filling unit are updated.

[0026] Furthermore, the update rule is expressed as:

[0027]

[0028] in:

[0029] Represents the rate of change of the factor field with respect to time; γ represents the stress response adjustment coefficient, σ(x) represents the current stress at position x, σ_target represents the target stress, and β represents the diffusion smoothing coefficient. Represents the spatial Laplacian value of the factor field.

[0030] Furthermore, based on the principle of global error minimization, iteratively optimizing the factor field distribution so that the overall stress distribution of the filled modified screw in the bone tissue approaches the target state includes:

[0031] In the finite element simulation environment, an overall error evaluation index is set, and the difference between the current stress and the target stress of each node inside the screw is integrated and accumulated;

[0032] After the initial simulation solution, the stress values ​​of all nodes inside the screw are extracted, and the initial overall error value is obtained by numerical integration according to the error function formula;

[0033] The iteration is terminated when the overall error drops below the preset ratio of the initial error or the overall error gradient is less than the set threshold;

[0034] Calculate the gradient information of the overall error function to the factor field, and adjust the response control factor value of each node along the negative gradient direction;

[0035] After updating the factor field, the overall stress distribution of the screw is re-simulated and the overall error is recalculated to determine whether the convergence conditions are met. If not, the iteration is continued; if so, the iteration is terminated and the final factor field distribution is output.

[0036] Furthermore, it is characterized in that the error function is defined as:

[0037] J(φ)=∫ Ω (σ_current(x)-σ_target(x)) 2 dx,

[0038] in:

[0039] J(φ) represents the overall error, Ω represents the computational domain where the filling screw is located, σ_current(x) is the current stress value at position x, σ_target(x) is the target stress value at the corresponding position, and dx is the integrated volume unit.

[0040] Furthermore, outputting the stress response distribution, strain distribution, and mechanical adaptation area of ​​the filled modified screw in the bone tissue for evaluating its fixation performance under osteoporosis conditions includes:

[0041] After the finite element simulation is completed, the maximum principal stress, minimum principal stress and equivalent stress data of all unit nodes inside the screw are exported to generate a three-dimensional spatial distribution diagram;

[0042] Extract the maximum principal strain, minimum principal strain and equivalent plastic strain distribution of all unit nodes during loading;

[0043] According to the final optimized response control factor field distribution, the interior of the screw is divided into areas with different adaptation levels;

[0044] Comprehensive stress response distribution, strain distribution and mechanical adaptation area information to quantitatively calculate the fixed stability index;

[0045] The screw stress distribution diagram, strain distribution diagram, adaptation area division diagram and fixation performance score are summarized into a standardized technical report.

[0046] Furthermore, the fixed stability index is calculated as follows:

[0047] FPS=w1×(σ_max / σ_target)+w2×(ε_max / ε_target)+w3×(Δd / Δd_target),

[0048] in:

[0049] FPS is the fixed performance score, σ_max is the maximum principal stress, σ_target is the upper limit of the target principal stress, ε_max is the maximum principal strain, ε_target is the upper limit of the target principal strain, Δd is the maximum displacement of the fixed area, Δd_target is the displacement control target, w1, w2, and w3 are the weight coefficients of each indicator, which are set according to actual application requirements.

[0050] The present invention provides a mechanical analysis method for filled and modified screws based on a finite element analysis model, which has the following beneficial effects:

[0051] By setting up a filling structure with stress response adjustment capability inside the screw, the filling material can dynamically adjust its own material properties according to the local stress state, effectively alleviating the local stress concentration phenomenon after screw implantation, and improving the fixation stability and fatigue life of the screw in a complex osteoporosis environment.

[0052] By introducing a response control factor field, the local adaptability of each position inside the filling structure is dynamically modeled and updated in real time. This can achieve spatial continuous adjustment of material properties during the simulation process, forming a flexible transition area and a high-rigidity support area inside the screw that are highly matched with the stress environment, significantly improving the mechanical coordination of the entire implant system.

[0053] Based on the principle of global error minimization, the response control factor field distribution is iteratively optimized. Through systematic adjustment of the overall stress distribution, the overall performance imbalance problem caused by traditional local optimization methods is avoided, ensuring the optimal force adaptation effect in the overall bone tissue environment after screw implantation, and enhancing long-term stability and failure resistance.

[0054] In summary, the present invention outputs the stress response distribution, strain distribution, and mechanical adaptation area after screw implantation, and performs quantitative evaluation based on comprehensive fixation performance indicators. This can intuitively and systematically reflect the fixation effect of the modified screw under osteoporosis conditions, providing an effective preoperative design basis and postoperative performance evaluation method, thereby improving the safety and scientific nature of personalized screw implantation therapy. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0056] Figure 1 It is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0057] Below, the invention is preferably described with reference to the accompanying drawings and specific embodiments.

[0058] This embodiment solves the above problem through the following steps:

[0059] In one embodiment, reference Figure 1 The present invention provides a mechanical analysis method for a modified screw with a filling material based on a finite element analysis model. By constructing a multi-scale finite element analysis model, the stress response, deformation behavior, and fixation stability of a modified screw containing a responsive filling material structure in a complex biomechanical environment are refinedly modeled and simulated. Specifically, the method includes the following steps:

[0060] Step S10 , acquiring three-dimensional medical image data of the target bone tissue region, and constructing a finite element analysis model of the microscopic trabecular structure and the macroscopic pelvic structure based on the three-dimensional medical image data.

[0061] In order to realistically and accurately simulate the mechanical behavior of filled and modified screws within bone tissue, modeling must be based on the actual bone structure characteristics of the individual patient. The density, arrangement direction, and integrity of the trabecular structure within bone tissue, especially the brittle bone tissue of the elderly, have a direct impact on the fixation performance and force distribution of the screw. Therefore, by acquiring three-dimensional medical imaging data of the target bone tissue area and constructing a finite element analysis model of the microscopic trabecular structure and the macroscopic pelvic structure based on the imaging data, it is possible to simultaneously reflect the contribution of the local microstructure to the overall mechanical behavior at multiple scales, significantly improving the accuracy and biological relevance of the mechanical analysis.

[0062] Based on the above principles, a specific implementation of step S10 includes the following steps:

[0063] Step S101 is to acquire three-dimensional medical imaging data, specifically by using a multi-slice spiral CT or high-resolution MRI device to perform continuous tomographic scanning of the target patient's pelvic area, obtain complete imaging data covering the pelvis and surrounding structures, and save the imaging data as a DICOM format file.

[0064] Step S102, preprocessing the DICOM format image data, specifically performing image noise removal operations to reduce scanning artifacts, performing grayscale normalization processing to standardize the density range between different patients or devices, and performing slice resampling to unify the resolution when necessary. Optional implementation schemes include using Gaussian filtering for denoising or using bilinear interpolation for resampling.

[0065] Step S103, extracting the bone tissue area, specifically setting a density threshold range in the preprocessed image data to separate the bone tissue from the surrounding soft tissue. Optional implementation schemes include directly using a threshold-based region growing algorithm to extract bone tissue, or combining a deep learning image segmentation model to perform fine segmentation of trabeculae and cortical bone. For the threshold extraction method, by setting upper and lower grayscale values, all pixels within the range can be automatically marked as bone tissue areas.

[0066] Step S104 is to construct a microscopic trabecular structure model. Specifically, for the extracted bone tissue area, a three-dimensional trabecular network is reconstructed at high resolution. The trabecular mesh is generated using a voxelization method. The voxelization method is to represent spatially continuous bone tissue as a stack of cubic units to maintain the true shape and connectivity of the trabeculae. If the voxel size is set to 100 microns, the trabecular morphology can be guaranteed to be basically intact.

[0067] Step S105, constructing a macroscopic pelvic structure model, specifically, performing a three-dimensional reconstruction of the overall pelvic contour at a medium resolution, extracting the sacroiliac joint, pubic symphysis, acetabulum and pelvic ring areas, and establishing a macroscopic mesh model. For important connection structure areas, optional implementation solutions include local mesh encryption, that is, refining the mesh units around the sacroiliac joint and pubic symphysis to half the size of the basic unit to improve local simulation accuracy.

[0068] Step S106, establishing a multi-scale coupling relationship between the micro and macro structures, specifically by transferring the local stiffness parameters of the micro trabecular structure unit to the macro pelvic structure model unit through the node mapping method or the shape function interpolation method, and setting a bidirectional mechanical feedback path at the same time, so that the macro pelvic deformation can reversely affect the stress state of the micro trabecular unit. Optional implementation schemes include direct node position alignment projection or weighted interpolation mapping based on the local coordinate system. The node mapping method refers to finding the minimum distance pairing relationship between the micro unit node and the macro unit node in space, thereby establishing a data transmission path.

[0069] By constructing finite element analysis models of the microscopic trabecular structure and the macroscopic pelvic structure based on three-dimensional medical imaging data, it is possible to achieve cross-scale mechanical behavior simulation from local to global while maintaining anatomical accuracy, effectively capture the local failure mechanism of the osteoporotic area, and accurately evaluate the overall pelvic stability changes. In the simulation analysis of filling-modified screw implantation, it can significantly improve the accuracy of the prediction results and the clinical guidance significance, avoid the stress prediction errors and structural stability misjudgment problems caused by traditional homogeneous modeling methods, and provide a scientific basis for screw design optimization and personalized treatment plan formulation.

[0070] For example, taking a 68-year-old female patient with brittle pelvic fracture as an example, 64-row spiral CT scanning technology was used to collect continuous tomographic images from the lumbar sacral region to the acetabulum region. After the image data was preprocessed by Gaussian filtering and the resolution was unified, the density threshold method was used to extract the bone tissue area. A high-precision microscopic finite element model with a voxel size of 100 microns was generated for the trabecular structure inside the lumbar spine and sacrum. At the same time, a medium-resolution three-dimensional reconstruction of the overall pelvic contour was performed, and a local encrypted grid was set at the sacroiliac joint and pubic symphysis. The multi-scale coupling relationship between the microscopic and macroscopic models was established through the node projection method, and the three-dimensional finite element modeling of patients with brittle pelvic fractures was completed, providing a basis for the subsequent mechanical analysis of the implantation of modified filling screws.

[0071] Step S20, introducing a filling-modified screw structure into the finite element analysis model, wherein the filling-modified screw includes an internal filling structure with stress response adjustment capability, and the filling structure is composed of a responsive material and can dynamically adjust its material performance parameters according to the stress distribution around the screw.

[0072] A filled-modified screw structure refers to a composite implant structure in which a filling material with variable mechanical properties is embedded inside a traditional metal screw or in a specific area to improve the overall stress state of the screw.

[0073] After the filled modified screw is implanted into the bone tissue, due to the different degrees of osteoporosis and microscopic trabecular structure heterogeneity of individual patients, the screw is prone to local stress concentration, shear damage or pull-out failure during the stress process. The traditional homogeneous screw structure cannot dynamically adapt to the local mechanical state according to changes in the implantation environment, resulting in insufficient fixation performance or premature failure. Therefore, the present invention introduces a filled modified screw structure into the finite element analysis model, and designs a filling structure with stress response adjustment capability inside the screw. The filling structure is composed of a responsive material and can dynamically adjust its elastic modulus, yield strength and other material performance parameters according to changes in the stress field around the screw, so that the screw exhibits corresponding local stiffness and energy absorption characteristics in different stress areas, thereby achieving implantation environment adaptation and improving the overall fixation effect and fatigue life.

[0074] In a specific implementation, step S20 includes the following sub-steps:

[0075] Step S201, defining the geometric structure of the filled modified screw in the finite element analysis model, specifically designing a hollow cavity or partitioned filling area inside the screw body, and arranging the filling material to force-sensitive positions such as the screw axis, thread root or screw head. Optional implementation schemes include setting a through cylindrical cavity, a segmented multi-cavity structure or a honeycomb filling pattern inside the screw.

[0076] Step S202, specifying the material property of the filling area as a responsive material, specifically defining the material type of the filling area as a nonlinear material model with stress response adjustment function in the finite element software. Optional implementation schemes include setting the elastic modulus of the material to change continuously with the stress field, or dynamically adjusting the yield strain point according to the local stress amplitude. If a formula is used to characterize the change relationship of the elastic modulus of the filling material, the relationship between the elastic modulus E_eff and the stress field σ(x) can be set as

[0077]

[0078] Among them, E_eff represents the effective elastic modulus after dynamic adjustment, E_0 represents the initial elastic modulus, and α represents the response adjustment coefficient. Represents the gradient modulus of the stress field at position x.

[0079] Step S203, establish the contact interface between the filled modified screw and the bone tissue, specifically defining the contact relationship between the outer surface of the screw and the bone tissue model in the finite element model. The contact type can be set to friction contact or bonding contact. The contact friction coefficient or bonding strength is set according to the screw implantation depth and bone density. The friction contact model allows relative slippage at the interface, and the bonding contact model is used to simulate the initial stable stage of the screw fixation period.

[0080] Step S204: Apply loading conditions and initialize the material performance response. Specifically, vertical pressure, shear force, or torsional load is applied to the screw and bone tissue finite element model according to the patient's actual physiological load or standard mechanical loading conditions. At the same time, the material response mechanism of the filling area is activated. The material performance parameters are dynamically adjusted as the local stress field changes and updated to a new mechanical state.

[0081] Step S205 , complete the preliminary simulation solution and extract the internal stress, deformation, and energy absorption distribution data of the screw, and analyze the adaptability and fixation stability of the filled modified screw under different loading conditions.

[0082] By introducing a filled modified screw structure into the finite element analysis model and adopting an internal filling structure with stress response adjustment capabilities, the screw can automatically adapt to local force changes under different implantation environments, thereby effectively alleviating stress concentration, improving overall implant stability, and reducing the probability of pull-out failure caused by osteoporosis or local trabecular damage. At the same time, energy buffering and crack initiation delay are achieved, greatly improving the fatigue life and long-term fixation performance of the modified screw in a complex bone tissue environment, and providing a new technical path for the design of personalized medical implants.

[0083] For example, following the example of the previous steps, after completing the reconstruction of the three-dimensional medical imaging data and the construction of the multi-scale finite element model of the pelvis, a hollow cavity with an axial diameter of 1.5 mm is designed to pass through the screw body and filled with a responsive material. In the ANSYS software, the filling material is defined as a nonlinear material model in which the elastic modulus changes with the local stress gradient. The initial elastic modulus is set to 500 MPa, the response adjustment coefficient is set to 0.05, and vertical pressure and shear load under simulated walking conditions are applied for simulation.

[0084] Step S30: constructing a response regulation factor field for characterizing the local adaptability of each position in the filling structure, and automatically updating the distribution of the factor field according to changes in the stress state.

[0085] In this invention, the response control factor field refers to a spatially continuous distribution field established within the filling structure, used to describe the degree of material property regulation. Its value can dynamically change with the local stress state, driving the adaptive adjustment of material properties. The factor field distribution refers to the spatially continuous arrangement of the values ​​of the response control factor at different spatial locations within the filling area, used to describe the spatial regulation state of local material properties.

[0086] In a specific implementation, the implementation of step S30 includes the following sub-steps:

[0087] Step S301, initialize the response control factor field, specifically define a factor variable φ at each finite element unit node in the filling area, and set the initial value to φ_0, which represents the initial material performance state. The initial factor field can be set to a uniform distribution or assigned an initial value based on the bone density distribution. Optional implementation schemes include setting the initial φ value based on the bone tissue CT value or setting a fixed uniform initial value.

[0088] Step S302: Define the factor field update rule. Specifically, dynamically adjust the response control factor φ based on the deviation Δσ between the stress field σ(x) obtained by the current step simulation of the screw and bone tissue and the preset target stress σ_target. The update rule is expressed as

[0089]

[0090] in, represents the rate of change of the factor field with respect to time, γ represents the stress response adjustment coefficient, σ(x) represents the current stress at position x, σ_target represents the target stress, and β represents the diffusion smoothing coefficient. Represents the spatial Laplace operator value of the factor field, which is used to maintain the spatial continuity and smoothness of the factor field.

[0091] Step S303 : performing stress state sampling, specifically extracting the current stress σ(x) of all unit nodes inside the filling structure after each iteration step of the simulation loading, and calculating the deviation Δσ from the target stress σ_target.

[0092] In step S304, the response control factor field is iteratively updated according to the update rules. Specifically, according to the update equation set in step S302, the value of φ is synchronously updated at all nodes, and a smoothing process is performed on the updated factor field to avoid abnormal jumps in material properties due to local fluctuations.

[0093] Step S305: Based on the latest response control factor field, the material performance parameters of each filling unit are updated. Specifically, the value of the factor φ is associated with the material constitutive parameters, and the local elastic modulus, yield strength or damping parameter is adjusted to form a spatially continuously changing material performance distribution.

[0094] Step S306 , continue the simulation solution and enter the next stress sampling and factor update cycle until the entire loading process is completed or the convergence condition is met.

[0095] By constructing and dynamically updating the response control factor field, continuous spatial adjustment of the internal material properties of the filled modified screw can be achieved, so that the material stiffness and plasticity properties change adaptively during the stress process, effectively alleviating the local stress concentration phenomenon, improving the overall stress uniformity of the implanted screw, and at the same time improving the matching performance of the screw and bone tissue interface, significantly enhancing the long-term fixation stability and fatigue life of the implant system, thereby achieving safer and more reliable clinical application effects in osteoporosis or complex stress environments.

[0096] For example, following the previous example, after completing the finite element modeling of the pelvis and embedding the filling modified screw, the response control factor φ is initialized at each finite element unit node in the filling area inside the screw, the initial value is set to 1.0, and the target stress σ_target is set to 30 MPa. During the simulation of loading the patient's weight-equivalent vertical force, the current stress σ(x) of each node is sampled in real time, the stress deviation is calculated and iteratively updated through the set factor field evolution equation. The response control factor tends to increase in areas with higher stress, thereby enhancing the local material stiffness, and maintains a low level in areas with lower stress, ultimately forming an elastic modulus distribution that is highly matched with the local support requirements of bone tissue.

[0097] Step S40: Based on the principle of global error minimization, iteratively optimize the factor field distribution so that the overall stress distribution of the filled modified screw in the bone tissue approaches the target state.

[0098] In this paper, the principle of global error minimization involves evaluating the overall difference between the current and target stress distributions within the screw structure. This difference is then gradually reduced through optimization strategies, allowing the overall structural performance to approach the desired state. The target state is the desired stress or strain distribution achieved after the screw is implanted in bone tissue, typically set to a maximum principal stress threshold or a desired uniform stress field.

[0099] Since the local material properties inside the filled modified screw are dynamically adjusted through the response control factor field, the local stress state changes continuously during the simulation process. If only local adjustments are made, the coordination of the overall mechanical properties cannot be guaranteed, and local over-strengthening or weakening is likely to occur. Therefore, in order to ensure that the stress distribution of the screw in the overall bone tissue environment tends to the set target state, it is necessary to iteratively optimize the distribution of the response control factor field based on the principle of global error minimization. Through continuous updating and correction, the material properties of each region inside the screw can be optimally matched under the overall force system, thereby achieving the mechanical optimization goal of local adaptation and overall coordination.

[0100] In a specific implementation, step S40 includes the following sub-steps:

[0101] Step S401, define the overall error function, specifically, set the overall error evaluation index in the finite element simulation environment, integrate and accumulate the difference between the current stress and the target stress of each node inside the screw, and the overall error function J(φ) is defined as

[0102] J(φ)=∫ Ω (σ_current(x)-σ_target(x)) 2 dx,

[0103] Where J(φ) represents the overall error, Ω represents the computational domain where the filler screw is located, σ_current(x) is the current stress value at position x, σ_target(x) is the target stress value at the corresponding position, and dx is the integrated volume unit.

[0104] Step S402 , calculating the initial overall error, specifically, extracting the stress values ​​of all nodes inside the screw after the preliminary simulation solution, and numerically integrating the error function formula in step S401 to obtain the initial overall error value J_0.

[0105] Step S403, constructing the optimization objective and convergence criterion, specifically setting the overall error to drop below a certain proportion of the initial error or the overall error gradient to be less than a set threshold to terminate the iteration. Optional implementation schemes include setting the error to drop to within 10% or setting the error gradient to be less than 1% as the convergence condition.

[0106] Step S404: Update the response control factor field based on the overall error gradient. Specifically, calculate the gradient information of the overall error function J(φ) to the factor field φ, and adjust the response control factor value of each node along the negative gradient direction. The gradient descent update formula is:

[0107]

[0108] Among them, φ_new is the updated factor value, φ_old is the factor value of the previous step, η is the step coefficient, is the partial derivative of the overall error with respect to the factor.

[0109] In step S405, after updating the factor field, the overall stress distribution of the screw is re-simulated and the overall error is recalculated to determine whether the convergence condition set in step S403 is met. If not, the process returns to step S404 to continue iterating. If so, the iteration is terminated and the final factor field distribution is output.

[0110] In step S406, the finally optimized response control factor field is used as the basis for the performance distribution of the filling structure material inside the screw to achieve the optimal distribution of the overall stress.

[0111] By iteratively optimizing the response control factor field distribution based on the principle of global error minimization, not only can local adjustments be made to local stress anomalies, but also the coordination and unification of the material properties inside the screw can be achieved within the overall range, effectively avoiding the problem of overall mechanical property degradation caused by local excessive reinforcement or softening, improving the overall stress uniformity of the interface between the screw and bone tissue, reducing the risk of stress concentration, and improving the overall stability and long-term durability of the screw after implantation, providing a systematic and executable optimization path for the design and application of filling and modified screws in complex osteoporosis environments.

[0112] For example, following the previous example, after completing the construction of the multi-scale finite element model of the pelvis, implantation of the filling-modified screw, initialization of the response control factor field and local adjustment, the target stress σ_target is set to 30 MPa, and the initial overall error J_0 is calculated to be 450 MPa square. The factor field distribution is adjusted according to the overall error gradient through each iteration, and the step coefficient η is set to 0.01. After 8 consecutive iterations, the overall error drops to within 7% of the initial value. Finally, the elastic modulus of the filling material inside the screw is automatically increased in the stress concentration area, and the low stress area remains flexible. The simulation results show that the overall principal stress distribution is more uniform.

[0113] Step S50: outputting the stress response distribution, strain distribution, and mechanical adaptation area of ​​the filled modified screw in the bone tissue for evaluating its fixation performance under osteoporosis conditions.

[0114] After completing the response control factor field optimization of the filled modified screw, in order to systematically evaluate the fixation effect of the modified screw under osteoporosis conditions, it is necessary to output the stress response distribution, strain distribution and mechanical adaptation area of ​​the modified screw inside the bone tissue. By comprehensively analyzing the force uniformity, local strain concentration and material adaptation characteristics, the stability and safety of the screw after implantation are evaluated. Therefore, the system outputs various mechanical response data in the post-processing stage of the simulation results, which can provide a basis for screw design improvement and clinical implantation strategy optimization, and at the same time verify the applicability and effectiveness of the proposed method for actual osteoporosis patients.

[0115] In a specific implementation, step S50 includes the following sub-steps:

[0116] Step S501 is to extract the stress response distribution. Specifically, after the finite element simulation is completed, the maximum principal stress, minimum principal stress and equivalent stress data of all unit nodes inside the screw are exported to generate a three-dimensional spatial distribution diagram. Optional implementation schemes include displaying the stress range in the form of a color-coded cloud map or extracting key sections for two-dimensional slice analysis.

[0117] Step S502 is to extract the strain distribution. Specifically, the maximum principal strain, minimum principal strain, and equivalent plastic strain distribution of all unit nodes during the loading process are extracted. If necessary, a strain evolution sequence is derived according to different time steps to evaluate the local deformation accumulation trend. Optional implementation solutions include drawing the strain vector field or generating a cumulative deformation animation sequence.

[0118] Step S503, identifying the mechanical adaptation area, specifically dividing the interior of the screw into different adaptation level areas based on the final optimized response control factor field distribution, such as a high stiffness adaptation area, a medium adaptation area, and a flexible transition area. Optional implementation schemes include setting factor threshold intervals for automatic partitioning, or using a clustering algorithm to identify continuous adaptation areas.

[0119] Step S504: Evaluate the fixing performance index, specifically by integrating the stress response distribution, strain distribution and mechanical adaptation area information, and quantitatively calculate the fixing stability index, including but not limited to the maximum principal stress peak, the maximum principal strain peak, the stress concentration factor, and the displacement amplitude of the fixing area. If necessary, define a comprehensive fixing performance scoring formula. The example formula is as follows:

[0120] FPS=w1×(σ_max / σ_target)+w2×(ε_max / ε_target)+w3×(Δd / Δd_target),

[0121] Among them, FPS is the fixed performance score, σ_max is the maximum principal stress, σ_target is the upper limit of the target principal stress, ε_max is the maximum principal strain, ε_target is the upper limit of the target principal strain, Δd is the maximum displacement of the fixed area, Δd_target is the displacement control target, and w1, w2, and w3 are the weight coefficients of each indicator, which are set according to actual application requirements.

[0122] Step S505: Output a comprehensive analysis report, specifically summarizing the screw stress distribution map, strain distribution map, adaptation area division map, and fixation performance score into a standardized technical report as a reference for subsequent optimization design or clinical implant decision-making.

[0123] In this step, by outputting the stress response distribution, strain distribution and mechanical adaptation area of ​​the filled modified screw in the bone tissue and conducting a systematic evaluation based on the comprehensive fixation performance indicators, the stability, adaptability and safety of the screw after implantation can be intuitively and quantitatively reflected, potential failure risks can be effectively identified, the adaptive regulation effect of the filling structure can be verified, and the screw design optimization and individualized treatment plan formulation can be guided, significantly improving the clinical application effect and long-term reliability of implants in osteoporosis patients.

[0124] For example, following the above example, after completing the three-dimensional finite element modeling of the pelvis, implantation of the modified filling screw and factor field optimization, the maximum principal stress distribution cloud map inside the screw was output, and it was found that the maximum principal stress in the stress concentration area was 28 MPa, which was lower than the set target upper limit of 30 MPa. The strain distribution map showed that the maximum principal strain was 0.45%, which was within the safe deformation range. According to the final response regulation factor field, three types of mechanical adaptation areas were divided. The high stiffness adaptation area was mainly distributed in the thread root and the connecting bone dense area, and the flexible transition area was distributed in the middle section of the screw. The comprehensive fixation performance score FPS was calculated to be 0.82, indicating that the modified screw has good fixation stability and biomechanical adaptability under the osteoporosis condition of this patient.

[0125] The prior art mentioned in the aforementioned background technology section and specific embodiment section of the present invention may be regarded as a part of the present invention and used to understand the meaning of some technical features or parameters.

Claims

1. A mechanical analysis method for a filled and modified screw based on a finite element analysis model, characterized in that: The steps include: Acquiring three-dimensional medical imaging data of a target bone tissue region, and constructing a finite element analysis model of a microscopic trabecular bone structure and a macroscopic pelvic structure based on the three-dimensional medical imaging data; Introducing a filling-modified screw structure into the finite element analysis model, wherein the screw includes an internal filling structure with stress response adjustment capability, wherein the filling structure is composed of a responsive material and can dynamically adjust its material performance parameters according to the stress distribution around the screw; Constructing a response regulation factor field to characterize the local adaptability of each position in the filling structure, and automatically updating the distribution of the factor field according to changes in the stress state; Based on the principle of global error minimization, the factor field distribution is iteratively optimized so that the overall stress distribution of the filled modified screw in the bone tissue approaches the target state; The stress response distribution, strain distribution and mechanical adaptation area of ​​the filled modified screw in the bone tissue are output to evaluate its fixation performance under osteoporosis conditions.

2. The mechanical analysis method for filled and modified screws based on the finite element analysis model according to claim 1 is characterized in that: The step of acquiring three-dimensional medical imaging data of the target bone tissue area includes: Continuous tomographic scanning of the target pelvic area is performed using multi-slice spiral CT or high-resolution MRI equipment to acquire complete three-dimensional image data covering the sacroiliac joint, acetabulum, and pubic symphysis area. The acquired image data is saved as a DICOM format file, and image noise removal processing is performed on the DICOM format image data to eliminate artifacts. Grayscale normalization processing is performed to standardize the density range of data from different devices, and bilinear interpolation or cubic spline interpolation method is used to resample the image to unify the isotropic resolution.

3. The mechanical analysis method for filled and modified screws based on the finite element analysis model according to claim 1 is characterized in that: The constructing of a finite element analysis model of the microscopic trabecular structure and the macroscopic pelvic structure based on the three-dimensional medical imaging data includes: A density threshold segmentation method was used to extract bone tissue areas. The threshold range was set to adapt to the different density characteristics of trabeculae and cortical bone. The trabecular bone area and the overall pelvic contour were extracted separately. Voxelized modeling was used for the trabecular bone area to generate a microscopic finite element mesh with a voxel unit size less than or equal to 100 microns. Surface reconstruction and meshing were used for the overall pelvic area. Local mesh encryption was performed in the sacroiliac joint and pubic symphysis connection area to make the unit size less than half of the surrounding area.

4. The mechanical analysis method for filled and modified screws based on the finite element analysis model according to claim 1, characterized in that: The introducing of the filling-modified screw structure into the finite element analysis model comprises: Design hollow cavities or partitioned filling areas inside the screw body, and place the filling material at the screw axis, thread root, or force-sensitive locations on the screw head; In the finite element software, the material type of the filling area is defined as a nonlinear material model with stress response adjustment function; The contact relationship between the outer surface of the screw and the bone tissue model is defined in the finite element model. The contact type is set to friction contact or bonding contact. The contact friction coefficient or bonding strength is set according to the screw implantation depth and bone density. The friction contact model allows relative slippage at the interface. According to the patient's actual physiological load or standard mechanical loading conditions, vertical pressure, shear force or torsional load is applied to the screw and bone tissue finite element model, and the material response mechanism of the filling area is activated at the same time. The material performance parameters are dynamically adjusted as the local stress field changes and updated to the new mechanical state.

5. The mechanical analysis method for filled and modified screws based on the finite element analysis model according to claim 1 is characterized in that: The constructing of the response regulation factor field comprises: A factor variable is defined at each finite element node in the filling area and initialized; Dynamically adjust the response control factor based on the deviation between the stress field obtained by the current simulation step of the screw and bone tissue and the preset target stress; After each iteration of the simulation loading, the current stress of all unit nodes inside the filling structure is extracted and the deviation from the target stress is calculated; Iteratively update the response control factor field according to the update rule, and perform a smoothing process on the updated factor field; Based on the latest response control factor field, the material performance parameters of each filling unit are updated.

6. The mechanical analysis method for filled and modified screws based on the finite element analysis model according to claim 5 is characterized in that: The update rule is expressed as: in: Represents the rate of change of the factor field with respect to time; γ represents the stress response adjustment coefficient, σ(x) represents the current stress at position x, σ_target represents the target stress, and β represents the diffusion smoothing coefficient. Represents the spatial Laplacian value of the factor field.

7. The mechanical analysis method for filled and modified screws based on the finite element analysis model according to claim 1 is characterized in that: Based on the principle of global error minimization, the factor field distribution is iteratively optimized to make the overall stress distribution of the filled modified screw in the bone tissue approach the target state, including: In the finite element simulation environment, an overall error evaluation index is set, and the difference between the current stress and the target stress of each node inside the screw is integrated and accumulated; After the initial simulation solution, the stress values ​​of all nodes inside the screw are extracted, and the initial overall error value is obtained by numerical integration according to the error function formula; The iteration is terminated when the overall error drops below the preset ratio of the initial error or the overall error gradient is less than the set threshold; Calculate the gradient information of the overall error function to the factor field, and adjust the response control factor value of each node along the negative gradient direction; After updating the factor field, the overall stress distribution of the screw is re-simulated and the overall error is recalculated to determine whether the convergence conditions are met. If not, the iteration is continued; if so, the iteration is terminated and the final factor field distribution is output.

8. The mechanical analysis method for filled and modified screws based on the finite element analysis model according to claim 7 is characterized in that The error function is defined as: J(φ)=∫ Ω (σ_current(x)-σ_target(x)) 2 dx, in: J(φ) represents the overall error, Ω represents the computational domain where the filling screw is located, σ_current(x) is the current stress value at position x, σ_target(x) is the target stress value at the corresponding position, and dx is the integrated volume unit.

9. The mechanical analysis method for filled and modified screws based on the finite element analysis model according to claim 7, characterized in that: Outputting the stress response distribution, strain distribution, and mechanical adaptation area of ​​the filled modified screw in the bone tissue for evaluating its fixation performance under osteoporosis conditions includes: After the finite element simulation is completed, the maximum principal stress, minimum principal stress and equivalent stress data of all unit nodes inside the screw are exported to generate a three-dimensional spatial distribution diagram; Extract the maximum principal strain, minimum principal strain and equivalent plastic strain distribution of all unit nodes during loading; According to the final optimized response control factor field distribution, the interior of the screw is divided into areas with different adaptation levels; Comprehensive stress response distribution, strain distribution and mechanical adaptation area information to quantitatively calculate the fixed stability index; The screw stress distribution diagram, strain distribution diagram, adaptation area division diagram and fixation performance score are summarized into a standardized technical report.

10. The mechanical analysis method for filled and modified screws based on the finite element analysis model according to claim 9, characterized in that: The fixed stability index is calculated as follows: FPS=w1×(σ_max / σ_target)+w2×(ε_max / ε_target)+w3×(Δd / Δd_target), in: FPS is the fixed performance score, σ_max is the maximum principal stress, σ_target is the upper limit of the target principal stress, ε_max is the maximum principal strain, ε_target is the upper limit of the target principal strain, Δd is the maximum displacement of the fixed area, Δd_target is the displacement control target, w1, w2, and w3 are the weight coefficients of each indicator, which are set according to actual application requirements.

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