A filling modified screw mechanical analysis method based on a finite element analysis model

Abstract

The application belongs to the field of simulation, and provides a filling modified screw mechanical analysis method based on a finite element analysis model, which comprises the following steps: obtaining three-dimensional medical image data of a target bone tissue region, and constructing a finite element analysis model of a micro bone trabecula structure and a macro pelvis structure based on the three-dimensional medical image data; introducing a filling modified screw structure into the finite element analysis model; constructing a response control factor field 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; iteratively optimizing the distribution of the factor field based on a global error minimization principle, so that the overall stress distribution of the filling modified screw in the bone tissue tends to a target state; and outputting the stress response distribution, strain distribution and mechanical adaptation region of the filling modified screw in the bone tissue, which are used for evaluating the fixing performance of the filling modified screw under the condition of osteoporosis.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of simulation, and particularly relates to a filling modified screw mechanical analysis method based on a finite element analysis model. BACKGROUND

[0002] With the aggravation of population aging, osteoporosis is increasingly prevalent in the elderly population, and the problem of brittle fracture caused by osteoporosis has become an important challenge in clinical treatment. In the repair process of brittle fracture, screws are commonly used as internal fixation means and are widely used in the reconstruction and stabilization of the pelvis, spine and other parts. However, after the traditional metal screw structure is implanted into the body of an osteoporotic patient, due to the insufficient strength of the bone tissue, problems such as pull-out failure, loosening failure or local fracture often occur, leading to an increase in surgical failure rate and seriously affecting patient recovery.

[0003] In the prior art, in order to improve the fixing effect of the screw in the osteoporotic bone tissue, the commonly used means include increasing the diameter of the screw, using a thread strengthening design, applying bone cement to enhance fixation, and surface roughening treatment. These methods improve the initial fixation force of the screw to some extent, but since the material properties of the screw body are fixed, they cannot adaptively adjust according to the changes in the local mechanical environment after implantation, so there are still problems such as stress concentration, bone collapse and insufficient long-term fixation stability.

[0004] The main drawback of the prior art is that the dynamic adaptation of the material properties of the screw to the local mechanical state of the bone tissue cannot be achieved, and the stiffness or plasticity of the screw structure cannot be adjusted according to the stress distribution after implantation, resulting in the widespread existence of local over-rigidity or over-softness, which further causes the overall performance of the fixation system to degrade or fail prematurely, limiting the widespread application of screws in high-risk osteoporotic patients. SUMMARY

[0005] In order to solve the problems in the prior art, the present application provides a filling modified screw mechanical analysis method based on a finite element analysis model, characterized in that it comprises:

[0006] Obtaining three-dimensional medical image data of a target bone tissue region, and constructing a finite element analysis model of micro-bone trabecula structure and macro-pelvis structure based on the three-dimensional medical image data;

[0007] Introducing a filling modified screw structure into the finite element analysis model, the screw comprising an internal filling structure with stress response adjustment capability, the filling structure being composed of a responsive material and being capable of dynamically adjusting its material property parameters according to the stress distribution around the screw;

[0008] Constructing a response control factor field for characterizing 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 changes.

[0009] Based on the principle of global error minimization, iteratively optimize the factor field distribution, so that the overall stress distribution of the filling modified screw in the bone tissue tends to the target state;

[0010] Output the stress response distribution, strain distribution and mechanical adaptation area of the filling modified screw in the bone tissue, for evaluating its fixation performance under osteoporosis condition.

[0011] Further, the step of acquiring three-dimensional medical image data of the target bone tissue region comprises:

[0012] Use multi-slice spiral CT or high-resolution MRI equipment to perform continuous tomographic scanning on the target pelvic region, collect complete three-dimensional image data covering the sacroiliac joint, acetabulum and pubic symphysis region, save the collected image data as DICOM format files, and perform image noise removal processing on the DICOM format image data to eliminate artifacts, perform gray scale normalization processing to standardize the density interval of different device data, and use bilinear interpolation or cubic spline interpolation method to resample the image to unify the isotropic resolution.

[0013] Further, the step of constructing a finite element analysis model of the micro trabecular bone structure and the macro pelvic structure based on the three-dimensional medical image data comprises:

[0014] The density threshold segmentation method is used to extract the bone tissue region, and the threshold range is set to adapt to the different density characteristics of the trabecular bone and the cortical bone. The trabecular bone region and the overall pelvic contour are extracted respectively. For the trabecular bone region, a voxel modeling method is used to generate a micro finite element grid with a voxel unit size less than or equal to 100 microns. For the overall pelvic region, surface reconstruction and grid division are used, and local grid encryption processing is performed in the sacroiliac joint and pubic symphysis connection region, so that the unit size is less than half of the surrounding area.

[0015] Further, the step of introducing a filling modified screw structure into the finite element analysis model comprises:

[0016] Design a hollow cavity or a partition filling area in the screw body, and layout the filling material to the stress sensitive position of the screw shaft, the thread root or the screw head;

[0017] Define the material type of the filling area as a nonlinear material model with stress response adjustment function in the finite element software;

[0018] Define the contact relationship between the outer surface of the screw and the bone tissue model in the finite element model, and set the contact type to frictional contact or cohesive contact. Set the contact friction coefficient or cohesive strength according to the screw implantation depth and bone density. The frictional contact model allows relative slip to occur at the interface;

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

[0020] Further, the construction of the response regulation factor field comprises:

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

[0022] According to the deviation between the stress field obtained by the current step simulation of the screw and the bone tissue and the preset target stress, the response regulation factor is dynamically adjusted;

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

[0024] According to the update rule, the response regulation factor field is iteratively updated, and the updated factor field is smoothed once;

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

[0026] Further, the expression of the update rule is:

[0027]

[0028] Wherein:

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

[0030] Further, based on the global error minimization principle, the factor field distribution is iteratively optimized to make the overall stress distribution of the filling modified screw in the bone tissue tend to the target state, comprising:

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

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

[0033] terminate the iteration when the overall error falls below a preset proportion of the initial error or the gradient of the overall error is less than a preset threshold value;

[0034] calculating gradient information of the overall error function on the factor field, and adjusting the response control factor value of each node in the negative gradient direction;

[0035] After updating the factor field, the overall stress distribution of the screw is simulated and solved again, and the overall error is recalculated to determine whether the convergence condition is met. If not, the iteration continues, and if met, the iteration is terminated and the final factor field distribution is output.

[0036] Further, the error function is defined as:

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

[0038] wherein:

[0039] J(φ) represents the overall error, Ω represents the calculation domain where the screw is filled, 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 integral volume unit.

[0040] Further, the stress response distribution, strain distribution and mechanical adaptation area of the modified screw filled in the bone tissue are output, which are used to evaluate the fixation performance of the screw under the condition of osteoporosis, including:

[0041] After the finite element simulation is completed, the maximum principal stress, minimum principal stress and equivalent stress data of all element nodes inside the screw are derived, and a three-dimensional spatial distribution map is generated;

[0042] The maximum principal strain, minimum principal strain and equivalent plastic strain distribution of all element nodes in the loading process are extracted;

[0043] According to the final optimized response control factor field distribution, the screw interior is divided into different adaptation level regions;

[0044] The stress response distribution, strain distribution and mechanical adaptation area information are integrated to quantitatively calculate the fixation stability index;

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

[0046] Further, the fixation stability index is calculated by the following method:

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

[0048] wherein:

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

[0050] The filling modification screw mechanical analysis method based on the finite element analysis model has the following beneficial effects:

[0051] By setting the filling structure with stress response adjustment capability inside the screw, the filling material can dynamically adjust its material properties according to the local stress state, effectively relieving 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] The introduction of the response control factor field dynamically models and updates the local adaptation capability of each position inside the filling structure, which can realize spatial continuous adjustment of material properties during simulation, form a flexible transition area and a high stiffness support area in the screw that are highly matched with the stress environment, and significantly improve the mechanical coordination of the overall implantation system.

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

[0054] In summary, the present application can intuitively and systematically reflect the fixation effect of the modified screw in the osteoporosis condition by outputting the stress response distribution, strain distribution and mechanical adaptation area after screw implantation, and quantitatively evaluating based on the comprehensive fixation performance index, providing effective preoperative design basis and postoperative performance evaluation means, and improving the safety and scientificity of screw personalized implantation therapy. BRIEF DESCRIPTION OF DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings described below only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

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

[0057] Next, the preferred description of the application will be made in combination with the drawings and the specific embodiments.

[0058] The present embodiment solves the above problems by the following steps:

[0059] In one embodiment, with reference to Figure 1 The present application provides a filling modified screw mechanical analysis method based on a 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 precisely modeled and simulated by constructing a multi-scale finite element analysis model. Specifically, the method comprises the following steps:

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

[0061] In order to truly and accurately simulate the mechanical behavior of the filling modified screw inside the bone tissue, the modeling must be based on the actual bone structure characteristics of the individual patient. The trabecular structure density, arrangement direction and integrity inside the bone tissue, especially the old brittle bone tissue, have a direct impact on the fixation performance and stress distribution of the screw. Therefore, by acquiring three-dimensional medical image data of a target bone tissue region, and constructing a finite element analysis model of a micro bone trabecular structure and a macro pelvic structure based on the image data, the contribution of the local microstructure to the overall mechanical behavior can be reflected simultaneously at the multi-scale level, significantly improving the accuracy and biological relevance of the mechanical analysis.

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

[0063] Step S101, collecting three-dimensional medical image data, specifically using a multi-row spiral CT or high-resolution MRI device to perform continuous tomographic scanning on the target patient's pelvic region, acquiring complete image data covering the pelvis and surrounding structures, and saving the image data as a DICOM format file.

[0064] Step S102, pre-processing the DICOM format image data, specifically performing image noise removal operation to reduce scanning artifacts, performing gray scale normalization processing to standardize the density range between different patients or devices, and performing slice resampling if necessary to unify the resolution. The optional implementation scheme includes using Gaussian filtering for denoising or using bilinear interpolation method for resampling.

[0065] Step S103, extracting the bone tissue region, specifically setting a density threshold range in the pre-processed image data to separate the bone tissue from the surrounding soft tissue. The optional implementation scheme includes directly using a threshold-based region growing algorithm to extract the bone tissue, or combining a deep learning image segmentation model to finely segment the trabecular bone and cortical bone. For the threshold extraction method, the upper and lower limit gray values can be set to automatically mark all pixel points within the range as bone tissue regions.

[0066] Step S104, constructing a micro trabecular bone structure model, specifically reconstructing a three-dimensional trabecular bone network at high resolution for the extracted bone tissue region, and generating a trabecular bone grid using voxelization method. Voxelization method refers to representing spatially continuous bone tissue as a stack of cubic units, maintaining the true morphology and connectivity of trabecular bone. If the voxel size is set to 100 microns, the trabecular bone morphology can be basically complete.

[0067] Step S105, constructing a macroscopic pelvic structure model, specifically three-dimensionally reconstructing the overall pelvic contour at medium resolution, extracting the sacroiliac joint, pubic symphysis, acetabulum and pelvic ring region, and establishing a macroscopic grid model. For important connection structure regions, the optional implementation scheme includes local grid encryption, i.e. refining the grid units around the sacroiliac joint and pubic symphysis to half of the basic unit size to improve local simulation accuracy.

[0068] Step S106, establishing a multi-scale coupling relationship between the micro and macro structures, specifically transferring the local stiffness parameters of the micro trabecular bone structure units to the macro pelvic structure model units through node mapping method or shape function interpolation method, and setting a bidirectional mechanical feedback path to enable the macro pelvic deformation to affect the stress state of the micro trabecular bone units in the opposite direction. The optional implementation scheme includes direct node position alignment projection or weighted interpolation mapping based on local coordinate system. Node mapping method refers to finding the minimum distance pairing relationship between the micro unit nodes and the macro unit nodes in space to establish the data transmission path.

[0069] By constructing the finite element analysis model of micro trabecular structure and macro pelvic structure based on three-dimensional medical image data respectively, the cross-scale mechanical behavior simulation from local to whole can be realized while maintaining anatomical accuracy, effectively capturing the local failure mechanism of osteoporotic region, accurately evaluating the overall pelvic stability change, significantly improving the accuracy of prediction results and clinical guidance significance in filling modified screw implant simulation analysis, avoiding the stress prediction error and structure stability misjudgment problem caused by traditional homogeneous modeling method, and providing a scientific basis for screw design optimization and individualized treatment plan.

[0070] Exemplarily, taking a 68-year-old female patient with fragile pelvic fracture as an example, the continuous tomographic images of the lumbosacral and acetabular regions are collected by using 64-slice spiral CT scanning technology, the image data is preprocessed by Gaussian filtering and unified resolution, the bone tissue region is extracted by using density threshold method, the high-precision micro finite element model with a voxel size of 100 microns is generated for the internal trabecular structure of the lumbar vertebrae and sacrum, and the medium-resolution three-dimensional reconstruction is performed on the overall pelvic contour, the local encryption grid is set at the sacroiliac joint and pubic symphysis position, the multi-scale coupling relationship of the micro and macro models is established by the node projection method, and the three-dimensional finite element modeling of the patient with fragile pelvic fracture is completed, providing a basis for subsequent filling modified screw implant mechanical analysis.

[0071] Step S20, introducing a filling modified screw structure into the finite element analysis model, the filling modified screw including an internal filling structure with stress response adjustment capability, the filling structure being composed of a responsive material and being capable of dynamically adjusting material performance parameters according to stress distribution around the screw.

[0072] The filling modified screw structure refers to embedding a filling material with variable mechanical properties in the internal or specific area of a traditional metal screw to improve the overall stress state of the screw.

[0073] After the filling modified screw is implanted into the bone tissue, due to different osteoporosis degrees and heterogeneity of micro trabecular structure of individual patients, local stress concentration, shear failure or pull-out failure of the screw may easily occur during the stress process, the traditional homogeneous screw structure cannot dynamically adapt to the local mechanical state according to the change of the implant environment, resulting in insufficient fixation performance or premature failure, therefore, the filling modified screw structure is introduced into the finite element analysis model, the filling structure with stress response adjustment capability is designed in the screw, the filling structure is composed of a responsive material and is capable of dynamically adjusting the elastic modulus, yield strength and other material performance parameters according to the stress field change around the screw, so that the screw exhibits corresponding local stiffness and energy absorption characteristics in different stress regions, realizing implant environment self-adaptation, improving the overall fixation effect and fatigue life.

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

[0075] Step S201, define the geometry of the filling modified screw in the finite element analysis model, specifically design a hollow cavity or partition filling area in the screw body, and layout the filling material to the stress sensitive positions such as screw shaft, thread root or screw head. The optional implementation scheme includes setting a through cylindrical cavity, a segmented multi-cavity structure or a honeycomb filling pattern in the screw.

[0076] Step S202, specify the material properties of the filling area as a responsive material, specifically define the material type of the filling area as a nonlinear material model with stress response adjustment function in the finite element software. The optional implementation scheme includes 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 effective elastic modulus E_eff and the stress field σ(x) can be set as

[0077]

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

[0079] Step S203, establish the contact interface between the filling modified screw and the bone tissue, specifically define 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 as friction contact or adhesive contact. Set the contact friction coefficient or adhesive strength according to the screw implantation depth and bone density. The friction contact model allows relative slip at the interface, and the adhesive contact model is used to simulate the initial stable stage of the screw fixation period.

[0080] Step S204, apply the loading condition and initialize the material performance response, specifically apply the vertical pressure, shear force or torsional load on the screw and bone tissue finite element model according to the actual physiological load of the patient or the standard mechanical loading condition, and activate the filling area material response mechanism at the same time. The material performance parameters are dynamically adjusted with the change of local stress field, and updated to the new mechanical state.

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

[0082] By introducing the filling modified screw structure in the finite element analysis model, and using the internal filling structure with stress response adjustment capability, the screw can automatically adapt to the local stress change under different implantation environments, thereby effectively relieving the stress concentration phenomenon, improving the overall implantation stability, reducing the pull-out failure probability caused by osteoporosis or local bone trabecula destruction, simultaneously realizing energy buffering and crack initiation delay, greatly improving the fatigue life and long-term fixation performance of the modified screw in the complex bone tissue environment, and providing a new technical path for personalized medical implant design.

[0083] Illustratively, the examples following the preceding steps are as follows: after completing the three-dimensional medical image data reconstruction and the pelvic multi-scale finite element model construction, a hollow cavity with a diameter of 1.5 mm is designed to be arranged axially through the screw body, and the filling response material is filled; in the ANSYS software, the filling material is defined as a nonlinear material model with the elastic modulus changing with the local stress gradient, the initial elastic modulus is set to 500 MPa, the response adjustment coefficient is 0.05, and the simulation is carried out by applying the vertical pressure and shear load under the simulated walking state.

[0084] Step S30, a response regulation factor field is constructed, which is used to characterize the local adaptation capability of each position in the filling structure, and the distribution of the factor field is automatically updated according to the stress state change.

[0085] In the present application, the response regulation factor field refers to a spatially continuous distribution field arranged in the filling structure, which is used to describe the material performance adjustment degree, and the value can dynamically change with the local stress state, so as to drive the adaptive adjustment of the material properties. The factor field distribution refers to the spatial continuity arrangement of the response regulation factor values at different spatial positions in the filling region, which is used to describe the spatial adjustment state of the local material properties.

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

[0087] Step S301, initialize the response regulation factor field, specifically, define a factor variable φ at each finite element unit node in the filling region, and set the initial value uniformly as φ_0, which represents the initial material performance state; the initial factor field can be uniformly distributed or assigned with an initial value based on the bone density distribution; the optional implementation scheme includes 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 regulation factor φ according to the deviation Δσ between the stress field σ(x) obtained by the screw and bone tissue simulation at the current step and the preset target stress σ_target, and the update rule is expressed as

[0089]

[0090] wherein, denotes the rate of change of the factor field with respect to time, γ denotes a stress response adjustment coefficient, σ(x) denotes the current stress at position x, σ_target denotes a target stress, β denotes a diffusion smoothing coefficient, denotes the spatial Laplacian value of the factor field, for maintaining the spatial continuity and smoothness of the factor field.

[0091] Step S303, stress state sampling is performed, specifically, after simulating loading each iteration step, the current stress σ(x) of all element nodes in the filling structure is extracted, and the deviation Δσ from the target stress σ_target is calculated.

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

[0093] Step S305, based on the latest response control factor field, the material property parameters of each filling element are updated, specifically, the value of the factor φ is associated with the material constitutive parameters to adjust the local elastic modulus, yield strength or damping parameters, forming a spatially continuous material property distribution.

[0094] Step S306, continue to simulate and solve, and enter the next stress sampling and factor updating cycle until the entire loading history is completed or the convergence condition is met.

[0095] By constructing and dynamically updating the response control factor field, the continuous spatial adjustment of the material properties inside the filling modified screw can be realized, so that the material stiffness and plasticity performance adaptively change during the stress process, effectively relieving 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 the bone tissue interface, significantly enhancing the long-term fixation stability and fatigue life of the implanted system, so as to realize safer and more reliable clinical application effect in osteoporosis or complex stress environment.

[0096] By way of example, as described in the foregoing examples, after completing the finite element modeling of the pelvis and embedding the filling modified screw, the response control factor φ is initialized on each finite element node in the filling area inside the screw, with an initial value of 1.0 and a target stress σ_target set to 30 MPa. During the simulation of the patient's body weight equivalent vertical force, the current stress σ(x) of each node is sampled in real time, the stress deviation is calculated, and the factor field evolution equation is iteratively updated. The response control factor tends to increase in the area with higher stress, so that the local material stiffness is enhanced, and remains at a lower level in the area with lower stress, and finally an elastic modulus distribution highly matched with the local support demand of the bone tissue is formed.

[0097] Step S40, based on the principle of global error minimization, iteratively optimize the distribution of the factor field, so that the overall stress distribution of the filling modified screw in the bone tissue tends to the target state.

[0098] In the present application, the principle of global error minimization refers to evaluating the overall difference between the current stress distribution and the target stress distribution with the overall structure of the screw as the object, gradually reducing the difference through optimization strategy, and making the overall structural performance approach the expected state. The target state refers to the stress or strain distribution standard that the screw is expected to achieve after being implanted in the bone tissue, which is usually set as a certain maximum principal stress threshold or a desired uniform stress field.

[0099] Since the local material properties inside the filling modified screw are dynamically adjusted by the response control factor field, the local stress state changes continuously during the simulation. If only local adjustment is based, the coordination of the overall mechanical properties cannot be guaranteed, and the problem of local over-strengthening or weakening may 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, the distribution of the response control factor field needs to be iteratively optimized based on the principle of global error minimization, and continuously updated and corrected, so that the material properties of each region inside the screw are optimally matched under the overall stress system, thereby achieving the mechanical optimization goal of local adaptation and overall coordination and unity.

[0100] In a specific implementation, the 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 of each node inside the screw and the target stress, and define the overall error function J(φ) as

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

[0103] Where J(φ) represents the overall error, Ω represents the calculation domain of the filling screw, 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 integral volume unit.

[0104] Step S402, calculate the initial overall error, specifically after the initial solution of the simulation, extract the stress values of all nodes inside the screw, and according to the error function formula in step S401, numerically integrate to obtain the initial overall error value J_0.

[0105] Step S403, construct the optimization target and convergence criterion, specifically set the overall error to drop to a certain percentage below the initial error or the overall error gradient to be less than a set threshold to terminate iteration, and the optional implementation scheme includes setting the error to drop 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, and the gradient descent update formula is

[0107]

[0108] wherein φ_new is the updated factor value, φ_old is the factor value of the last step, η is the step size coefficient, is the partial derivative of the overall error to the factor.

[0109] Step S405, after updating the factor field, re-simulate the overall stress distribution of the screw and re-calculate the overall error, and judge whether the convergence condition set in step S403 is met, if not, return to step S404 for iteration, if yes, terminate the iteration and output the final factor field distribution.

[0110] Step S406, take the final optimized response control factor field as the basis for the performance distribution of the filling structure material inside the screw, and complete 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 the local stress abnormality be adjusted locally, but also the material performance inside the screw can be coordinated and unified in the overall range, effectively avoiding the problem of overall mechanical performance degradation caused by local over-reinforcement or softening, improving the overall stress uniformity of the screw and bone tissue interface, reducing the risk of stress concentration, improving the overall stability and long-term durability of the screw after implantation, and providing a systematic and executable optimization path for the design and application of filling modified screws in complex osteoporosis environment.

[0112] By way of example, as described in the foregoing examples, after completing the construction of the pelvis multi-scale finite element model, the implantation of the filling modified screw, the initialization and local adjustment of the response control factor field, the target stress σ_target is set to 30 MPa, the initial overall error J_0 is calculated as 450 MPa square, the factor field distribution is adjusted according to the overall error gradient in each iteration, the step size coefficient η is set to 0.01, and after 8 times of continuous iteration, the overall error is reduced to within 7% of the initial value, the elastic modulus of the filling material inside the screw is automatically improved in the stress concentration area, and the flexibility is maintained in the low stress area, and the simulation results show that the overall principal stress distribution is more uniform.

[0113] Step S50, output the stress response distribution, strain distribution and mechanical adaptation region of the filling modified screw in the bone tissue, for evaluating its fixation performance under osteoporosis condition.

[0114] After completing the response regulation factor field optimization of the filling modified screw, in order to systematically evaluate the fixation effect of the modified screw under osteoporosis condition, it is necessary to output the stress response distribution, strain distribution and mechanical adaptation region of the modified screw inside the bone tissue, through comprehensive analysis of stress uniformity, local strain concentration and material adaptation characteristics, to evaluate the stability and safety of the screw after implantation, therefore, through the simulation result post-processing stage, the system outputs various mechanical response data, which can provide basis for screw design improvement and clinical implantation strategy optimization, and at the same time verify the applicability and effectiveness of the proposed method to actual osteoporosis patients.

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

[0116] Step S501, 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 element nodes inside the screw are derived, a three-dimensional space distribution map is generated, and optional implementation schemes include displaying the stress range in the form of a color-coded cloud chart, or extracting key cross sections for two-dimensional slice analysis.

[0117] Step S502, extract the strain distribution, specifically, extract the maximum principal strain, minimum principal strain and equivalent plastic strain distribution of all element nodes during the loading process, if necessary, derive the strain evolution sequence according to different time steps to evaluate the local deformation accumulation trend, and optional implementation schemes include drawing a strain vector field or generating a cumulative deformation animation sequence.

[0118] Step S503, identify the mechanical adaptation region, specifically, according to the response regulation factor field distribution after the final optimization, divide the screw inside into different adaptation level regions, such as high stiffness adaptation zone, medium adaptation zone and flexible transition zone, and optional implementation schemes include setting factor threshold intervals for automatic partitioning, or using clustering algorithm to identify continuous adaptation region.

[0119] Step S504, evaluate the fixation performance index, specifically, comprehensively analyze the stress response distribution, strain distribution and mechanical adaptation region information, quantitatively calculate the fixation stability index, including but not limited to maximum principal stress peak value, maximum principal strain peak value, stress concentration coefficient, fixed region displacement amplitude, if necessary, define a comprehensive fixation performance score formula, an example formula is as follows

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

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

[0122] In step S505, a comprehensive analysis report is output, specifically, the screw stress distribution graph, the strain distribution graph, the adaptive region division graph and the fixed performance score are summarized into a standardized technical report as a reference for subsequent optimization design or clinical implantation decision.

[0123] In this step, by outputting the stress response distribution, strain distribution and mechanical adaptation region of the filling modified screw in the bone tissue, and based on the comprehensive fixation performance index, the stability, adaptability and safety of the screw after implantation can be intuitively and quantitatively reflected, the potential failure risk can be effectively identified, the self-adaptive regulation effect of the filling structure can be verified, the screw design optimization and individualized treatment plan can be guided, and the clinical application effect and long-term reliability of the implanted body of the osteoporosis patient can be significantly improved.

[0124] Illustratively, according to the foregoing examples, after completing the three-dimensional finite element modeling of the pelvis, the implantation of the filling modified screw and the factor field optimization, the maximum principal stress distribution cloud chart of the screw is output, it is found that the maximum principal stress in the stress concentration area is 28 MPa, which is lower than the set target upper limit of 30 MPa, the strain distribution graph shows that the maximum principal strain is 0.45%, which is within the safe deformation range, and three types of mechanical adaptation regions are divided according to the final response regulation factor field, the high stiffness adaptation region is mainly distributed in the thread root and the connected bone dense area, the flexible transition area is distributed in the middle section of the screw, and the comprehensive fixed performance score FPS calculation result is 0.82, which indicates that the modified screw has good fixation stability and biomechanical adaptability under the condition of osteoporosis of this patient.

[0125] The prior art mentioned in the foregoing background section and the specific embodiment section can be used as part of the present application to understand the meaning of some technical features or parameters.

Claims

1. A method for analyzing the mechanics of a fill-modified screw based on a finite element analysis model, characterized by, The method comprises the following steps: Obtain three-dimensional medical image data of the target bone tissue region, and construct a finite element analysis model of the micro trabecular structure and the macro pelvic structure based on the three-dimensional medical image data; Introduce a filling modified screw structure into the finite element analysis model, the screw comprising an internal filling structure with stress response adjustment capability, the filling structure being composed of a responsive material and capable of dynamically adjusting its material performance parameters according to the stress distribution around the screw; Construct a response control factor field for characterizing the local adaptation capability of each position in the filling structure, and automatically update the distribution of the factor field according to the stress state change; Iteratively optimize the distribution of the factor field based on the global error minimization principle, so that the overall stress distribution of the filling modified screw in the bone tissue tends to the target state; Output the stress response distribution, strain distribution and mechanical adaptation region of the filling modified screw in the bone tissue for evaluating the fixation performance of the screw under the condition of osteoporosis. Construct a micro trabecular structure model, specifically, for the extracted bone tissue region, reconstruct a three-dimensional trabecular network at a high resolution, and generate a trabecular grid using a voxelization method. Construct a macro pelvic structure model, specifically, perform three-dimensional reconstruction on the overall pelvic contour at a medium resolution, extract the sacroiliac joint, pubic symphysis, acetabulum and pelvic ring region, and establish a macro grid model. The response control factor field refers to a spatially continuous distribution field set in the filling structure, which is used to describe the degree of material performance adjustment. The mechanical adaptation region is divided into different adaptation level regions according to the distribution of the response control factor field after final optimization.

2. The finite element analysis model-based filling-modified screw mechanics analysis method according to claim 1, characterized by, The step of obtaining three-dimensional medical image data of the target bone tissue region comprises: Use a multi-slice spiral CT or high-resolution MRI device to perform continuous tomographic scanning on the target pelvic region, collect complete three-dimensional image data covering the sacroiliac joint, acetabulum and pubic symphysis region, save the collected image data as DICOM format files, perform image noise removal processing on the DICOM format image data to eliminate artifacts, perform gray scale normalization processing to standardize the density range of different device data, and use bilinear interpolation or cubic spline interpolation method to resample the image to unify the isotropic resolution.

3. The finite element analysis model-based filling-modified screw mechanics analysis method of claim 1, wherein, The step of constructing a finite element analysis model of the micro trabecular structure and the macro pelvic structure based on the three-dimensional medical image data comprises: Use a density threshold segmentation method to extract the bone tissue region, set the threshold range to adapt to the different density characteristics of the trabecular bone and cortical bone, extract the trabecular bone region and the overall pelvic contour respectively, use voxelization modeling for the trabecular bone region to generate a micro finite element grid with a voxel unit size less than or equal to 100 microns, and use surface reconstruction and grid division for the overall pelvic region, and perform local grid densification processing in the sacroiliac joint, pubic symphysis connection region, so that the unit size is less than half of the surrounding area.

4. The finite element analysis model-based filling-modified screw mechanics analysis method of claim 1, wherein, The step of introducing a filling modified screw structure into the finite element analysis model comprises: Design a hollow cavity or partition filling area in the screw body, and layout the filling material to the stress sensitive positions of the screw shaft, thread root or screw head. Defining the material type of the filling region as a nonlinear material model with stress response adjustment function in the finite element software; Defining the contact relationship between the outer surface of the screw and the bone tissue model in the finite element model, setting the contact type as frictional contact or bonded contact, setting the contact friction coefficient or bonded strength according to the screw implantation depth and bone density, and allowing relative slip at the interface in the frictional contact model; According to the actual physiological load of the patient or the standard mechanical loading condition, vertical pressure, shear force or torsional load is applied on the screw and bone tissue finite element model, and the material response mechanism of the filling region is activated, the material performance parameters are dynamically adjusted according to the local stress field, and the mechanical state is updated to a new one.

5. The finite element analysis model-based filling-modified screw mechanics analysis method according to claim 1, characterized by, The construction of the response regulation factor field includes: Defining a factor variable at each finite element node in the filling region and initializing it; According to the deviation between the stress field obtained by the current step simulation of the screw and the bone tissue and the preset target stress, the response regulation factor is dynamically adjusted; After simulating each iteration step, the current stress of all element nodes in the filling structure is extracted, and the deviation from the target stress is calculated; According to the update rule, the response regulation factor field is iteratively updated, and the updated factor field is smoothed once; Based on the latest response regulation factor field, the material performance parameters of each filling element are updated.

6. The finite element analysis model-based filling-modified screw mechanics analysis method according to claim 5, characterized by, The expression of the update rule is: φ / t = γ × (σ(x) - σ_target) + β × 2 φ, Wherein: φ / t represents the rate of change of the factor field with respect to time; γ represents a stress response adjustment coefficient, σ(x) represents the current stress at position x, σ_target represents a target stress, β represents a diffusion smoothing coefficient, 2 φ represents the spatial Laplacian value of the factor field.

7. The finite element analysis model-based fill-modified screw mechanics analysis method of claim 1, wherein, Based on the global error minimization principle, the factor field distribution is iteratively optimized, so that the overall stress distribution of the filling modified screw in the bone tissue tends to the target state, which includes: Setting the overall error evaluation index in the finite element simulation environment, integrating and accumulating the difference between the current stress of each node in the screw and the target stress; After the initial solution of the simulation, the stress values of all nodes in the screw are extracted, and the initial overall error value is obtained by numerical integration according to the error function formula; Setting the overall error to drop to a preset proportion of the initial error or the overall error gradient to be less than a set threshold to terminate the iteration; The gradient information of the overall error function to the factor field is calculated, and the response regulation factor value of each node is adjusted along the negative gradient direction; After updating the factor field, the overall stress distribution of the screw is simulated and solved again, and the overall error is calculated again to determine whether the convergence condition is met. If not, continue iteration; If it is met, terminate the iteration and output the final factor field distribution.

8. The finite element analysis model-based filling-modified screw mechanics analysis method according to claim 7, characterized by The error function is defined as: J(φ) = ∫ Ω (σ_current(x) - σ_target(x)) 2 dx, Wherein: J(φ) represents the overall error, Ω represents the calculation domain of the filling screw, 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 integral volume element.

9. The finite element analysis model-based filling-modified screw mechanics analysis method according to claim 7, characterized by, The stress response distribution, strain distribution and mechanical adaptation region of the filling modified screw in the bone tissue are output for evaluating its fixation performance under osteoporosis conditions, which include: After the finite element simulation is completed, the maximum principal stress, minimum principal stress and equivalent stress data of all element nodes in the screw are exported, and a three-dimensional spatial distribution map is generated; The maximum principal strain, minimum principal strain and equivalent plastic strain distribution of all element nodes in the loading process are extracted; Based on the final optimized response control factor field distribution, the interior of the screw is divided into regions with different fitting levels; Based on the comprehensive stress response distribution, strain distribution, and mechanical adaptation region information, quantitative calculation of the fixed stability index is performed. The screw stress distribution diagram, strain distribution diagram, fit area division diagram, and fixing performance score are compiled into a standardized technical report.

10. The finite element analysis model-based fill-modified screw mechanics analysis method of claim 9, wherein, 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 in the fixed zone, Δd_target is the displacement control target, and w1, w2, and w3 are the weighting coefficients of each index, which are set according to the actual application requirements.

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