Skull repair implant material parameter configuration method and system

Abstract

The invention relates to the technical field of medical data processing, in particular to a skull repair implant material parameter configuration method and system, and the method comprises the following steps: obtaining the image data of a skull defect area, and determining the boundary information of skull defect based on the image data; according to the boundary information, obtaining physical attribute information of own bones adjacent to the boundary, and based on the physical attribute information, evaluating the bone regeneration capacity of an area adjacent to the boundary; determining skeleton regeneration potential distribution of each position in the skull defect area according to the skeleton regeneration capacity of the area adjacent to the boundary; performing unit division on the skull implant, and obtaining skeleton regeneration potential information corresponding to each unit of the implant according to the skeleton regeneration potential distribution; according to bone regeneration potential distribution of all positions in a skull defect area, material parameters of all units of the implant are finely configured, and precise matching of the degradation rate of the implant and the growth process of new bone tissue is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of medical data processing, and in particular to a skull repair implant material parameter configuration method and system. BACKGROUND

[0002] Skull repair is a key means for treating skull defects caused by trauma, tumor resection, etc. Traditional skull repair uses biologically inert materials such as titanium alloy and PEEK, which can provide immediate mechanical support, but long-term use can cause a "stress shielding" effect. Because the stiffness of the implant is much higher than that of the human skeleton, it will bear most of the external force on the head, causing the edge of the implant to lack mechanical stimulation of the skeleton, which can cause bone loss, atrophy, and other long-term complications such as interface loosening and implant failure.

[0003] To overcome the problem of stress shielding, existing technology has designed a gradient mechanical property implant, i.e., the center has high stiffness and the edge near the self-skeleton has low stiffness, to achieve a smooth transition in mechanical properties. However, this static design does not take into account the dynamic characteristics of the organism, and the ideal goal of skull defect repair is to guide the regeneration of the self-skeleton and achieve in-situ healing. Based on this goal, the new generation of skull repair materials has shifted to biodegradable and absorbable materials such as polycaprolactone (PCL) or polylactic acid (PLA). The design concept of this type of material is to serve as a temporary mechanical support and guide template in the early stages of healing, gradually degrade and be absorbed over time, and the space occupied by it is then filled with newly formed bone tissue, ultimately achieving regenerative repair without implants. However, this dynamic repair strategy brings new complexities. The repair system has two related and opposite dynamic processes: one is the degradation of the implant leading to a decrease in mechanical properties, and the other is the growth of new bone tissue leading to an increase in mechanical properties. To ensure that the defect area has sufficient mechanical integrity throughout the repair period, the speeds of these two processes need to be precisely matched.

[0004] Furthermore, in a real physiological environment, the regeneration process of bone tissue is extremely uneven in space. In a larger skull defect area, the healing potential at different locations is significantly different. For example, areas close to the lamina cribrosa or dura mater have good blood supply and abundant osteoblasts, and bone regeneration is fast; the center of the defect is far from the blood supply and healing is slow. This causes the mechanical strength of the newly formed bone to gradually form in irregular patches in the defect area. At the same time, the degradation process of the implant material may not be completely uniform, as it is influenced by the local microenvironment (such as pH, enzyme concentration, body fluid flow), which is itself related to cell metabolism and healing process.

[0005] This makes the parameter configuration task of degradable implants extremely difficult. In the prior art, when designing degradable implants, the overall and average material degradation and bone healing speed are often configured. However, this method is difficult to cope with the challenge of inconsistent growth speed of new bone tissue in the skull defect area. If the differentiated healing potential of different positions in the defect area cannot be evaluated and the implant is finely configured based on this, the implant in some areas may be decomposed too early, lose its function when the new bone has not provided sufficient support, and form a mechanical weak point; in other areas where healing is rapid, the implant degrades too slowly, and its residual structure continues to hinder the further maturation and remodeling of the new bone, ultimately affecting the quality of repair and the recovery of function.

[0006] The prior art needs to be improved in view of the above problems. SUMMARY

[0007] The purpose of the present application is to solve the problems existing in the prior art and provide a skull repair implant material parameter configuration method and system.

[0008] In a first aspect, the present application provides a skull repair implant material parameter configuration method, which comprises the following steps: Obtain image data of a skull defect area, and determine boundary information of the skull defect based on the image data; According to the boundary information, obtain physical attribute information of the boundary-adjacent self-bone, and evaluate the bone regeneration ability of the boundary-adjacent area based on the physical attribute information; According to the bone regeneration ability of the boundary-adjacent area, determine the bone regeneration potential distribution of each position in the skull defect area; Divide the skull implant into units, and obtain the bone regeneration potential information corresponding to each unit of the implant according to the bone regeneration potential distribution; According to the bone regeneration potential information of each unit of the implant, determine the material degradation rate of each unit of the implant; Adjust the material structure parameters of each unit of the implant to realize the material degradation rate; Generate manufacturing instructions for manufacturing the implant.

[0009] In a second aspect, a skull repair implant material parameter configuration system is provided, which comprises: An information acquisition module is configured to obtain image data of a skull defect area, and determine boundary information of the skull defect based on the image data; A regeneration ability evaluation module is configured to obtain physical attribute information of the boundary-adjacent self-bone according to the boundary information, and evaluate the bone regeneration ability of the boundary-adjacent area based on the physical attribute information; The potential distribution determination module is used to determine the bone regeneration potential distribution at each location within the skull defect area based on the bone regeneration capacity of the region adjacent to the boundary. The unit information acquisition module is used to divide the skull implant into units and, based on the bone regeneration potential distribution, acquire the bone regeneration potential information corresponding to each unit of the implant. The degradation rate determination module is used to determine the material degradation rate of each unit of the implant based on the bone regeneration potential information of each unit of the implant. The parameter configuration module is used to adjust the material structure parameters of each unit of the implant according to the material degradation rate of each unit of the implant; The instruction generation module is used to generate manufacturing instructions for manufacturing the implant.

[0010] Compared with the prior art, the present invention has the following beneficial effects: By precisely configuring the material parameters of each unit of the implant according to the distribution of bone regeneration potential at various locations within the skull defect area, the degradation rate of the implant and the growth process of new bone tissue can be accurately matched. This effectively avoids mechanical weaknesses or obstacles to new bone maturation caused by degradation mismatch in traditional methods, and significantly improves the quality and long-term effect of skull repair. Attached Figure Description

[0011] Figure 1 This is a flowchart of the method of the present invention.

[0012] Figure 2 This is a schematic diagram of the system structure of the present invention.

[0013] In the diagram: 201, Information Acquisition Module; 202, Regeneration Capacity Assessment Module; 203, Potential Distribution Determination Module; 204, Unit Information Acquisition Module; 205, Degradation Rate Determination Module; 206, Parameter Configuration Module; 207, Instruction Generation Module. Detailed Implementation

[0014] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0015] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0016] like Figure 1 The method for configuring parameters of cranioplasty implant materials, as shown, includes the following steps: S101. Obtain image data of the skull defect area and determine the boundary information of the skull defect based on the image data; S102. Based on the boundary information, obtain the physical attribute information of the self-bones adjacent to the boundary, and evaluate the bone regeneration capacity of the region adjacent to the boundary based on the physical attribute information. S103. Based on the bone regeneration capacity of the area adjacent to the boundary, determine the distribution of bone regeneration potential at each location within the skull defect area; S104. Divide the skull implant into units and obtain the bone regeneration potential information corresponding to each unit of the implant based on the distribution of bone regeneration potential. S105. Determine the material degradation rate of each implant unit based on the bone regeneration potential information of each implant unit. S106. By adjusting the material structure parameters of each unit of the implant, the material degradation rate is achieved; S107. Generate manufacturing instructions for manufacturing implants.

[0017] Imaging data refers to data reflecting the morphology and internal structure of the skull defect area. This data can be obtained using computed tomography (CT) scans, magnetic resonance imaging (MRI), or ultrasound imaging. The purpose is to acquire three-dimensional geometric information of the skull defect area, providing a foundation for subsequent analysis and design. Boundary information refers to the geometric contour data of the skull defect area, which can be represented as a series of three-dimensional coordinate points or a closed set of curves. Its purpose is to define the area requiring repair, providing geometric parameters for subsequent bone regeneration capacity assessment and implant design. Physical property information refers to data reflecting the mechanical or biological characteristics of the bone itself. This can be characterized using parameters such as bone mineral density (BMD), bone stiffness, or bone chemical composition. Its purpose is to quantify the condition and regenerative capacity of the bone adjacent to the boundary. Bone regeneration capacity refers to the potential of the bone in the adjacent area to promote new bone formation and growth. This can be assessed based on physical property information, such as by analyzing BMD values. Its purpose is to provide a biological basis for subsequently determining the distribution of bone regeneration potential at various locations within the skull defect area. The bone regeneration potential distribution refers to the spatial mapping of the expected bone regeneration rate or potential level at different locations within the skull defect area. It can be represented as a three-dimensional voxel grid, where each voxel corresponds to a regeneration potential value. Its purpose is to provide an understanding of the healing prospects of the entire defect area and guide the differentiated design of implants. Unit partitioning refers to decomposing the three-dimensional digital model of the skull implant into multiple independently controllable regions. The size and shape of the units can be determined based on the precision of the additive manufacturing equipment or the characteristics of the bone regeneration potential distribution, aiming to configure parameters for different regions of the implant. The material degradation rate refers to the rate at which the implant material decomposes and is absorbed within the body. It can be determined based on bone regeneration potential information, for example, by establishing a correspondence table or mapping function. Its purpose is to enable personalized degradation of the implant according to the bone regeneration needs of different regions. Material structural parameters refer to the microscopic or macroscopic structural characteristics that affect the degradation behavior of the implant material. These can include porosity, pore size, internal lattice structure type, or material ratio, etc. The purpose is to control the degradation rate of the material through physical structure adjustments, thereby achieving a preset degradation rate.

[0018] The core innovation of this application lies in matching the distribution of bone regeneration potential at various locations within the skull defect area with the material degradation rate of each implant unit. This solves the problem of asynchronous implant degradation and new bone growth in traditional methods, ensuring the mechanical integrity of the repaired area throughout the healing cycle. The working principle is as follows: First, the system acquires image data of the skull defect area and determines the boundary information of the skull defect based on this data. This initial step is fundamental to understanding the geometry of the defect, providing spatial localization for subsequent biological assessment. Next, based on the determined boundary information, the system extends outward to the adjacent bone to obtain its physical properties. These physical properties, such as bone density, directly reflect the condition and metabolic activity of the bone in that area. Based on these physical properties, the system can assess the bone regeneration capacity of the adjacent area, thus providing a basis for subsequent healing potential prediction. Furthermore, based on the bone regeneration capacity of the adjacent area, the system uses spatial interpolation or mapping algorithms to extend these local assessment results to the entire skull defect area, thereby determining the distribution of bone regeneration potential at various locations within the skull defect area. This distribution map illustrates the rate of bone regeneration at different locations within the defect area, which is crucial for achieving personalized repair. Subsequently, to apply this spatialized biological information to implant design, the system divides the cranial implant into units, decomposing it into multiple independently controllable regions. For each unit in the implant, the system queries its corresponding location on the bone regeneration potential distribution map to obtain the bone regeneration potential information for that unit. Further, based on the bone regeneration potential information obtained for each unit of the implant, the system establishes a correspondence between bone regeneration potential and material degradation rate, thereby determining the required material degradation rate for each unit of the implant. This step ensures that the "disappearance" rhythm of the implant at different locations matches the "growth" rhythm of newly formed bone at the corresponding locations. To achieve these differentiated degradation rates, the system controls the material degradation behavior by adjusting the material structural parameters of each unit of the implant, such as changing porosity or internal lattice structure. This adjustment of structural parameters is the physical means to achieve the preset degradation rate. Ultimately, the system translates all these spatialized material structural parameters into manufacturing instructions for implant fabrication. These instructions can be recognized and executed by additive manufacturing equipment to produce skull implants with customized degradation properties. The entire process forms a closed loop, starting with the patient's imaging data, through biological assessment, spatial mapping, implant design and parameter configuration, and finally generating executable manufacturing instructions. This ensures that the implant can dynamically adapt to the individualized bone regeneration process, thereby maintaining the structural integrity of the repaired area throughout the healing cycle.

[0019] As one embodiment of the present invention, the step of determining the distribution of bone regeneration potential at various locations within a skull defect area based on the bone regeneration capacity of the adjacent region includes: Identify areas on the boundary that are susceptible to image artifacts; For areas susceptible to image artifacts, analyze the distribution of pixel values ​​within the area, obtain the numerical range representing the real bone signal in the distribution, and determine the physical attribute information of the bone adjacent to the boundary based on the numerical range. For areas not susceptible to image artifacts, conventional measurement methods are used to obtain the physical property information of the skeleton near the boundary. Based on the acquired physical property information, assess the bone regeneration capacity of the region adjacent to the boundary; Based on the assessed bone regeneration capacity, the distribution of bone regeneration potential at various locations within the skull defect area is determined.

[0020] Among them, the area susceptible to image artifacts refers to the local range where, during medical image acquisition, minute patient movements or drastic changes in tissue density cause non-realistic deviations in image pixel values. This can be identified through curvature analysis of the boundary geometry or by using image gradient and edge detection algorithms. The numerical range representing the true bone signal refers to the pixel value intervals within the image artifact-affected area, identified and extracted through statistical analysis of pixel grayscale values. These intervals accurately reflect the true density or compositional characteristics of bone tissue and can be obtained using methods such as histogram analysis, peak detection, or Gaussian mixture model fitting. Physical property information refers to the objective measurable characteristics of bone, such as bone density, bone mineral content, or trabecular bone structure parameters. This can be expressed using Heinz units (H). Bone density can be quantified using the U-value, or the trabecular structure can be characterized through texture analysis. Conventional measurement methods refer to obtaining bone physical property information by using standardized and direct image pixel value calculation methods in areas not significantly affected by image artifacts. These methods can be calculated using simple arithmetic mean or regional average gray value. Bone regeneration capacity refers to the ability of bone tissue to self-repair and form new bone after damage. It can be assessed based on the physical property information of the bone, combined with known biological models or empirical correspondences. Bone regeneration potential distribution refers to the spatial mapping of the expected regeneration rate or regeneration intensity of bone tissue at different locations within the skull defect area. It can be represented as a three-dimensional voxel grid or a continuous function. Spatial interpolation algorithms can be used to extend the regeneration capacity at the boundary to the entire defect area.

[0021] This application's solution improves the accuracy of the entire cranioplasty implant material parameter configuration method by optimizing the determination of bone regeneration potential distribution at various locations within the cranioplasty defect area. Specifically, after acquiring image data of the cranioplasty defect area and determining boundary information, the solution first identifies regions on the boundary that are susceptible to image artifacts. This is because image artifacts typically appear at bone edges or in areas with drastic density changes. By identifying these regions, targeted subsequent processing can be performed, avoiding indiscriminate processing of all regions. For these regions susceptible to image artifacts, the solution further analyzes the distribution of pixel values ​​within the region, obtains the numerical range representing the true bone signal in the distribution, and determines the physical property information of the adjacent bone based on this numerical range. Image artifacts alter pixel values, leading to inaccurate physical property information obtained through direct measurement. By analyzing the pixel value distribution, the interference of artifacts can be eliminated, and the true physical property information of the bone can be obtained more accurately. Simultaneously, for regions not susceptible to image artifacts, the solution uses conventional measurement methods to obtain the physical property information of the adjacent bone. In areas free from artifact interference, conventional measurement methods are sufficiently accurate, requiring no additional processing and simplifying the calculation process. Subsequently, based on the acquired physical property information, the scheme assesses the bone regeneration capacity in the vicinity of the boundary. Bone physical properties are closely related to its regeneration capacity; this capacity can be inferred from physical property information. Finally, based on the assessed bone regeneration capacity, the scheme determines the distribution of bone regeneration potential at various locations within the skull defect area. The distribution of bone regeneration potential is influenced by multiple factors, including bone physical properties and blood supply; by comprehensively considering these factors, the distribution of bone regeneration potential can be determined more accurately. Through the aforementioned differentiated processing strategies, this scheme can more accurately assess bone regeneration capacity, thus providing a more reliable basis for subsequent implant design. This improvement enables the determination of the degradation rate of each unit material in the cranioplasty implant material parameter configuration method based on more precise bone regeneration potential information, thereby achieving a precise spatial and temporal coordination between the reduction of implant mechanical properties and the enhancement of new bone tissue mechanical properties, effectively addressing the challenge of CT scan artifacts to the accuracy of healing potential assessment.

[0022] As one embodiment of the present invention, the step of controlling the material degradation rate by adjusting the material structure parameters of each unit of the implant includes: Degradable biomaterials with differentiated degradation behaviors are selected, and the degradation rate of one of the materials responds to local biological signals; Based on the bone regeneration potential information of each implant unit, determine the material ratio in each implant unit; Based on the bone regeneration potential information of each unit of the implant, determine the porosity or internal structure of each unit of the implant. By adjusting the material structure parameters of each unit of the implant, including adjusting the material ratio, porosity, or internal structure, the actual degradation rate of each unit of the implant can be adjusted according to local biological signals, thereby compensating for the impact of structural deviations during the manufacturing process on the preset degradation rate.

[0023] The selection of biodegradable biomaterials with differentiated degradation behavior refers to at least two or more biodegradable biomaterials that exhibit different degradation rates, degradation mechanisms, or response characteristics to external stimuli under physiological conditions. This can be achieved by selecting materials with different chemical compositions, molecular weights, crystallinity, or surface modifications. The aim is to provide implants with multi-dimensional degradation regulation capabilities, laying the material foundation for subsequent adaptive degradation mechanisms. One material's degradation rate responding to local biological signals means that in the aforementioned differentiated degradation material system, at least one material's degradation rate is not fixed but dynamically adjusted according to changes in specific biological indicators in its microenvironment. This can be achieved by introducing chemical bonds or structures sensitive to specific biomolecules into the material; when these biomolecules reach a certain concentration, the material's degradation is accelerated or slowed down. Alternatively, the material can respond to changes in local ion concentration, pH value, or redox potential, thereby altering its degradation kinetics. The goal is to endow implants with dynamic responsiveness, enabling their degradation process to dynamically match the actual bone regeneration process in vivo, improving the accuracy and reliability of repair. Based on the bone regeneration potential information of each implant unit, the material ratio in each implant unit is determined. This refers to the relative content or proportion of different types of biodegradable biomaterials in each implant unit. Specifically, it can be expressed as weight percentage, volume percentage, or molar percentage. During the manufacturing process, it can be adjusted by precisely controlling the mixing ratio of different material powders or the extrusion amount during multi-material printing. The purpose is to regulate the overall degradation rate and mechanical performance decay curve of each implant unit by adjusting the relative content of materials with different degradation characteristics, so as to adapt to the bone regeneration potential of different regions. Based on the bone regeneration potential information of each implant unit, the porosity or internal structure of each implant unit is determined. This refers to the proportion of the void volume inside the implant material to the total volume, as well as the arrangement, shape, size, and connectivity of these voids. The specific porosity can be achieved by adjusting additive manufacturing parameters or by introducing pore-forming agents. The internal structure can manifest as a lattice structure, a porous scaffold, or a fiber network, etc. Its specific morphology can be realized through computer-aided design and 3D printing technology. The purpose is to further regulate the degradation rate and mechanical properties of each implant unit by changing the contact area between the material and the surrounding tissue, the permeation path of body fluids, and the mechanical transmission characteristics, while providing space for cell growth and blood vessel ingrowth.By adjusting the material structure parameters of each unit of the implant, including the material ratio, porosity, or internal structure, the actual degradation rate of each unit can be regulated according to local biological signals. This means that when the implant degrades in vivo, its actual degradation rate can be automatically adjusted according to changes in the biological microenvironment at its location, rather than strictly following a preset fixed rate. Specifically, this is usually achieved through the aforementioned material properties that respond to local biological signals. When the local biological signal reaches a certain level, the degradation of the responsive material is accelerated or slowed down, thereby affecting the degradation rate of the entire unit. The purpose is to compensate for possible structural deviations during the manufacturing process and to cope with the complex and ever-changing physiological environment in vivo, ensuring that the degradation of the implant and the growth of new bone tissue are dynamically synchronized, thereby improving the adaptability and success rate of repair.

[0024] Specifically, this approach first selects biodegradable biomaterials with differentiated degradation behaviors, one of which degrades in response to local biological signals. This means the implant is no longer a single homogeneous material, but rather composed of at least two materials with different properties: one that provides stable mechanical support and degrades at a relatively constant rate, and another that senses and responds to specific biological signals generated by newly formed bone tissue during growth. The introduction of this material system provides a basis for the implant to dynamically regulate its own degradation behavior. Based on this, the approach precisely determines the material ratios in each implant unit according to the bone regeneration potential information of each unit. In areas with high bone regeneration potential, a higher proportion of materials responding to local biological signals can be configured, aiming to allow the implant to degrade more quickly and make room for rapid new bone growth. Conversely, in areas with low bone regeneration potential, the proportion of materials providing stable support can be increased to ensure that the implant provides mechanical support for a longer period during slow bone regeneration. Simultaneously, the approach also determines the porosity or internal structure of each implant unit based on the bone regeneration potential information. Porosity and internal structure directly affect the contact area between the material and surrounding tissues, as well as fluid permeability, thereby further regulating the material's degradation rate. For example, high porosity and open structures can accelerate degradation, while low porosity and dense structures can slow it down. Through the aforementioned material ratios and adjustments to porosity or internal structure, the material structure parameters of each implant unit are precisely configured. More importantly, this configuration allows the actual degradation rate of each implant unit to be adjusted according to local biological signals. For instance, when new bone tissue actively grows and secretes specific biomolecules, the degradation of responsive materials is accelerated, compensating for any potential deviations in slow degradation; conversely, if new bone tissue growth is slow, the degradation of responsive materials will also slow down accordingly, ensuring that the implant does not fail prematurely. This adaptive adjustment capability allows the implant to overcome structural deviations during manufacturing and the complexity of the in vivo microenvironment, ensuring that the weakening of its mechanical properties and the enhancement of the mechanical properties of new bone tissue are truly synchronized spatially and temporally. This complements the basic approach. The basic approach achieves spatial differentiation and temporal pre-setting of implant degradation by pre-assessing bone regeneration potential and determining material degradation rates. However, the limitation of the basic approach is that its degradation behavior is relatively fixed, making it difficult to cope with manufacturing deviations and dynamic changes in vivo. This approach, building upon the pre-set basic design, introduces adaptive capabilities, allowing the implant to be fine-tuned according to actual biological processes. This combination enables the implant to be designed macroscopically based on the healing potential of different areas, and to dynamically compensate at the microscopic level based on real-time biological signals. This improves the reliability and success rate of cranioplasty, ensuring that the defect area maintains sufficient structural integrity throughout the entire repair cycle.

[0025] As one embodiment of the present invention, the step of enabling the actual degradation rate of each unit of the implant to be adjusted according to local biological signals includes: Identify local biosignals that indicate the growth process of new bone tissue. These local biosignals include biomolecules or their metabolites secreted by new bone tissue, or changes in local ion concentrations that reflect the bone mineralization process. The implant is designed with responsive materials in each unit, whose degradation behavior is influenced by recognized local biosignals. The responsive materials contain chemical bonds that can be cleaved by enzymes specific to newly formed bone tissue, or their degradation rate is affected by changes in local ion concentration. Set a degradation threshold for responsive materials so that the degradation behavior of responsive materials is only significantly accelerated when biomolecules or metabolites reach a specific concentration that reflects the maturation of bone tissue. By incorporating local biosignals into the degradation behavior of responsive materials and setting degradation thresholds, the actual degradation rate of each implant unit can be adjusted according to local biosignals.

[0026] Identifying local biosignals indicating the growth process of new bone tissue refers to acquiring and analyzing biological information within the skull defect area that reflects the formation and maturation of new bone tissue. This can be achieved by using implant-embedded sensors to monitor changes in the local microenvironment in real time, or by analyzing the concentration of biomarkers in the local tissue fluid. The aim is to monitor the dynamic process of bone healing in real time, providing a basis for adaptive adjustment of the implant degradation rate. Local biosignals include biomolecules or their metabolites secreted by new bone tissue, or changes in local ion concentrations reflecting the bone mineralization process. These include chemical substances produced by new bone tissue during growth, differentiation, and mineralization, such as proteins like osteocalcin and osteopontin, or their degradation products, as well as ions like calcium and phosphate ions whose concentrations change during bone mineralization. The purpose is to provide biological indicators that directly reflect the degree of bone tissue regeneration and maturation, serving as a basis for regulating implant degradation. In this context, designing responsive materials for each unit of the implant refers to constructing a material system capable of sensing and altering its degradation behavior in response to local biological signals. This can be achieved by embedding bioactive molecules or nanoparticles into a material matrix, allowing them to release or alter the material structure in a biological environment, or by chemically modifying the material surface to induce a specific reaction with biological signals. The aim is to make the degradation of the implant no longer linear, but rather regulated according to changes in local biological signals. Specifically, responsive materials contain chemical bonds that can be cleaved by enzymes specifically secreted by newly formed bone tissue, or their degradation rate is affected by changes in local ion concentration. This means introducing chemical bonds into the material's molecular chain that can be recognized and broken by enzymes specifically secreted by newly formed bone tissue, or the material's degradation rate changing with increases or decreases in local calcium ion, phosphate ion, etc. The goal is to enable the material to respond to biological signals, thereby achieving precise control of the degradation rate. Setting a degradation threshold for responsive materials refers to setting a trigger condition or critical point for the degradation behavior of responsive materials. For example, the degradation rate of the material will only accelerate significantly when the concentration of local biomolecules or metabolites reaches a preset specific value. The purpose is to avoid premature degradation of the implant and ensure that the implant only begins to degrade rapidly after the new bone tissue has reached maturity, thereby providing long-term mechanical support.

[0027] This application proposes a method that identifies local biosignals indicating the growth process of new bone tissue and designs responsive materials whose degradation behavior is influenced by these signals. A degradation threshold is also set, allowing the actual degradation rate of each unit of the implant to be adjusted according to local biosignals. Specifically, during cranioplasty, bone regeneration is not uniform but exhibits an uneven spatial distribution. Previous methods have differentiated the degradation rates of materials in different regions within a biodegradable cranioplasty implant based on the bone healing potential at different locations within the cranioplasty defect area, selecting biodegradable biomaterials with differentiated degradation behaviors. One material's degradation rate responds to local biosignals, and structural deviations during manufacturing are compensated for by adjusting material ratios, porosity, or internal structure. Building upon this, this application further introduces a mechanism for sensing and responding to real-world biosignals. First, by identifying local biosignals indicating the growth process of new bone tissue, such as biomolecules secreted by new bone tissue, their metabolites, or changes in local ion concentration reflecting bone mineralization, dynamic information on bone healing can be obtained in real time. These signals directly reflect the degree of bone regeneration and maturation, providing a biological basis for subsequent degradation regulation. Next, each unit of the implant is designed with responsive materials. The degradation behavior of these materials is influenced by identified local biosignals; for example, they may contain chemical bonds that can be cleaved by enzymes specific to newly formed bone tissue, or their degradation rate may be affected by changes in local ion concentration. Furthermore, a degradation threshold is set for the responsive materials to ensure that their degradation only accelerates significantly when biomolecules or metabolites reach specific concentrations reflecting bone tissue maturation. This prevents premature implant degradation, ensuring that the implant only begins to degrade rapidly after the newly formed bone tissue has reached maturity and provided mechanical support, thus making room for new bone growth. Through this mechanism, the actual degradation rate of each unit of the implant can be regulated according to local biosignals. This means that even with microstructural deviations during manufacturing or unexpected local differences in the healing environment within the organism, the implant can dynamically adjust its degradation rate through its inherent material properties. For example, in areas with rapid bone regeneration, active new osteoblasts generate biosignals that accelerate the degradation of the responsive materials, resulting in a faster overall degradation rate of the implant at that location, promptly making room for rapidly growing new bone tissue. In areas where bone regeneration is slow, the biosignals are relatively weak, and the degradation rate of the responsive material also slows down accordingly. In these locations, the implant provides long-term stable support, ensuring that no mechanical weaknesses emerge in the repair area before new bone has fully formed. This adaptive adjustment capability allows the implant to better match the growth process of new bone tissue, thereby ensuring that the skull defect area maintains structural integrity throughout the entire repair cycle, resolving the problem of mismatch between the preset degradation rate and the actual biological process.

[0028] As one embodiment of the present invention, the step of designing responsive materials in each unit of the implant, such that their degradation behavior is affected by recognized local biosignals, includes: The composition of responsive materials in each unit of the implant is designed to include material components capable of exhibiting differentiated degradation behavior in response to varying intensities of local biosignals. Based on the composition of responsive materials, the internal structure of responsive materials is designed so that they can modulate the penetration or action of local biological signals; By using responsive materials and designing the internal structure, the degradation behavior of each unit of the implant can be regulated according to changes in the intensity of local biosignals, thereby maintaining synchronization with the growth process of new bone tissue.

[0029] The composition of responsive materials refers to the chemical composition ratio of the materials in the implant that can respond to biological signals. This can be achieved using a mixture of various polymers, inorganic materials, or composite materials. The purpose is to regulate the material's sensitivity to biological signals by adjusting the proportions of different components. Material components that exhibit differentiated degradation behavior due to varying intensities of local biological signals refer to specific chemical substances or polymer segments contained in the responsive material that exhibit different degradation rates to different concentrations or activity levels of local biological signals (e.g., enzyme concentration, pH value, ion concentration). This can be achieved using polymer components with different molecular weights, crosslink densities, or chemical bond sensitivities. The purpose is to dynamically adjust the material's degradation behavior according to the strength of the biological signal. The internal structure of a material refers to its microscopic geometry and arrangement, such as porosity, pore size, pore connectivity, or crystal structure. This can be achieved by adjusting printing parameters (such as laser energy, scanning speed, and fill density) or post-processing techniques (such as foaming or solvent casting) in additive manufacturing. The aim is to control the contact efficiency between biological signals and the material through physical barriers or channels. Regulating the penetration or action of local biological signals refers to controlling the rate and extent to which local biological signals (such as biomolecules and ions) enter the material or interact with its surface by altering its physical structure. This can be achieved by adjusting the material's porosity, pore size, pore connectivity, or surface roughness. The aim is to influence the accessibility of biological signals to degradation sites within the material, thereby indirectly regulating the degradation rate.

[0030] Specifically, by designing the composition of responsive materials to include components capable of exhibiting differentiated degradation behaviors in response to varying intensities of local biosignals, responsive materials are not single-component but composed of multiple components with varying sensitivities or response rates to local biosignals. When the intensity of a local biosignal is high, the highly sensitive components degrade preferentially, thus accelerating the overall degradation rate; conversely, when the intensity of a local biosignal is low, only the less sensitive components degrade, thus slowing down the overall degradation rate. This differentiated composition design allows the material to dynamically adjust its degradation behavior according to the strength of the biosignal. Simultaneously, based on the composition of the responsive material, its internal structure is designed to regulate the penetration or action of local biosignals. The internal structure of the responsive material, such as porosity, pore size, and pore connectivity, affects the penetration and diffusion of local biosignals into the material's interior, as well as the interaction between the biosignal and the material components. A high-porosity structure facilitates rapid biosignal penetration, thus accelerating degradation; while a low-porosity structure hinders biosignal penetration, thus slowing down degradation. Furthermore, the internal structure can also affect the exposure degree of material components, thereby influencing their interaction with biosignals. By meticulously designing its internal structure, the responsiveness of responsive materials to local biosignals can be further modulated. Through the composition of the responsive material and the design of its internal structure, the degradation behavior of each implant unit can be adjusted according to changes in the intensity of local biosignals, thus maintaining synchronization with the growth process of new bone tissue. This means that the degradation rate of each implant unit is no longer fixed but can be dynamically adjusted according to changes in the intensity of local biosignals, thereby matching the growth rate of new bone tissue. In areas where bone regeneration is rapid, the biosignal intensity is high, and the implant degradation rate accelerates, providing more growth space for new bone tissue; while in areas where bone regeneration is slow, the biosignal intensity is low, and the implant degradation rate slows down, providing longer-lasting mechanical support for new bone tissue. This precise control over the composition and internal structure of the responsive material, combined with a scheme that identifies local biosignals and sets degradation thresholds, enables the implant to more intelligently adapt to the complex biological environment within the body. It can not only sense the growth process of new bone tissue but also respond precisely to changes in the intensity of this process through the material's own intrinsic mechanisms. This overcomes the problem of mismatch between degradation rate and biological signal caused by relying solely on material responsiveness without fine-tuning, ensuring that the weakening of the mechanical properties of the implant and the enhancement of the mechanical properties of the newly formed bone tissue are precisely matched in space and time throughout the entire repair cycle, thereby significantly improving the success rate and long-term effect of cranioplasty.

[0031] As one embodiment of the present invention, the step of identifying local biosignals indicating the growth process of new bone tissue includes: For implant units at various locations within the skull defect area, information on the content of different types of biomolecules in their adjacent microenvironment is obtained. Biomolecules are proteins or their degradation products that are unique to the bone formation process. Based on the obtained biomolecule content information, the location distribution characteristics of the biomolecule content information in the micro-region adjacent to the implant unit are analyzed. Based on the location and distribution characteristics, the growth status of new bone tissue in the micro-region where the implant unit is located is determined, serving as a local biosignal to indicate the growth process of new bone tissue.

[0032] Biomolecules are proteins or their degradation products present during bone formation. These can be proteins directly involved in bone mineralization or bone remodeling, such as osteocalcin, osteopontin, and alkaline phosphatase, or peptides or amino acids produced after their degradation in vivo. The aim is to ensure a high correlation between the detected signals and the growth activity of newly formed bone tissue, thereby providing accurate biological indicators. The locational distribution characteristics of biomolecule content in the micro-region adjacent to the implant unit refer to the concentration gradients, aggregation areas, or diffusion patterns of various biomolecules in the microscopic space surrounding the implant unit. This can be monitored in real-time using a micro-sensor array or obtained through tissue section staining combined with image analysis. The purpose is to reveal the spatial heterogeneity of bone tissue growth, such as active areas of osteocytes. Or mineralization frontier; where, the newly formed bone tissue growth status refers to the stage and rate of bone tissue formation, maturation or remodeling in the micro-region where the implant unit is located, which can be comprehensively evaluated based on the type, content and spatial distribution characteristics of biomolecules. For example, high concentrations of osteocalcin and uniformly distributed alkaline phosphatase may indicate an active bone mineralization process, the purpose of which is to provide accurate biofeedback for the dynamic regulation of subsequent implant degradation rate; where, the regional biosignal indicating the growth process of newly formed bone tissue refers to a bioindicator that can reflect the degree of bone tissue growth activity and maturation stage in the microenvironment surrounding the implant, which can be the newly formed bone tissue growth status determined by the above analysis, the purpose of which is to serve as an important input to drive the degradation behavior of responsive materials in the implant, ensuring that implant degradation is synchronized with bone tissue growth.

[0033] This approach first acquires information on the content of various biomolecules in the microenvironment surrounding each implant unit within the skull defect area. These biomolecules are proteins or their degradation products involved in bone formation. By focusing on biomolecules involved in bone formation, the acquired information directly and accurately reflects the growth status of newly formed bone tissue, as these molecules directly participate in or accompany the bone formation process, and their content changes are closely related to bone growth rate. Subsequently, based on the acquired biomolecule content information, the locational distribution characteristics of biomolecules in the micro-region adjacent to the implant unit are analyzed. This analysis of spatial distribution characteristics allows for a more comprehensive understanding of the spatial patterns of bone tissue growth. For example, the concentration of biomolecules on a specific surface of the implant unit may indicate preferential bone growth on that surface, which is significant for understanding the heterogeneity of regional healing. Finally, based on the locational distribution characteristics, the growth status of newly formed bone tissue in the micro-region where the implant unit is located is determined and used as a regional biosignal indicating the progress of newly formed bone tissue growth. By comprehensively considering the types, content, and spatial distribution of biomolecules, the approach can more accurately determine the stage and rate of regional bone tissue growth.

[0034] This method of identifying regional biosignals, combined with the overall scheme proposed in this application that allows the actual degradation rate of each implant unit to be adjusted according to regional biosignals, enables the implant's degradation behavior to be dynamically adjusted based on actual biological processes at the microscopic level, rather than solely relying on set macroscopic parameters. When the degradation behavior of each implant unit can be so precisely adjusted, it can better match the growth process of newly formed bone tissue, ensuring that in areas of rapid bone growth, the implant can degrade in a timely manner to make room; while in areas of slow bone growth, the implant can provide mechanical support for a longer period of time. This identification and adjustment mechanism improves the accuracy and reliability of the dynamic matching between cranioplasty implant materials and the organism, thereby effectively avoiding the problems of premature implant failure or hindering new bone growth, ultimately improving the long-term repair effect and functional recovery.

[0035] As one embodiment of the present invention, the steps of dividing the skull implant into units and obtaining bone regeneration potential information corresponding to each unit of the implant based on the distribution of bone regeneration potential include: Based on the geometric morphology of skull defects and the characteristics of bone regeneration potential distribution, the unit division method of skull implants is determined. Based on the unit division method, the cranial implant is divided into multiple units with differences in size or shape; For each of multiple units with differences in size or shape, spatial sampling or statistical analysis is performed on the distribution of bone regeneration potential; Based on the results of spatial sampling or statistical analysis, information on the bone regeneration potential of each unit is obtained.

[0036] The unit partitioning method refers to the specific strategy or rule for spatial segmentation of the skull implant. It can be determined by adaptive meshing based on geometric features, region segmentation based on bone regeneration potential gradient, or a combination of both. The purpose is to enable the implant partitioning to more accurately match the local characteristics of the skull defect and the spatial distribution of bone regeneration potential. Units with size or shape differences refer to sub-regions that differ in size or geometric shape, obtained through non-uniform segmentation methods. These can be implemented using tetrahedral meshes, hexahedral meshes, or irregular polygonal meshes, etc., to better adapt to the irregular geometric shape of the skull defect and the spatial distribution of bone regeneration potential, thereby improving the fit between the implant and the defect area. Spatial sampling or statistical analysis refers to the process of extracting discrete data points or calculating regional feature values ​​from the continuous distribution of bone regeneration potential. Spatial sampling can involve selecting several representative points within a unit to obtain its potential information, while statistical analysis can involve calculating the average, median, or mode of the potential information of all points within a unit. The purpose is to comprehensively and accurately obtain the bone regeneration potential information within each unit, providing a reliable basis for subsequent material parameter configuration.

[0037] As one embodiment of the present invention, the step of determining the material degradation rate of each implant unit based on the bone regeneration potential information of each implant unit includes: Establish a table showing the correspondence between bone regeneration potential information and material degradation rate; Based on the bone regeneration potential information of each implant unit, and according to the corresponding relationship table, the material degradation rate corresponding to each implant unit is found.

[0038] Establishing a correspondence table between bone regeneration potential information and material degradation rate refers to constructing a structured dataset or mathematical model to clearly define the mapping relationship between different bone regeneration potential values ​​and corresponding material degradation rates. This can be achieved by using nonlinear functions fitted with a large amount of experimental data, piecewise linear functions, multidimensional lookup tables, or models trained based on machine learning algorithms. The purpose is to provide a systematic and quantifiable basis for the conversion of bone regeneration potential information into material degradation rate.

[0039] This application's solution systematically solves the problem of effectively converting bone regeneration potential information into implant material degradation rates by establishing a correspondence table between bone regeneration potential information and material degradation rates, and then using this table to find the corresponding material degradation rates for each implant unit. Specifically, firstly, by establishing a correspondence table, different levels of bone regeneration potential information are explicitly associated with preset material degradation rates. This correspondence table can be constructed based on extensive biomechanical experimental data, clinical observation results, or computational simulations, ensuring the scientific validity and reliability of the conversion relationship. This pre-established, structured correspondence provides a clear and repeatable basis for subsequent degradation rate determination, avoiding the biases that may arise from simple linear mapping. Secondly, after obtaining the bone regeneration potential information for each implant unit, the system can quickly search according to the established correspondence table to determine the precise material degradation rate for each unit. This search process is efficient and accurate, transforming abstract biological potential information into specific material engineering parameters, enabling personalized configuration of degradation rates during the implant design phase. It is precisely this systematic matching and search mechanism that allows the material degradation rate of each unit of the implant to be precisely matched with the regenerative potential of the local bone. This further enhances the accuracy and controllability of the entire cranioplasty implant material parameter configuration method, ensuring that the reduction of the mechanical properties of the implant and the enhancement of the mechanical properties of the newly formed bone tissue can be more closely coordinated in space and time, thereby providing a more optimized mechanical environment and space for bone regeneration and significantly improving the overall repair effect.

[0040] As one embodiment of the present invention, the step of establishing a correspondence table between bone regeneration potential information and material degradation rate includes: Obtain the patient's physiological indicators; Based on physiological indicators, adjust the correlation between bone regeneration potential and material degradation rate; Based on the adjusted correspondence, a table of correspondences between bone regeneration potential information and material degradation rate was established.

[0041] Physiological indicators refer to data reflecting the individual biological state of the patient, which may include the patient's age, gender, history of underlying diseases, nutritional status, metabolic level, endocrine status, or specific biomarker levels, etc., with the aim of providing a data foundation for subsequent individualized adjustments; adjusting the correspondence between bone regeneration potential information and material degradation rate refers to dynamically modifying the preset matching rules between bone regeneration potential and material degradation rate based on the patient's physiological indicators, which can be achieved using rule bases based on expert experience, machine learning models, or biomechanical simulation models, with the aim of making the degradation rate of the implant more accurately match the patient's own bone regeneration speed; the correspondence table is a data set that stores the matching rules between bone regeneration potential information and material degradation rate in a structured form, which can be represented by databases, lookup tables, or mapping functions, with the aim of facilitating the system to quickly find and apply the adjusted matching rules.

[0042] Specifically, first, the system acquires the patient's physiological indicators. This information forms the basis for individualized adjustments, as factors such as the patient's age, gender, nutritional status, and metabolic level directly affect their bone regeneration capacity and material degradation behavior. For example, elderly patients typically experience slower bone regeneration, while malnourished patients may have weaker bone regeneration capabilities. Next, the system adjusts the correspondence between bone regeneration potential and material degradation rates based on this acquired physiological indicator information. This adjustment is the core of the solution, personalizing the previously general matching rules. For instance, for patients with weaker bone regeneration capacity, the system adjusts the correspondence accordingly, setting a slower degradation rate for materials at the same bone regeneration potential level to provide longer-lasting mechanical support. Conversely, for patients with strong regeneration capacity, the degradation rate can be appropriately accelerated to create space for new bone growth more quickly. This adjustment can be based on a pre-defined algorithm model or machine learning model to ensure the scientific validity and accuracy of the adjustment. Finally, based on this adjusted correspondence, the system establishes a new table showing the correspondence between bone regeneration potential and material degradation rates. This new correspondence table is tailored to specific patients, solidifying the individualized adjustments. During subsequent implant parameter configuration, the system can use this personalized table to precisely determine the material degradation rate for each implant unit. In this way, the degradation rate of the implant material more accurately matches the patient's own bone regeneration rate. This not only improves the repair effect but also avoids the problems of insufficient support due to excessively rapid degradation or hindered new bone growth due to excessively slow degradation. This individualized adjustment mechanism allows the entire cranioplasty implant material parameter configuration method to better adapt to the dynamics of the organism and individual differences, thereby ensuring that the defect area maintains sufficient mechanical integrity throughout the entire repair cycle, significantly improving the success rate of repair and the quality of patient rehabilitation.

[0043] like Figure 2 The system shown is a cranioplasty implant material parameter configuration system, which includes: The information acquisition module 201 is used to acquire image data of the skull defect area and determine the boundary information of the skull defect based on the image data; The regeneration capacity assessment module 202 is used to obtain the physical attribute information of the bone adjacent to the boundary based on the boundary information, and to assess the bone regeneration capacity of the area adjacent to the boundary based on the physical attribute information. The potential distribution determination module 203 is used to determine the distribution of bone regeneration potential at each location within the skull defect area based on the bone regeneration capacity of the adjacent area. The unit information acquisition module 204 is used to divide the skull implant into units and acquire bone regeneration potential information corresponding to each unit of the implant based on the distribution of bone regeneration potential. The degradation rate determination module 205 is used to determine the material degradation rate of each unit of the implant based on the bone regeneration potential information of each unit of the implant. The parameter configuration module 206 is used to adjust the material structure parameters of each unit of the implant according to the material degradation rate of each unit of the implant. The instruction generation module 207 is used to generate manufacturing instructions for manufacturing implants.

[0044] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method of configuring parameters of a skull-repair implant material, characterized by, The method comprises the following steps: acquiring image data of the skull defect area, and determining boundary information of the skull defect based on the image data; acquiring physical property information of the boundary-adjacent autologous bone according to the boundary information, and evaluating the bone regeneration capacity of the boundary-adjacent area based on the physical property information; determining the bone regeneration potential distribution of each position in the skull defect area according to the bone regeneration capacity of the boundary-adjacent area; dividing the skull implant into units, and acquiring bone regeneration potential information corresponding to each unit of the implant according to the bone regeneration potential distribution; determining the material degradation rate of each unit of the implant according to the bone regeneration potential information of each unit of the implant; adjusting the material structure parameters of each unit of the implant to achieve the material degradation rate; generating manufacturing instructions for manufacturing the implant.

2. The method of claim 1, wherein, The step of determining the bone regeneration potential distribution of each position in the skull defect area according to the bone regeneration capacity of the boundary-adjacent area comprises: identifying the area on the boundary that is susceptible to image artifacts; for the area susceptible to image artifacts, analyzing the distribution of pixel values in the area, acquiring the numerical range representing the true bone signal in the distribution, and determining the physical property information of the boundary-adjacent autologous bone based on the numerical range; for the area not susceptible to image artifacts, acquiring the physical property information of the boundary-adjacent autologous bone using a conventional measurement method; evaluating the bone regeneration capacity of the boundary-adjacent area based on the acquired physical property information; determining the bone regeneration potential distribution of each position in the skull defect area according to the evaluated bone regeneration capacity.

3. The method of claim 1, wherein the method further comprises: The step of controlling the material degradation rate by adjusting the material structure parameters of each unit of the implant comprises: selecting degradable biomaterials with differential degradation behavior, wherein the degradation rate of one material responds to local biological signals; determining the material ratio in each unit of the implant according to the bone regeneration potential information of each unit of the implant; determining the porosity or internal structure of each unit of the implant according to the bone regeneration potential information of each unit of the implant; by adjusting the material structure parameters of each unit of the implant, including adjusting the material ratio and the porosity or internal structure, the actual degradation rate of each unit of the implant can be adjusted according to the local biological signals, thereby compensating for the influence of structural deviations in the manufacturing process on the preset degradation rate.

4. The method of claim 3, wherein the parameters of the skull repair implant material are configured to be: The step of enabling the actual degradation rate of each unit of the implant to be adjusted according to the local biological signals comprises: identifying local biological signals indicative of the growth process of new bone tissue, the local biological signals including biological molecules secreted by new bone tissue or their metabolites, or local ion concentration changes reflecting the bone mineralization process; designing responsive materials in each unit of the implant, so that their degradation behavior is affected by the identified local biological signals, the responsive materials containing chemical bonds that can be cleaved by specific enzymes of new bone tissue, or their degradation rate is affected by the local ion concentration changes; setting a degradation threshold of the responsive material, so that the degradation behavior of the responsive material is only significantly accelerated when the biomolecules or metabolites reach a specific concentration reflecting the maturity of the bone tissue; by the degradation behavior of the responsive material being affected by the local biological signal and the setting of the degradation threshold, the actual degradation rate of each unit of the implant can be adjusted according to the local biological signal.

5. The method of claim 4, wherein the step of determining the parameters of the skull repair implant material is performed by a computer program. The step of designing the responsive material in each unit of the implant so that its degradation behavior is affected by the identified local biological signal comprises: designing the composition of the responsive material in each unit of the implant so that it contains material components that can produce differential degradation behavior for different intensities of the local biological signal; According to the composition of the responsive material, the internal structure of the responsive material is designed to be able to adjust the permeation or action of the local biological signal; By designing the composition and internal structure of the responsive material, the degradation behavior of each unit of the implant can be adjusted according to the intensity change of the local biological signal, so as to keep synchronization with the growth process of the new bone tissue.

6. The method of claim 4, wherein the step of determining the parameters of the skull repair implant material is performed by a computer program. The step of identifying the local biological signal indicating the growth process of the new bone tissue comprises: For the implant unit at each position in the skull defect area, obtain the content information of different kinds of biomolecules in the adjacent microenvironment of the implant unit, which are specific proteins or degradation products in the bone formation process; According to the obtained biomolecule content information, analyze the position distribution characteristics of the biomolecule content information in the micro region adjacent to the implant unit; According to the position distribution characteristics, determine the growth status of the new bone tissue in the micro region where the implant unit is located as the local biological signal indicating the growth process of the new bone tissue.

7. The method of claim 1, wherein the method further comprises: determining a parameter of the skull repair implant material. The step of dividing the skull implant into units and obtaining the bone regeneration potential information corresponding to each unit of the implant according to the bone regeneration potential distribution comprises: Based on the geometric shape of the skull defect and the characteristics of the bone regeneration potential distribution, determine the unit division mode of the skull implant; According to the unit division mode, divide the skull implant into a plurality of units with size or shape difference; For each of the plurality of units with size or shape difference, spatially sample or statistically analyze the bone regeneration potential distribution; According to the results of the spatial sampling or statistical analysis, obtain the bone regeneration potential information corresponding to each unit.

8. The method of claim 1, wherein the method further comprises: determining a parameter of the skull repair implant material. The step of determining the material degradation rate of each unit of the implant according to the bone regeneration potential information of each unit of the implant comprises: establishing a correspondence table between the bone regeneration potential information and the material degradation rate; According to the bone regeneration potential information of each unit of the implant, find the corresponding material degradation rate of each unit of the implant according to the correspondence table.

9. The method of claim 8, wherein the step of determining the parameters of the skull repair implant material is performed by a computer program. The step of establishing a correspondence table between the bone regeneration potential information and the material degradation rate comprises: obtaining physiological index information of the patient; According to the physiological index information, adjust the correspondence between the bone regeneration potential information and the material degradation rate; Based on the adjusted corresponding relationship, a corresponding relationship table between the bone regeneration potential information and the material degradation rate is established.

10. A system for configuring parameters of a skull-repair implant material for performing a method of configuring parameters of a skull-repair implant material according to any one of claims 1 to 9, characterized in that The system comprises: An information acquisition module is configured to acquire image data of a skull defect region and determine boundary information of the skull defect based on the image data; A regeneration capacity evaluation module is configured to acquire physical property information of self-bone adjacent to the boundary based on the boundary information, and evaluate bone regeneration capacity of the boundary adjacent region based on the physical property information; A potential distribution determination module is configured to determine bone regeneration potential distribution of each position in the skull defect region according to the bone regeneration capacity of the boundary adjacent region; A unit information acquisition module is configured to divide a skull implant into units, and acquire bone regeneration potential information corresponding to each unit of the implant according to the bone regeneration potential distribution; A degradation rate determination module is configured to determine a material degradation rate of each unit of the implant according to the bone regeneration potential information of each unit of the implant; A parameter configuration module is configured to adjust material structure parameters of each unit of the implant according to the material degradation rate of each unit of the implant; An instruction generation module is configured to generate manufacturing instructions for manufacturing the implant.

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