3D printing method and system for osteochondral scaffold

Abstract

The invention provides a 3D printing method and system for an osteochondral stent. The method comprises the following steps: collecting three-dimensional point cloud data of an osteochondral defect part; reconstructing a three-dimensional model of the defect part based on the point cloud data, and performing stress-strain analysis on the model; according to a stress distribution result, establishing a porosity dynamic adjustment model to adjust pore parameters; and generating a printing path based on the target pore parameters and the three-dimensional model, and sequentially printing the subchondral bone layer, the transition layer and the scaffold cartilage layer. Model reconstruction and stress analysis are driven through medical image data, dynamic calibration of pore parameters is realized in combination with a structure optimization algorithm, multi-material printing and multi-stage crosslinking are utilized, the pore parameters are adjusted through a porosity dynamic adjustment model, and stent failure caused by stress concentration is avoided; the gradient printing and cross-linking synergistically enhance the stability of the scaffold and the slow release ability of bioactive ions, so that the cell migration efficiency, the collagen deposition quality and the osteochondral interface integration strength are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of osteocartilage scaffold technology, and in particular to a 3D printing method and system for osteocartilage scaffolds. Background Technology

[0002] Osteocartilage defect repair is one of the core challenges in tissue engineering. Due to significant differences in structure, mechanical properties, and cellular composition between cartilage and subchondral bone, achieving integrated regeneration requires the construction of biomimetic gradient scaffolds. 3D printing technology, through precise control of material spatial distribution and microstructure, provides personalized solutions for osteocartilage repair. Its application aims to mimic the anisotropy of natural tissues, promoting cell migration, nutrient diffusion, and mechanical support, ultimately achieving functional regeneration. Existing conventional technologies mostly use homogeneous bio-inks (such as pure gelatin hydrogels) or simple layered designs, such as printing a single material and then curing it through chemical cross-linking. However, such methods have obvious drawbacks: First, the scaffold pore structure is static and cannot respond to the local mechanical environment, resulting in high-stress areas being prone to collapse while low-stress areas have insufficient cell infiltration; Second, in multi-cell printing, the spatial distribution of cells is coarse and lacks a dynamic optimization mechanism based on cell behavior, resulting in fibrosis or poor integration of the repaired tissue. Summary of the Invention

[0003] In view of the shortcomings of the prior art, the purpose of this invention is to provide a 3D printing method and system for osteocartilage scaffolds, aiming to solve the technical problem of poor scaffold printing quality in the prior art.

[0004] To achieve the above objectives, in a first aspect, the present invention provides: a 3D printing method for a cartilage scaffold, comprising the following steps: Three-dimensional point cloud data of the osteochondral defect site were acquired using medical imaging. A three-dimensional model of the defective area was reconstructed based on the point cloud data, and a biomechanical stress-strain analysis was performed on the model. Based on the stress distribution results, a dynamic porosity adjustment model is established using a structural optimization algorithm, and the target porosity parameters of the scaffold cartilage layer, transition layer and subchondral bone layer are calculated based on the dynamic porosity adjustment model. Based on the target pore parameters and the three-dimensional model, a printing path is generated, and a composite 3D printer is used to sequentially print the subchondral bone layer, transition layer and framework cartilage layer. The printed scaffold undergoes a multi-stage cross-linking process.

[0005] According to one aspect of the above technical solution, before the step of generating a printing path based on the target pore parameters and the three-dimensional model, the method further includes: Based on the target pore parameters, the three-dimensional model of the support is discretized into a mesh, with each mesh cell being regarded as a node and the connection between adjacent cells being regarded as an edge. Starting from all the pore nodes on the outer surface of the support, the pore network is traversed using a breadth-first search algorithm. The minimum number of edges from each internal pore node to the outer surface is calculated as the shortest path hop count. Optimize the target pore parameters so that the shortest path hop count is less than a preset threshold; The weight of the edge is determined based on the diffusion resistance of nutrients, and the calculation expression for the edge weight is as follows: ; In the formula, The weight of the edge. Let L be the permeability, L be the connection length between the centers of adjacent pores, and A be the cross-sectional area of ​​the pore.

[0006] According to one aspect of the above technical solution, the calculation expression for the optimized target pore parameters is as follows: ; In the formula, The adjusted target pore parameters, H is the preset threshold, where H is the number of hops in the shortest path. is the calibration factor, and P is the target pore parameter.

[0007] According to one aspect of the above technical solution, the calculation expression of the porosity dynamic adjustment model is as follows: ; In the formula, P is the target porosity parameter. As a reference stress threshold, The local equivalent stress value obtained through finite element analysis. This refers to the material coefficient related to cell compatibility.

[0008] According to one aspect of the above technical solution, the material coefficient is calibrated using a cell migration efficiency model, the calculation expression of which is: ; ; In the formula, For cell migration resistance, The viscosity coefficient of the extracellular matrix. The rate of change of fluid velocity per unit distance along the direction of cell migration. This is the maximum allowable migration resistance value set according to cell type.

[0009] According to one aspect of the above technical solution, the transition layer includes a conical hole and a serrated microstructure disposed within the hole wall of the conical hole, wherein the calculation expression for the spacing of the serrated microstructure is: ; ; In the formula, The spacing of the serrated microstructures The propagation speed of stress waves in the support material. The vibration frequency, The Young's modulus of the transition layer support material. The density of the transition layer support material. This represents the depth of the tapered hole.

[0010] According to one aspect of the above technical solution, the steps of sequentially printing the subchondral bone layer, transition layer, and framework cartilage layer using a composite 3D printer specifically include: The subchondral bone layer was printed using a fused deposition modeling process with polyetheretherketone (PEEK) as the material and a printing temperature of 380℃-420℃. The upper surface of the printed polyetheretherketone subchondral bone layer was subjected to low-pressure plasma treatment for 30-60 seconds at a power of 100W. The transition layer was printed using an electrospinning process. The material was polycaprolactone, the fiber diameter was 1-5μm, and the pore size of the resulting fiber membrane was less than 18μm. The scaffold cartilage layer was printed using a low-temperature extrusion molding process, and the material was a gelatin-chitosan hydrogel containing TGF-β1 growth factor.

[0011] According to one aspect of the above technical solution, the steps for performing multi-stage crosslinking treatment on the printed scaffold specifically include: The printed scaffold was immersed in a 5% CaCl2 solution for ionic cross-linking for 30 minutes. Photocrosslinking was performed using ultraviolet light with a wavelength of 365nm. The photocrosslinking time was determined based on the overall thickness of the scaffold, satisfying the following requirements: t=h 2 / D; In the formula, t is the photocrosslinking time, h is the overall thickness of the scaffold, and D is the diffusion coefficient of the photoinitiator in the corresponding material.

[0012] On the other hand, this application also discloses a 3D printing system for osteochondral scaffolds, comprising: The acquisition module is used to acquire three-dimensional point cloud data of osteochondral defects through medical imaging. The analysis module is used to reconstruct a three-dimensional model of the defective part based on the point cloud data and to perform biomechanical stress-strain analysis on the model. The porosity adjustment module is used to establish a dynamic porosity adjustment model based on the stress distribution results and a structural optimization algorithm, so as to calculate the target porosity parameters of the scaffold cartilage layer, transition layer and subchondral bone layer based on the dynamic porosity adjustment model. The printing module is used to generate a printing path based on the target pore parameters and the three-dimensional model, and to use a composite 3D printer to sequentially print the subchondral bone layer, the transition layer and the scaffold cartilage layer. The crosslinking module is used to perform multi-stage crosslinking treatment on the printed stent.

[0013] According to one aspect of the above technical solution, the system further includes: The optimization module is used to discretize the three-dimensional model of the support into a mesh based on the target pore parameters, where each mesh cell is regarded as a node and the connection between adjacent cells is regarded as an edge. Starting from all the pore nodes on the outer surface of the support, the pore network is traversed using a breadth-first search algorithm. The minimum number of edges from each internal pore node to the outer surface is calculated as the shortest path hop count. Optimize the target pore parameters so that the shortest path hop count is less than a preset threshold; The weight of the edge is determined based on the diffusion resistance of nutrients, and the calculation expression for the edge weight is as follows:

[0014] In the formula, The weight of the edge. Let L be the permeability, L be the connection length between the centers of adjacent pores, and A be the cross-sectional area of ​​the pore.

[0015] Compared with existing technologies, the beneficial effects of this invention are as follows: by driving model reconstruction and stress analysis through medical imaging data, and combining structural optimization algorithms to achieve dynamic calibration of pore parameters, and by utilizing multi-material printing and multi-stage cross-linking, the pore parameters are adjusted through a dynamic porosity adjustment model to avoid scaffold failure caused by stress concentration; gradient printing and cross-linking synergistically enhance the stability of the scaffold and the ability to release bioactive ions, thereby significantly improving cell migration efficiency, collagen deposition quality and osteochondral interface integration strength. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the 3D printing method for the osteocartilage scaffold in the first embodiment of the present invention. Figure 2 This is a structural block diagram of the 3D printing system for the osteocartilage scaffold in the fourth embodiment of the present invention; The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0017] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0018] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0020] Example 1 Please see Figure 1 The figure shows a flowchart of the 3D printing method of the osteocartilage scaffold in the first embodiment of the present invention. As shown in the figure, the method includes the following steps: Step S100: Acquire three-dimensional point cloud data of the osteocartilage defect area using medical imaging. Specifically, in this embodiment, an MRI scan of the patient's knee joint is performed to obtain two-dimensional sequence images in DICOM format. These images are then imported into Mimics software, and the contour of the osteocartilage defect area is extracted through threshold segmentation to generate three-dimensional point cloud data. Step S200: Reconstruct a three-dimensional model of the damaged area based on the point cloud data, and perform biomechanical stress-strain analysis on the model. Specifically, use the software's built-in mesh optimization tool to reconstruct the three-dimensional model of the damaged area, output the model in STL format, import it into Abaqus, set material properties, perform finite element analysis by applying joint physiological loads, and output equivalent stress cloud diagrams.

[0021] Step S300: Based on the stress distribution results, a dynamic porosity adjustment model is established using a structural optimization algorithm, and the target porosity parameters of the scaffold cartilage layer, transition layer, and subchondral bone layer are calculated based on the dynamic porosity adjustment model.

[0022] Preferably, in this embodiment, the calculation expression of the porosity dynamic adjustment model is: ; In the formula, P is the target porosity parameter. As a reference stress threshold, The local equivalent stress value obtained through finite element analysis. This refers to the material coefficient related to cell compatibility. In some application scenarios of this embodiment, based on the stress cloud map, the above dynamic porosity adjustment model is used, with a reference stress threshold of 1 Moa and an initial material coefficient of 0.15. The target porosity of each region is calculated using the above formula. The porosity in the high-stress region (σ>2MPa) is preferably 45% (corresponding to a pore size of 600-900μm), and the porosity in the low-stress region (σ≤0.5MPa) is preferably 50% (corresponding to a pore size of 300-500μm).

[0023] Furthermore, the material coefficients for different layers are different. These material coefficients are calibrated using a cell migration efficiency model, the calculation expression of which is: ; ; In the formula, For cell migration resistance, The viscosity coefficient of the extracellular matrix. The rate of change of fluid velocity per unit distance along the direction of cell migration. This represents the maximum allowable migration resistance value set according to cell type. Specifically, in some application scenarios of this embodiment, the migration rate of human mesenchymal stem cells in gelatin-chitosan hydrogel is determined by in vitro Transwell experiments. Taking an apparent migration resistance of 18 Pa as an example, the material coefficient k is calibrated to k = (50...). 18) / 50=0.64, where Set to 50 Pa.

[0024] By establishing a dynamic porosity adjustment model, the pore size in the high-stress zone is increased to promote bone ingrowth, while the pore size in the low-stress zone is decreased to facilitate cartilage deposition, thus avoiding scaffold failure caused by stress shielding or concentration.

[0025] Furthermore, in this embodiment, before the step of generating a printing path based on the target pore parameters and the three-dimensional model, the method further includes: Based on the target pore parameters, the three-dimensional model of the support is discretized into a mesh, with each mesh cell being regarded as a node and the connection between adjacent cells being regarded as an edge. Starting from all the pore nodes on the outer surface of the support, the pore network is traversed using a breadth-first search algorithm. The minimum number of edges from each internal pore node to the outer surface is calculated as the shortest path hop count. Optimize the target pore parameters so that the shortest path hop count is less than a preset threshold; The weight of the edge is determined based on the diffusion resistance of nutrients, and the calculation expression for the edge weight is as follows: ; In the formula, The weight of the edge. Let L be the permeability, L be the connection length between the centers of adjacent pores, and A be the cross-sectional area of ​​the pore.

[0026] The optimized formula for calculating the target pore size parameters is as follows: ; In the formula, The adjusted target pore parameters, H is the preset threshold, where H is the number of hops in the shortest path. P is the calibration factor and P is the target porosity parameter. In some application scenarios of this embodiment, the hop count threshold is set to 10. Based on the above calculation formula, the porosity of the region where H is greater than 10 is adjusted. After iterative calculation, by increasing the porosity in the region, the shortest path hop count is reduced to 9, which meets the requirements for effective nutrient delivery, shortens the nutrient diffusion distance, prevents cells in the central region from dying due to nutrient deficiency, and improves regeneration uniformity.

[0027] Step S400: Based on the target porosity parameters and the three-dimensional model, a printing path is generated, and a composite 3D printer is used to sequentially print the subchondral bone layer, transition layer, and scaffold cartilage layer. The PEEK bone layer provides high-strength support, the PCL transition layer buffers stress, and the hydrogel cartilage layer simulates soft tissue elasticity, preventing interfacial delamination.

[0028] Specifically, the steps of using a composite 3D printer to sequentially print the subchondral bone layer, transition layer, and framework cartilage layer include: The subchondral bone layer is printed using a fused deposition modeling process with polyetheretherketone (PEEK) as the material, and the printing temperature is 380℃-420℃; in this embodiment, the preferred printing temperature is 400℃.

[0029] The upper surface of the printed polyetheretherketone subchondral bone layer is subjected to low-pressure plasma treatment for 30-60 seconds at a power of 100W. By treating the upper surface of the PEEK layer with low-pressure plasma (preferred parameters: power 100W, time 45 seconds), hydrophilicity is enhanced to promote interlayer bonding.

[0030] The transition layer was printed using an electrospinning process. The material was polycaprolactone, the fiber diameter was 1-5μm, and the pore size of the resulting fiber membrane was less than 18μm. Furthermore, the aforementioned transition layer includes a conical hole and serrated microstructures disposed within the hole wall of the conical hole, wherein the calculation expression for the spacing of the serrated microstructures is: ; ; In the formula, The spacing of the serrated microstructures The propagation speed of stress waves in the support material. The vibration frequency, The Young's modulus of the transition layer support material. The density of the transition layer support material. The depth of the conical hole. During the electrospinning printing process, the process parameters are: voltage 12 kV, receiving distance 15 cm, fiber diameter preferably controlled at 3 μm, and pore size preferably <15 μm.

[0031] The scaffold cartilage layer was printed using a low-temperature extrusion molding process, with the material being a gelatin-chitosan hydrogel containing TGF-β1 growth factor. Process parameters included a nozzle temperature of 8°C, a platform temperature of 4°C, and an extrusion pressure of 25 kPa, ensuring that the hydrogel maintained its rheological properties and cell viability >95%.

[0032] Step S500 involves performing a multi-stage crosslinking treatment on the printed stent. Specifically, the multi-stage crosslinking treatment of the printed stent includes the following steps: The printed scaffold was immersed in a 5% CaCl2 solution for ionic cross-linking for 30 minutes. Photocrosslinking was performed using ultraviolet light with a wavelength of 365nm. The photocrosslinking time was determined based on the overall thickness of the scaffold, satisfying the following requirements: t=h 2 / D; In the formula, t is the photocrosslinking time, h is the overall thickness of the scaffold, and D is the diffusion coefficient of the photoinitiator in the corresponding material.

[0033] In summary, the 3D printing method for osteocartilage scaffolds in the above embodiments of the present invention uses medical imaging data to drive model reconstruction and stress analysis, combines structural optimization algorithms to achieve dynamic calibration of pore parameters, and utilizes multi-material printing and multi-stage cross-linking to adjust pore parameters through a porosity dynamic adjustment model, thereby avoiding scaffold failure caused by stress concentration. Gradient printing and cross-linking synergistically enhance the stability of the scaffold and the ability to release bioactive ions, thereby significantly improving cell migration efficiency, collagen deposition quality, and osteocartilage interface integration strength.

[0034] Example 2 A second embodiment of this application also provides a 3D printing system for osteocartilage scaffolds, which is used to implement the embodiments and preferred embodiments described herein, and will not be repeated hereafter. As used below, the terms "module," "unit," "subunit," etc., can refer to a combination of software and / or hardware that performs a predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0035] like Figure 2 As shown, the system includes: a data acquisition module 100, an analysis module 200, a pore adjustment module 300, a printing module 400, and a crosslinking module 500.

[0036] The acquisition module 100 is used to acquire three-dimensional point cloud data of osteocartilage defect sites through medical imaging. Analysis module 200 is used to reconstruct a three-dimensional model of the defective part based on the point cloud data and perform biomechanical stress-strain analysis on the model; The porosity adjustment module 300 is used to establish a dynamic porosity adjustment model based on the stress distribution results and a structural optimization algorithm, so as to calculate the target porosity parameters of the scaffold cartilage layer, transition layer and subchondral bone layer based on the dynamic porosity adjustment model. The printing module 400 is used to generate a printing path based on the target pore parameters and the three-dimensional model, and to use a composite 3D printer to sequentially print the subchondral bone layer, the transition layer and the scaffold cartilage layer. The crosslinking module 500 is used to perform multi-stage crosslinking treatment on the printed stent.

[0037] Preferably, in this embodiment, the system further includes: The optimization module is used to discretize the three-dimensional model of the support into a mesh based on the target pore parameters, where each mesh cell is regarded as a node and the connection between adjacent cells is regarded as an edge. Starting from all the pore nodes on the outer surface of the support, the pore network is traversed using a breadth-first search algorithm. The minimum number of edges from each internal pore node to the outer surface is calculated as the shortest path hop count. Optimize the target pore parameters so that the shortest path hop count is less than a preset threshold; The weight of the edge is determined based on the diffusion resistance of nutrients, and the calculation expression for the edge weight is as follows:

[0038] In the formula, The weight of the edge. Let L be the permeability, L be the connection length between the centers of adjacent pores, and A be the cross-sectional area of ​​the pore.

[0039] It should be noted that the modules can be functional modules or program modules, and can be implemented in software or hardware. For modules implemented in hardware, the modules can reside in the same processor; or the modules can be located in different processors in any combination.

[0040] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A 3D printing method for an osteocartilage scaffold, characterized in that, Includes the following steps: Three-dimensional point cloud data of the osteochondral defect site were acquired using medical imaging. A three-dimensional model of the defective area was reconstructed based on the point cloud data, and a biomechanical stress-strain analysis was performed on the model. Based on the stress distribution results, a dynamic porosity adjustment model is established using a structural optimization algorithm, and the target porosity parameters of the scaffold cartilage layer, transition layer and subchondral bone layer are calculated based on the dynamic porosity adjustment model. Based on the target pore parameters and the three-dimensional model, a printing path is generated, and a composite 3D printer is used to sequentially print the subchondral bone layer, transition layer and framework cartilage layer. The printed scaffold undergoes a multi-stage cross-linking process.

2. The 3D printing method for osteocartilage scaffolds according to claim 1, characterized in that, Before the step of generating a printing path based on the target pore parameters and the three-dimensional model, the method further includes: Based on the target pore parameters, the three-dimensional model of the support is discretized into a mesh, with each mesh cell being regarded as a node and the connection between adjacent cells being regarded as an edge. Starting from all the pore nodes on the outer surface of the support, the pore network is traversed using a breadth-first search algorithm. The minimum number of edges from each internal pore node to the outer surface is calculated as the shortest path hop count. Optimize the target pore parameters so that the shortest path hop count is less than a preset threshold; The weight of the edge is determined based on the diffusion resistance of nutrients, and the calculation expression for the edge weight is as follows: ； In the formula, The weight of the edge. Let L be the permeability, L be the connection length between the centers of adjacent pores, and A be the cross-sectional area of ​​the pore.

3. The 3D printing method for osteocartilage scaffolds according to claim 2, characterized in that, The optimized formula for calculating the target pore size parameters is as follows: ； In the formula, The adjusted target pore parameters, H is the preset threshold, where H is the number of hops in the shortest path. is the calibration factor, and P is the target pore parameter.

4. The 3D printing method for the osteocartilage scaffold according to claim 1, characterized in that, The calculation expression for the porosity dynamic adjustment model is as follows: ； In the formula, P is the target porosity parameter. As a reference stress threshold, The local equivalent stress value obtained through finite element analysis. This refers to the material coefficient related to cell compatibility.

5. The 3D printing method for the osteocartilage scaffold according to claim 1, characterized in that, The material coefficients are calibrated using a cell migration efficiency model, the calculation expression of which is: ； ； In the formula, For cell migration resistance, The viscosity coefficient of the extracellular matrix. The rate of change of fluid velocity per unit distance along the direction of cell migration. This is the maximum allowable migration resistance value set according to cell type.

6. The 3D printing method for the osteocartilage scaffold according to claim 1, characterized in that, The transition layer includes a conical hole and serrated microstructures disposed within the hole wall of the conical hole. The calculation expression for the spacing of the serrated microstructures is as follows: ； ； In the formula, The spacing of the serrated microstructures The propagation speed of stress waves in the support material. The vibration frequency, The Young's modulus of the transition layer support material. The density of the transition layer support material. This represents the depth of the tapered hole.

7. The 3D printing method for osteocartilage scaffolds according to claim 1, characterized in that, The specific steps involved in using a composite 3D printer to sequentially print the subchondral bone layer, transition layer, and framework cartilage layer include: The subchondral bone layer was printed using a fused deposition modeling process with polyetheretherketone (PEEK) as the material and a printing temperature of 380℃-420℃. The upper surface of the printed polyetheretherketone subchondral bone layer was subjected to low-pressure plasma treatment for 30-60 seconds at a power of 100W. The transition layer was printed using an electrospinning process. The material was polycaprolactone, the fiber diameter was 1-5μm, and the pore size of the resulting fiber membrane was less than 18μm. The scaffold cartilage layer was printed using a low-temperature extrusion molding process, and the material was a gelatin-chitosan hydrogel containing TGF-β1 growth factor.

8. The 3D printing method for osteocartilage scaffolds according to claim 1, characterized in that, The specific steps for multi-stage cross-linking treatment of the printed scaffold include: The printed scaffold was immersed in a 5% CaCl2 solution for ionic cross-linking for 30 minutes. Photocrosslinking was performed using ultraviolet light with a wavelength of 365nm. The photocrosslinking time was determined based on the overall thickness of the scaffold, satisfying the following requirements: t=h 2 / D; In the formula, t is the photocrosslinking time, h is the overall thickness of the scaffold, and D is the diffusion coefficient of the photoinitiator in the corresponding material.

9. A 3D printing system for osteocartilage scaffolds, characterized in that, include: The acquisition module is used to acquire three-dimensional point cloud data of osteochondral defects through medical imaging. The analysis module is used to reconstruct a three-dimensional model of the defective part based on the point cloud data and to perform biomechanical stress-strain analysis on the model. The porosity adjustment module is used to establish a dynamic porosity adjustment model based on the stress distribution results and a structural optimization algorithm, so as to calculate the target porosity parameters of the scaffold cartilage layer, transition layer and subchondral bone layer based on the dynamic porosity adjustment model. The printing module is used to generate a printing path based on the target pore parameters and the three-dimensional model, and to use a composite 3D printer to sequentially print the subchondral bone layer, the transition layer and the scaffold cartilage layer. The crosslinking module is used to perform multi-stage crosslinking treatment on the printed stent.

10. The 3D printing system for osteocartilage scaffolds according to claim 9 is characterized in that, The system also includes: The optimization module is used to discretize the three-dimensional model of the support into a mesh based on the target pore parameters, where each mesh cell is regarded as a node and the connection between adjacent cells is regarded as an edge. Starting from all the pore nodes on the outer surface of the support, the pore network is traversed using a breadth-first search algorithm. The minimum number of edges from each internal pore node to the outer surface is calculated as the shortest path hop count. Optimize the target pore parameters so that the shortest path hop count is less than a preset threshold; The weight of the edge is determined based on the diffusion resistance of nutrients, and the calculation expression for the edge weight is as follows: In the formula, The weight of the edge. Let L be the permeability, L be the connection length between the centers of adjacent pores, and A be the cross-sectional area of ​​the pore.

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