Craniomaxillofacial repair system based on digital simulation

Abstract

The invention discloses a cranio-maxillofacial repair system based on digital simulation, particularly relates to the technical field of digital simulation, and can preliminarily predict and finely adjust a three-dimensional image of a bone defect area through mirror image overturning, functional area division and adjustment based on functional indexes, so that the actual bone defect condition is reflected more accurately. Powerful support is provided for the design of a subsequent repair scheme; by simulating the movement and function of a craniomaxillofacial surface, the function recovery condition after bone defect repair is predicted, and a function simulation quality index is output, so that a user can intuitively understand the repair effect, and a basis is provided for treatment decision making; performing conjoint analysis on the surface smoothness index, the functional simulation quality index and the simulation bone quality evaluation index, and outputting a bone reconstruction availability coefficient Ks; judging the relationship between the bone reconstruction availability coefficient and a corresponding threshold Tza; the problem that decision support cannot be scientifically provided for craniomaxillofacial repair in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of digital simulation, more particularly, the present application relates to a kind of craniofacial prosthesis system based on digital simulation. BACKGROUND

[0002] Clinical data clearly reveals the problem of serious bone defect difficult to heal after fracture, and the optimization of its treatment scheme is particularly urgent. At present, autologous bone transplantation is regarded as the gold standard for repairing such defects, but its limitations are significant: trauma caused by multiple operations, bone source limitations and complications in the donor area, which limit its wide application. Under this background, the rise of additive manufacturing technology (especially 3D printing technology) has injected new vitality into the field of bone tissue regeneration.

[0003] 3D printed scaffolds, with their highly personalized design based on accurate 3D images of patient bone defects and optimized porous structure, effectively promote blood circulation and bone tissue ingrowth. Flexible adjustment of its process parameters can also simulate the natural anisotropy of bone, providing unprecedented precision and adaptability for bone defect repair. The emergence of this technology not only overcomes the shortcomings of traditional methods in structural repeatability, but also significantly improves the effectiveness and success rate of bone regeneration and repair.

[0004] However, although 3D printed bone scaffolds show great potential, they still face challenges in practical application. In particular, in the field of craniofacial repair, traditional methods are difficult to comprehensively and objectively evaluate postoperative functional recovery, which has become a bottleneck restricting efficacy evaluation and treatment plan optimization. Therefore, the introduction of digital twin technology provides a solution to this problem. SUMMARY

[0005] In order to overcome the above-mentioned defects of the prior art, the present application provides a kind of craniofacial prosthesis system based on digital simulation to solve the problems raised in the above background art.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solution: a kind of craniofacial prosthesis system based on digital simulation, comprising: The data acquisition module performs CT and MRI scanning of the patient's craniofacial region to obtain two-dimensional craniofacial image data of the patient; The three-dimensional reconstruction module is used to convert the two-dimensional craniofacial image data into a three-dimensional model, and outputs a three-dimensional craniofacial model A of the patient; The bone defect area acquisition module is used to obtain a bone defect area image B of the patient; The availability analysis module analyzes the bone defect area image B and outputs a surface smoothness index SI; places the bone defect area image B in the craniofacial three-dimensional model A to obtain a reconstructed craniofacial three-dimensional model, predicts a functional index of the reconstructed craniofacial three-dimensional model through simulation testing, and outputs a function simulation quality index Gz; combines the bone defect area image B with 3D printing software to perform 3D printing, and outputs the to-be-implanted simulation bone and a simulation bone quality evaluation index FQI of the to-be-implanted simulation bone; The availability evaluation module jointly analyzes the surface smoothness index, the function simulation quality index, and the simulation bone quality evaluation index, and outputs a bone reconstruction availability coefficient Ks; the bone reconstruction availability coefficient Ks is obtained through the formula The bone reconstruction availability coefficient Ks is obtained through joint analysis; The availability judgment module is configured to judge the relationship between the bone reconstruction availability coefficient and the corresponding threshold Tza; if the bone reconstruction availability coefficient exceeds the threshold Tza, it indicates that the to-be-implanted simulation bone is available; otherwise, the bone defect area acquisition module is returned to regenerate the bone defect area image B; if the bone reconstruction availability coefficient Ks exceeds the threshold, it indicates that the to-be-implanted simulation bone meets the preset level in terms of physical properties, functional recovery, and manufacturing quality, and is therefore judged to be available; if the bone reconstruction availability coefficient Ks does not exceed the threshold, it indicates that the simulation bone is insufficient and cannot meet the expectation, and is therefore judged to be unavailable.

[0007] Preferably, the bone defect area acquisition module includes a defect area preliminary acquisition unit and a region adjustment unit. The defect area preliminary acquisition unit: uses the mirror symmetry of the patient's craniofacial mirror to flip the reference through the mirror to preliminarily predict the shape and size of the bone defect area, and outputs a first predicted bone defect three-dimensional image; the region adjustment unit: divides the craniofacial into a plurality of functional regions according to anatomical structure and functional requirements, and locates the functional region where the bone defect is located; based on the function corresponding to the functional region, adjusts the morphology, size, and connection relationship of the surrounding bone structure of the first predicted bone defect three-dimensional image, ensures that the reconstructed bone structure meets the functional requirements, and outputs the bone defect area image B.

[0008] Preferably, the availability analysis module includes a surface smoothness analysis unit, a simulation test analysis unit, and a simulation bone quality analysis unit, the surface smoothness analysis unit is configured to obtain the surface smoothness index SI of the bone defect area image B; the simulation test analysis unit is configured to obtain the simulation bone quality evaluation index FQI; the simulation bone quality analysis unit is configured to obtain the simulation bone quality evaluation index FQI of the to-be-implanted simulation bone; the simulation test analysis unit includes the following contents: Build a craniofacial digital twin model; According to the actual movement and functional requirements of the craniofacial, simulation parameters such as masticatory force, respiratory airflow, and craniofacial muscle movement are set; The simulation parameters are input into the craniofacial digital twin model, and the simulation test is started; The performance of the craniofacial in the simulation test is observed, and the quantitative parameters of the functional indicators of the bone defect repair area are recorded; The quantitative parameters of the functional indicators are jointly analyzed, and the simulation bone quality evaluation index is output; Based on the functional simulation quality index, it is predicted whether the functional recovery after bone defect repair meets the expectation.

[0009] Preferably, the first predicted bone defect three-dimensional image is obtained by loading two-dimensional craniofacial image data of the patient from a storage medium; selecting a healthy side of the patient's craniofacial as a reference to create a mirror image; superimposing the mirror image and the original image, and identifying the bone defect area through transparency adjustment or difference highlighting function; using image measurement to quantify the size, shape and position of the bone defect, and generating the first predicted bone defect three-dimensional image; The bone defect area image B is obtained by: according to the anatomical structure of the craniofacial, the craniofacial is divided into different functional areas; the importance of each functional area to the functional indicators is evaluated; based on the requirements of the functional areas, the shape and size of the first predicted bone defect three-dimensional image are adjusted, including adjusting the shape of the defect to match the surrounding bone structure, and increasing or reducing the size of the defect area according to the functional requirements.

[0010] Preferably, the surface smoothness index SI is obtained by: Let the point set on the surface of the bone defect area image B be S={(x q , y q , z q )}, where q=1, 2, …, P, where P represents the total number of points; Calculate the Gaussian curvature K q of each point (x q , y q , z q ); the surface smoothness index SI is calculated by the formula , which represents the average value of the Gaussian curvature of all points.

[0011] Preferably, the acquisition process of the functional simulation quality index includes the following steps: ​Step S11, data collection and preprocessing: collect the functional indicators of the reconstructed craniofacial three-dimensional model, and set m functional indicators, use i and j to represent the sequential number of the functional indicators, i, j ∈ m, and i≠j; the normalization method used is linear normalization, which is used to scale each functional indicator to between 0 and 1, and the quantization parameter of the i th functional indicator is denoted as x i, and the quantization parameter of the j th functional indicator is denoted as x j ; Step S12, use the Pearson correlation coefficient to calculate the correlation between the functional indicators, and denote the correlation coefficient of the functional indicator i and the functional indicator j as r ij ; Step S13, set the base weight of the i th functional indicator as w 0i, and use the correlation coefficient to adjust the base weight, according to the formula Output the weight w i of the i th functional indicator i ; Step S14, weighted summation, calculate the functional simulation quality index G z through the formula , wherein δ represents the accuracy influence coefficient of the simulation test; the higher the accuracy, the closer the accuracy influence coefficient to 1, otherwise closer to 0.

[0012] Preferably, the correlation coefficient is obtained in the following manner: Perform n simulation tests, use k to represent the sequential number of the simulation test, record the quantization parameter of each functional indicator, and perform normalization processing on the quantization parameter; calculate the correlation coefficient r ij of the functional indicator i and the functional indicator j through the formula ; wherein x ij and x i (k) and x j (k) are the normalized values of the functional indicator i and the functional indicator j in the k th sample respectively, and x i_ and x j_ are the normalized mean values of the functional indicator i and the functional indicator j respectively.

[0013] Preferably, the simulation bone quality evaluation index FQI is obtained in the following manner: Scan the simulation bone to be implanted to obtain a simulation bone three-dimensional image, calculate the design similarity of the simulation bone three-dimensional image and the bone defect region image B, denoted as x s ; Analyze the pore connectivity of the simulation bone to be implanted, and output the pore connectivity parameter k x ; Analyze the material of the simulation bone to be implanted, and output the mechanical stability parameter l w ; Input the design similarity, pore connectivity parameter and mechanical stability parameter into the simulation bone quality evaluation model, and output the simulation bone quality evaluation index; the simulation bone quality evaluation model satisfies the formula a, b, c respectively represent the influence index of each item, a, b, c are adjusted according to specific application scenarios and requirements to reflect the importance of different parameters in evaluation.

[0014] Preferably, when the surface smoothness index SI and the function simulation quality index meet the requirements at the same time, the bone defect area image B is combined with the 3D printing software to design the to-be-implanted simulation bone which fits the shape of the patient's bone defect, and 3D printing is performed; otherwise, the bone defect area image B is regenerated; the bone defect area image B is combined with the 3D printing software to design the bone implant model which fits the shape of the patient's bone defect, and 3D printing is performed to output the to-be-implanted simulation bone.

[0015] Preferably, when the surface smoothness index SI and the function simulation quality index meet the requirements at the same time, the bone defect area image B is combined with the 3D printing software to design the to-be-implanted simulation bone which fits the shape of the patient's bone defect, and 3D printing is performed; otherwise, the bone defect area image B is regenerated; the bone defect area image B is combined with the 3D printing software to design the bone implant model which fits the shape of the patient's bone defect, and 3D printing is performed to output the to-be-implanted simulation bone; according to the clinical requirements and the patient's condition, a suitable 3D printing ceramic material is selected.

[0016] The technical effects and advantages of the present application are as follows: (1) The craniofacial repair system based on digital simulation provided by the present application can preliminarily predict and finely adjust the three-dimensional image of the bone defect area through mirror flipping, function area division and adjustment based on function indicators, so as to more accurately reflect the actual bone defect situation and provide strong support for the design of subsequent repair schemes; through simulation of the movement and function of the craniofacial, the function recovery situation after bone defect repair is predicted, and the function simulation quality index is output, so that the user can intuitively understand the repair effect and provide a basis for treatment decision; the surface smoothness index, the function simulation quality index and the simulation bone quality evaluation index are analyzed jointly, and the bone reconstruction availability coefficient Ks is output; the relationship between the bone reconstruction availability coefficient and the corresponding threshold Tza is judged; the problem that the existing technology cannot scientifically provide decision support for craniofacial repair is solved.

[0017] (2) The digital simulation-based craniofacial repair system provided by the present invention designs a personalized simulated bone to be implanted according to the patient's specific bone defect conditions and combines 3D printing technology, and evaluates its quality through the quality evaluation index of the simulated bone to be implanted. This personalized repair plan can better meet the needs of patients and improve the repair effect; by jointly analyzing multiple evaluation indexes (surface smoothness index, functional simulation quality index, simulated bone quality evaluation index), it can automatically evaluate the availability of bone reconstruction and give a clear judgment result; if the evaluation result does not meet the requirements, it automatically returns to the bone defect area acquisition module to regenerate the bone defect area image until a satisfactory repair plan is obtained. This automated evaluation and feedback mechanism greatly improves the design efficiency and accuracy of the repair plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flowchart of the craniomaxillofacial restoration process based on digital simulation of the present invention.

[0019] Figure 2 This is a structural block diagram of the craniomaxillofacial repair system of the present invention. DETAILED DESCRIPTION

[0020] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0021] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0022] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present disclosure, its application, or uses.

[0023] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification. Example

[0024] See Figure 1 The flowchart of craniomaxillofacial restoration based on digital simulation and Figure 2 The structural block diagram of the craniomaxillofacial repair system is shown in FIG. Figure 1 A craniomaxillofacial restoration system based on digital simulation is shown, comprising: The data acquisition module performs CT and MRI scans on the patient's craniofacial region to obtain two-dimensional craniofacial image data of the patient; and exports the two-dimensional craniofacial image data obtained by scanning to a storage medium; It is explained that during the data acquisition process, ensure that the CT (computed tomography) and MRI (magnetic resonance imaging) equipment is in good working condition, select appropriate scanning parameters such as slice thickness and resolution according to the patient's condition; perform denoising and contrast enhancement preprocessing on the two-dimensional craniofacial image data to improve the quality of three-dimensional reconstruction; the contrast enhancement preprocessing involves threshold segmentation and surface reconstruction steps; adjust the smoothness and detail level of the model to ensure that the model accurately reflects the actual shape of the patient's craniofacial region and is convenient for subsequent analysis; The three-dimensional reconstruction module converts the two-dimensional craniofacial image data into a three-dimensional model using professional medical image three-dimensional reconstruction software such as Mimics and 3DSlicer, and outputs a three-dimensional craniofacial model A of the patient; The bone defect area acquisition module is used to obtain a bone defect area image B of the patient; the shape and size of the bone defect area are preliminarily predicted by mirroring the undamaged side as a reference, and a first predicted bone defect three-dimensional image is output; the craniofacial region is divided into several functional areas, and the functional area where the bone defect is located is located; based on the function corresponding to the functional area, the function index of the bone defect to the craniofacial function is used as a constraint to adjust the shape, size and bone structure connection relationship of the first predicted bone defect three-dimensional image, and a bone defect area image B is output; The usability analysis module analyzes the bone defect area image B and outputs a surface smoothness index SI; the bone defect area image B is placed in the three-dimensional craniofacial model A to obtain a reconstructed three-dimensional craniofacial model, the function index of the reconstructed three-dimensional craniofacial model is predicted through simulation test, and a function simulation quality index Gz is output; the bone defect area image B is combined with 3D printing software to perform 3D printing, and a to-be-implanted simulation bone is output, and a simulation bone quality evaluation index FQI of the to-be-implanted simulation bone is output; The usability evaluation module jointly analyzes the surface smoothness index, the function simulation quality index and the simulation bone quality evaluation index, and outputs a bone reconstruction usability coefficient Ks; the bone reconstruction usability coefficient Ks is calculated by the formula The bone reconstruction usability coefficient Ks is obtained by joint analysis; The usability judgment module is used to judge the relationship between the bone reconstruction usability coefficient and the corresponding threshold Tza; if the bone reconstruction usability coefficient exceeds the threshold Tza, it indicates that the to-be-implanted simulation bone is usable; otherwise, return to the bone defect area acquisition module to regenerate the bone defect area image B; if the bone reconstruction usability coefficient Ks exceeds the threshold, it indicates that the to-be-implanted simulation bone meets the preset level in terms of physical properties, function recovery and manufacturing quality, and is therefore judged to be usable; if the bone reconstruction usability coefficient Ks does not exceed the threshold, it indicates that the simulation bone is insufficient and cannot meet the expectation, and is therefore judged to be unusable.

[0025] Further, the bone defect area acquisition module comprises a defect area preliminary acquisition unit and an area adjustment unit: The defect area preliminary acquisition unit: utilizes the mirror symmetry of the patient's craniofacial mirror, takes the undamaged side as a reference, and preliminarily predicts the shape and size of the bone defect area by mirror flipping, and outputs a first predicted bone defect three-dimensional image; the area adjustment unit: divides the craniofacial region into several functional areas according to anatomical structure and functional requirements, and locates the functional area where the bone defect is located; based on the function corresponding to the functional area, taking the functional index of the bone defect to the craniofacial function as a constraint, adjusting the shape, size and connection relationship of the surrounding bone structure of the first predicted bone defect three-dimensional image, ensuring that the reconstructed bone structure meets the functional requirements, and outputting a bone defect area image B.

[0026] In a possible embodiment, the first predicted bone defect three-dimensional image is obtained by: using a simulated craniofacial model to preliminarily predict the shape and size of the bone defect area, and outputting a first predicted bone defect three-dimensional image; for asymmetric bone defect cases, a simulated craniofacial model is used for prediction; by constructing a highly realistic craniofacial digital twin model, and based on known defect information (such as X-ray film, CT scan, etc.), the occurrence process of the bone defect is simulated, so as to preliminarily predict the shape, size and position of the bone defect, and generate a corresponding three-dimensional image.

[0027] Further, the availability analysis module comprises a surface smoothness analysis unit, a simulation test analysis unit and a simulation bone quality analysis unit, the surface smoothness analysis unit is used to obtain the surface smoothness index SI of the bone defect area image B; the simulation test analysis unit is used to obtain the simulation bone quality evaluation index FQI; the simulation bone quality analysis unit is used to obtain the simulation bone quality evaluation index FQI of the simulation bone to be implanted; The simulation test analysis unit comprises the following contents: Building a craniofacial digital twin model; According to the actual movement and functional requirements of the craniofacial region, set the simulation parameters, such as chewing force, respiratory airflow, craniofacial muscle movement; Input the simulation parameters into the craniofacial digital twin model and start the simulation test; Observe the performance of the craniofacial region in the simulation test, and record the quantitative parameters of the functional indicators of the bone defect repair area; Jointly analyze the quantitative parameters of the functional indicators, and output the simulation bone quality evaluation index; Based on the functional simulation quality index, predict whether the functional recovery after bone defect repair meets the expectation.

[0028] What needs to be further explained in the embodiment of the present invention is that the first predicted bone defect three-dimensional image is obtained by: loading the patient's two-dimensional craniomaxillofacial image data from a storage medium; selecting the healthy side of the patient's craniomaxillofacial region as a reference and creating its mirror image; superimposing the mirror image with the original image, and identifying the bone defect area through transparency adjustment or difference highlighting function; using image measurement to quantify the size, shape and position of the bone defect, and generating the first predicted bone defect three-dimensional image; the bone defect area image B is obtained by: according to the anatomical structure of the craniomaxillofacial region, such as the frontal bone, parietal bone, temporal bone, maxilla, mandible The craniofacial region is divided into different functional areas according to the structure of the bones, etc.; the importance of each functional area to functional indicators, such as chewing, breathing, vision and other craniofacial functions, is evaluated; based on the needs of the functional areas, the morphology and size of the first predicted bone defect three-dimensional image are adjusted, including adjusting the shape of the defect to match the surrounding bone structure, increasing or decreasing the size of the defect area according to functional needs, and outputting a bone defect area image B; maxillofacial surgery experts or medical experts in related fields are invited to review the adjusted bone defect three-dimensional image to ensure that it meets the anatomical structure and functional requirements, and the approved bone defect area image B is used in subsequent steps.

[0029] Furthermore, the surface smoothness index SI is obtained as follows: Assume that the point set on the surface of the bone defect area image B is S={(x q ,y q , z q )}, where q = 1, 2, ..., P, where P represents the total number of points; calculate each point (x q ,y q , z q )'s Gaussian curvature K q ; Through the formula The surface smoothness index SI is calculated. Represents the average value of the Gaussian curvature of all points.

[0030] Furthermore, the process of obtaining the functional simulation quality index includes the following steps: Step S11, data collection and preprocessing: collecting functional indicators of the reconstructed craniomaxillofacial three-dimensional model, assuming m functional indicators, with i and j representing the sequential numbers of the functional indicators, i, j∈m, and i≠j; the normalization method used is linear normalization, which is used to scale each functional indicator to a range between 0 and 1, and the quantitative parameter of the i-th functional indicator is recorded as xi, and the quantitative parameter of the j-th functional indicator is recorded as xj; Step S12: Use the Pearson correlation coefficient to calculate the correlation between the functional indicators, and record the correlation coefficient between the functional indicator i and the functional indicator j as rij; Step S13: Assume the basic weight of the i-th functional index is w0i, and use the correlation coefficient to adjust the basic weight according to the formula Output the weight w of the i-th functional index i ; Step S14: weighted summation, by formula The functional simulation quality index Gz is calculated, where δ represents the accuracy influence coefficient of the simulation test; the higher the accuracy, the closer the accuracy influence coefficient is to 1, otherwise it is closer to 0.

[0031] Furthermore, the correlation coefficient is obtained as follows: Carry out n simulation tests, use k to represent the order number of the simulation tests, record the quantitative parameters of each functional indicator, and normalize the quantitative parameters; through the formula Calculate the correlation coefficient r between functional index i and functional index j ij ; where x i (k) and x j (k) are the normalized values ​​of function index i and function index j in the kth sample, x i_ and x j_ are the normalized means of functional index i and functional index j, respectively.

[0032] Furthermore, the method for obtaining the simulated bone quality assessment index FQI is: Scan the simulated bone to be implanted to obtain a three-dimensional image of the simulated bone, and calculate the design similarity between the three-dimensional image of the simulated bone and the image B of the bone defect area, denoted as xs; the design similarity is a value between 0 (completely dissimilar) and 1 (completely identical); Analyze the pore connectivity of the simulated bone to be implanted and output the pore connectivity parameter kx. The pore connectivity is obtained based on the complexity of the pore network and the number of connected paths. The pore connectivity is a value between 0 (completely disconnected) and 1 (completely connected). Analyze the simulated bone material to be implanted and output a mechanical stability parameter lw. The mechanical stability parameter indicates the stability of the simulated bone material to be implanted under mechanical load. The mechanical stability parameter is related to the properties, structural design, and porosity of the simulated bone material. The mechanical stability parameter is a value between 0 (extremely unstable) and 1 (very stable). The design similarity, pore connectivity parameter and mechanical stability parameter are input into the simulated bone quality evaluation model, and the simulated bone quality evaluation index is output; the simulated bone quality evaluation model satisfies the formula , a, b, c represent the impact index of each item respectively. a, b, c are adjusted according to the specific application scenarios and requirements to reflect the importance of different parameters in the evaluation.

[0033] Further, when the surface smoothness index SI and the function simulation quality index simultaneously meet the requirements, the bone defect region image B is combined with 3D printing software to design a to-be-implanted simulation bone that fits the shape of the bone defect of the patient and is subjected to 3D printing; otherwise, the bone defect region image B is regenerated; the bone defect region image B is combined with 3D printing software to design a bone implant model that fits the shape of the bone defect of the patient and is subjected to 3D printing, and a to-be-implanted simulation bone is output.

[0034] Further, when the surface smoothness index SI and the function simulation quality index simultaneously meet the requirements, the bone defect region image B is combined with 3D printing software to design a to-be-implanted simulation bone that fits the shape of the bone defect of the patient and is subjected to 3D printing; otherwise, the bone defect region image B is regenerated; the bone defect region image B is combined with 3D printing software to design a bone implant model that fits the shape of the bone defect of the patient and is subjected to 3D printing, and a to-be-implanted simulation bone is output; according to clinical requirements and patient conditions, a suitable 3D printing ceramic material, such as a bioceramic, is selected.

[0035] Embodiment 2 The embodiment of the present application provides a building process of a craniofacial digital twin model, including the following steps: Data acquisition: using high-precision medical imaging equipment such as cone beam tomography CT (CBCT) or MRI (magnetic resonance imaging) to scan the craniofacial region and obtain detailed anatomical structure data; combining with motion capture technology or real-time imaging technology to collect dynamic data of the craniofacial region; Three-dimensional modeling: using medical image processing software to process the collected data to extract the structures of the craniofacial bones and soft tissues; using three-dimensional modeling software to construct a craniofacial three-dimensional model according to the extracted data, and ensuring the accuracy and details of the model during the modeling process to reflect the real anatomical structure; Digital twin platform building: importing the craniofacial three-dimensional model into simulation software to obtain a craniofacial digital twin model; setting physical properties (such as density, elastic modulus, etc.) and boundary conditions (such as constraints, loads, etc.); Simulation and verification: performing simulation calculation to simulate various functional activities (such as craniofacial muscle movements such as chewing and opening mouth) of the craniofacial region, predict the response and changes of the craniofacial digital twin model, and verify the accuracy and reliability of the craniofacial digital twin model by comparison with real data; outputting the verified craniofacial digital twin model.

[0036] It needs to be further explained in the embodiments of the present application that setting the simulation parameters comprises: setting reasonable chewing force size and direction according to the age, gender, and chewing habits of the patient, combined with the principle of biomechanics; considering the airway structure of the nasal cavity and oral cavity, setting parameters such as airflow speed and flow during the breathing process to simulate the respiratory function; setting muscle contraction force, range of motion, speed parameters according to the anatomical structure and functional characteristics of the muscle to simulate the dynamic movement of the craniofacial.

[0037] It needs to be further explained in the embodiments of the present application that for functional indicators such as chewing efficiency, respiratory patency, craniofacial movement coordination, and visual abnormality, a quantitative evaluation method of the functional indicators is designed, and the embodiments of the present application do not make a unique limitation on the quantitative evaluation method of the functional indicators; for example, the chewing efficiency is evaluated by calculating the food crushing rate during chewing; the respiratory patency is evaluated by simulating the airway resistance during the breathing process; the craniofacial movement coordination is evaluated by measuring the joint movement trajectory and muscle contraction coordination; and the visual abnormality is evaluated by simulating the changes of the visual system.

[0038] It needs to be further explained in the embodiments of the present application that the similarity (such as the error percentage) between the craniofacial digital twin model and the real anatomical structure, and the accuracy influence coefficient of the simulation results and the experimental data are analyzed; a linear normalization formula is used to convert the quantitative parameters into a value between 0 and 1, where 0 represents the worst (such as completely inconsistent), and 1 represents the best (such as completely consistent).

[0039] Summary: The digital twin model can receive data from the physical world in real time and make corresponding analysis and prediction; in the craniofacial test, the changes of the craniofacial are observed and analyzed in real time, and adjustments and optimizations are made as needed; through the craniofacial test by the digital twin model, the risk and cost can be reduced.

[0040] Finally: The above only describes the preferred embodiments of the present application and is not used to limit the present application, and any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A digital simulation-based craniofacial prosthesis system, characterized by, The method comprises the following steps: a data acquisition module, which performs CT and MRI scans on the patient's craniofacial region to obtain two-dimensional craniofacial image data of the patient; a three-dimensional reconstruction module, which is used to convert the two-dimensional craniofacial image data into a three-dimensional model and output a three-dimensional craniofacial model A of the patient; a bone defect area acquisition module, which is used to obtain a bone defect area image B of the patient; an availability analysis module, which analyzes the bone defect area image B and outputs a surface smoothness index SI; places the bone defect area image B in the three-dimensional craniofacial model A to obtain a reconstructed three-dimensional craniofacial model, predicts the functional indicators of the reconstructed three-dimensional craniofacial model through simulation testing, and outputs a functional simulation quality index Gz; combines the bone defect area image B with 3D printing software to perform 3D printing, and outputs a simulated bone to be implanted and a simulation bone quality evaluation index FQI of the simulated bone to be implanted; The availability evaluation module combines and analyzes the surface smoothness index, the function simulation quality index and the simulation bone mass evaluation index to output a bone reconstruction availability coefficient Ks. The bone reconstruction availability coefficient Ks is obtained by combined analysis. an availability judgment module, which is used to determine the relationship between the bone reconstruction availability coefficient and the corresponding threshold Tza; if the bone reconstruction availability coefficient exceeds the threshold Tza, it indicates that the simulated bone to be implanted is available; otherwise, the bone defect area acquisition module is returned to regenerate the bone defect area image B.

2. The digitally simulated craniofacial repair system of claim 1, wherein, The bone defect area acquisition module comprises a defect area preliminary acquisition unit and a region adjustment unit: The defect area preliminary acquisition unit uses the mirror symmetry of the patient's craniofacial region, takes the undamaged side as a reference, and preliminarily predicts the shape and size of the bone defect area by mirror flipping to output a first predicted bone defect three-dimensional image; The region adjustment unit divides the craniofacial region into several functional regions according to anatomical structures and functional requirements, locates the functional region where the bone defect is located, adjusts the morphology, size and connection relationship of the surrounding bone structure of the first predicted bone defect three-dimensional image based on the functions corresponding to the functional regions, and ensures that the reconstructed bone structure meets the functional requirements to output the bone defect area image B.

3. The digitally simulated craniofacial repair system of claim 1, wherein, The availability analysis module comprises a surface smoothness analysis unit, a simulation test analysis unit and a simulation bone quality analysis unit, the surface smoothness analysis unit is used to obtain the surface smoothness index SI of the bone defect area image B; the simulation test analysis unit is used to obtain the simulation bone quality evaluation index FQI; and the simulation bone quality analysis unit is used to obtain the simulation bone quality evaluation index FQI of the simulated bone to be implanted; The simulation test analysis unit comprises the following contents: building a craniofacial digital twin model; setting simulation parameters according to the actual movement and functional requirements of the craniofacial region, such as chewing force, respiratory airflow and craniofacial muscle movement; inputting the simulation parameters into the craniofacial digital twin model to start the simulation test; observing the performance of the craniofacial region in the simulation test and recording the quantitative parameters of the functional indicators of the bone defect repair region; jointly analyzing the quantitative parameters of the functional indicators to output the simulation bone quality evaluation index; predicting whether the functional recovery after bone defect repair meets the expectation based on the functional simulation quality index.

4. The digitally simulated craniofacial repair system of claim 1, wherein, The surface smoothness index SI is obtained in the following manner: Let the point set on the surface of the bone defect region image B be S={(x q ,y q ,z q )} where q=1,2,…,P, where P represents the total number of points; calculate the Gaussian curvature K q of each point (x q ,y q ,z q ); the surface smoothness index SI, is calculated by the formula , which represents the average value of the Gaussian curvature of all points.

5. The digitally simulated craniofacial repair system of claim 1, wherein, The acquisition process of the functional simulation quality index comprises the following steps: Step S11, data collection and preprocessing: collecting functional indicators of the reconstructed posterior craniomaxillofacial three-dimensional model, assuming m functional indicators, with i and j representing the sequential numbers of the functional indicators, i, j∈m, and i≠j; The normalization method used is linear normalization, which is used to scale each functional index to between 0 and 1. The quantitative parameter of the i-th functional index is recorded as xi, and the quantitative parameter of the j-th functional index is recorded as xj; Step S12: Use the Pearson correlation coefficient to calculate the correlation between the functional indicators, and record the correlation coefficient between the functional indicator i and the functional indicator j as rij; Step S13, set the base weight of the i-th function index as w0i, use the correlation coefficient to adjust the base weight, according to the formula Output the weight wi of the i-th function index; Step S14, weighted summation, by formula The functional simulation quality index Gz is calculated, wherein δ represents the accuracy influence coefficient of the simulation test; the higher the accuracy, the closer the accuracy influence coefficient to 1, otherwise closer to 0.

6. The digitally simulated craniofacial repair system of claim 5, wherein, The correlation coefficient is obtained as follows: n simulation tests are performed, k represents the sequential number of the simulation test, the quantification parameters of each functional index are recorded, and the quantification parameters are normalized; the correlation coefficient r of the functional index i and the functional index j is calculated by the formula ij ; wherein x i (k) and x j (k) are the normalized values of the functional index i and the functional index j in the kth sample, respectively, and x i_ and x j_ are the normalized mean values of the functional index i and the functional index j, respectively.​ 7. The digitally simulated craniofacial repair system of claim 1, wherein, The method for obtaining the simulated bone quality assessment index FQI is as follows: Scan the simulated bone to be implanted to obtain a three-dimensional image of the simulated bone, and calculate the design similarity between the three-dimensional image of the simulated bone and the image B of the bone defect area, which is recorded as xs; Analyze the pore connectivity of the simulated bone to be implanted and output the pore connectivity parameter kx; Analyze the simulated bone material to be implanted and output the mechanical stability parameter lw; The design similarity, the pore connectivity parameter and the mechanical stability parameter are input into the simulation bone mass evaluation model, and a simulation bone mass evaluation index is output; the simulation bone mass evaluation model satisfies the formula , a, b, c respectively represent the influence index of each term, and a, b, c are adjusted according to specific application scenarios and requirements to reflect the importance of different parameters in evaluation.

8. The digitally simulated craniofacial repair system of claim 1, wherein, When the surface smoothness index SI and the functional simulation quality index meet the requirements at the same time, the bone defect area image B is combined with the 3D printing software to design a simulated bone to be implanted that fits the shape of the patient's bone defect, and 3D printing is performed; otherwise, the bone defect area image B is regenerated; the bone defect area image B is combined with the 3D printing software to design a bone implant model that fits the shape of the patient's bone defect, and 3D printing is performed to output the simulated bone to be implanted.

9. The digitally simulated craniofacial repair system of claim 1, wherein, When the surface smoothness index and the functional simulation quality index both meet the preset requirements, the bone defect area image B is combined with the 3D printing software to design a simulated bone to be implanted that fits the shape of the patient's bone defect and perform 3D printing; Otherwise, regenerate the bone defect area image B; combine the bone defect area image B with the 3D printing software to design a bone implant model that fits the shape of the patient's bone defect, and perform 3D printing to output the simulated bone to be implanted; select the 3D printing ceramic material based on clinical needs and patient conditions.

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