A digital simulation-based craniofacial prosthesis system

Abstract

The application discloses a kind of craniofacial prosthesis systems based on digital simulation, specifically relates to digital simulation technical field, can preliminary predict and fine adjustment the three-dimensional image of bone defect area by mirror flip, functional area division and adjustment based on functional index, to more accurately reflect actual bone defect situation, provide strong support for subsequent repair scheme design;Through simulation simulation craniofacial movement and function, predict the functional recovery after bone defect repair, and output function simulation quality index, so that user can intuitively understand the repair effect, provide basis for treatment decision;Joint analysis surface smoothness index, function simulation quality index and simulation bone quality evaluation index, output bone reconstruction availability coefficient Ks;Judge the relationship between bone reconstruction availability coefficient and corresponding threshold Tza;Solve the problem that prior art cannot scientifically provide decision support for craniofacial prosthesis.

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 treatment scheme is particularly urgent. At present, autologous bone grafting 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:

[0007] 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;

[0008] 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;

[0009] The bone defect area acquisition module is used to obtain a bone defect area image B of the patient;

[0010] 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;

[0011] 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 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

[0012] 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.

[0013] Preferably, the bone defect area acquisition module includes a defect area preliminary acquisition unit and a region adjustment unit.

[0014] 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 mirror into a plurality of functional regions according to the 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, the function index of the bone defect to the craniofacial function is used as a constraint to adjust the morphology, size, and connection relationship of the surrounding bone structure of the first predicted bone defect three-dimensional image, to ensure that the reconstructed bone structure meets the functional requirements, and outputs the bone defect area image B.

[0015] 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; and the simulation test analysis unit includes the following contents:

[0016] A craniofacial digital twin model is built;

[0017] 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;

[0018] The simulation parameters are input into the craniofacial digital twin model, and the simulation test is started;

[0019] 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;

[0020] The quantitative parameters of the functional indicators are jointly analyzed, and the simulation bone quality evaluation index is output;

[0021] Based on the functional simulation quality index, it is predicted whether the functional recovery after bone defect repair meets the expectation.

[0022] 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;

[0023] 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.

[0024] Preferably, the surface smoothness index SI is obtained by:

[0025] 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;

[0026] 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.

[0027] Preferably, the functional simulation quality index is obtained by the following steps:

[0028] Step S11, Data Collection and Preprocessing: Collect functional indicators of the reconstructed three-dimensional craniofacial model. There are m functional indicators, and i and j represent 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 between 0 and 1. The quantization parameter of the i-th functional indicator is denoted as xi, and the quantization parameter of the j-th functional indicator is denoted as xj.

[0029] Step S12: Use the Pearson correlation coefficient to calculate the correlation between each functional indicator, and denote the correlation coefficient between functional indicator i and functional indicator j as rij;

[0030] Step S13: Let the base weight of the i-th functional indicator be w0i. Use the correlation coefficient to adjust the base weight according to the formula. Output the weight w of the i-th functional indicator i ;

[0031] Step S14: Weighted summation, using the 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.

[0032] Preferably, the correlation coefficient is obtained in the following way:

[0033] Perform n simulation tests, denoted by k, to represent the sequential number of the simulation tests. Record the quantitative parameters of each functional indicator and normalize the quantitative parameters. Then, use the formula... The correlation coefficient r between functional index i and functional index j was calculated. ij ;where x i (k) and x j (k) These are the normalized values ​​of functional index i and functional index j in the k-th sample, respectively, x i_ and x j_ These are the normalized means of functional indicators i and j, respectively.

[0034] Preferably, the simulated bone quality assessment index (FQI) is obtained in the following way:

[0035] 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;

[0036] Analyze the pore connectivity of the simulated bone to be implanted and output the pore connectivity parameter kx;

[0037] Analyze the simulated bone material to be implanted and output the mechanical stability parameter lw;

[0038] Input the design similarity, pore connectivity parameter and mechanical stability parameter into the simulation bone quality evaluation model, and output a simulation bone quality evaluation index; the simulation bone quality evaluation model satisfies the formula , a, b, c respectively represent the influence index of each term, a, b, c are adjusted according to specific application scenarios and requirements to reflect the importance of different parameters in evaluation.

[0039] Preferably, 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 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, and the to-be-implanted simulation bone is output.

[0040] Preferably, 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 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, and the to-be-implanted simulation bone is output; according to the clinical requirements and the patient's condition, a suitable 3D printing ceramic material is selected.

[0041] The technical effects and advantages of the present application are as follows:

[0042] (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, functional area division and adjustment based on functional indicators, so as to more accurately reflect the actual bone defect situation and provide strong support for the design of subsequent repair schemes; by simulating the movement and function of the craniofacial region, the functional recovery after bone defect repair is predicted, and the functional 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 functional 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 prior art cannot scientifically provide decision support for craniofacial repair is solved.

[0043] (2) The craniofacial repair system based on digital simulation provided by the present invention designs a personalized simulated bone to be implanted based on the patient’s specific bone defect condition and combined with 3D printing technology. The quality of the simulated bone to be implanted is evaluated by the quality assessment index of the simulated bone to be implanted. This personalized repair plan can better meet the needs of the patient and improve the repair effect. By jointly analyzing multiple assessment indices (surface smoothness index, functional simulation quality index, simulated bone quality assessment index), the availability of bone reconstruction can be automatically assessed and a clear judgment result can be given. If the assessment 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 assessment and feedback mechanism greatly improves the design efficiency and accuracy of the repair plan. Attached Figure Description

[0044] Figure 1 This is a flowchart of the craniofacial repair process based on digital simulation of the present invention.

[0045] Figure 2 This is a structural block diagram of the craniofacial repair system of the present invention. Detailed Implementation

[0046] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0047] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0048] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0049] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification. Example

[0050] See Figure 1 A flowchart of craniofacial reconstruction based on digital simulation and Figure 2 The structural block diagram of the craniofacial repair system is provided in the embodiments of the present invention. Figure 1 The illustrated craniofacial reconstruction system based on digital simulation includes:

[0051] A data acquisition module, performing CT and MRI scans on a patient's craniofacial region to obtain two-dimensional craniofacial image data of the patient; exporting the two-dimensional craniofacial image data obtained by scanning to a storage medium;

[0052] It is explained that during the data acquisition process, the CT (computed tomography) and MRI (magnetic resonance imaging) devices are ensured to be in good working condition, and appropriate scanning parameters such as slice thickness and resolution are selected according to the patient's condition; the two-dimensional craniofacial image data is preprocessed by denoising and contrast enhancement to improve the quality of three-dimensional reconstruction; the contrast enhancement preprocessing involves threshold segmentation and surface reconstruction steps; the smoothness and detail level of the model are adjusted to ensure that the model accurately reflects the actual shape of the patient's craniofacial region and is convenient for subsequent analysis;

[0053] A three-dimensional reconstruction module, using professional medical image three-dimensional reconstruction software such as Mimics and 3DSlicer, converts the two-dimensional craniofacial image data into a three-dimensional model using three-dimensional reconstruction functions, and outputs a three-dimensional craniofacial model A of the patient;

[0054] A bone defect area acquisition module for obtaining 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;

[0055] A 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 testing, 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;

[0056] A 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 obtained by the formula The bone reconstruction usability coefficient Ks is obtained by joint analysis;

[0057] 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 thus is 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 thus is judged to be unavailable.

[0058] Further, the bone defect area acquisition module includes a defect area preliminary acquisition unit and a region adjustment unit.

[0059] The defect area preliminary acquisition unit: uses the mirror symmetry of the patient's craniofacial surface, takes the undamaged side as a reference, and reverses 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 surface into several functional regions according to anatomical structures and functional requirements, and locates the functional region where the bone defect is located. Based on the function corresponding to the functional region, the function index of the bone defect to the craniofacial function is used as a constraint to adjust the shape, size and connection relationship of the surrounding bone structure of the first predicted bone defect three-dimensional image, so as to ensure that the reconstructed bone structure meets the functional requirements, and output a bone defect area image B.

[0060] In a possible embodiment, the first predicted bone defect three-dimensional image is obtained by: using a simulation 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 conditions, a simulation 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 to preliminarily predict the shape, size and position of the bone defect, and generate a corresponding three-dimensional image.

[0061] Further, 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 a surface smoothness index SI of the bone defect area image B. The simulation test analysis unit is configured to obtain a simulation bone quality evaluation index FQI. The simulation bone quality analysis unit is configured to obtain a simulation bone quality evaluation index FQI of the to-be-implanted simulation bone.

[0062] The simulation test analysis unit includes the following contents:

[0063] The craniofacial digital twin model is built.

[0064] Based on the actual movement and functional requirements of the craniofacial region, simulation parameters such as chewing force, respiratory airflow, and craniofacial muscle movement are set.

[0065] Input the simulation parameters into the craniofacial digital twin model and start the simulation test;

[0066] Observe the performance of the craniofacial region in simulation tests and record the quantitative parameters of functional indicators in the bone defect repair area;

[0067] The quantitative parameters of the combined functional indicators are analyzed to output a simulated bone quality assessment index;

[0068] The functional simulation quality index is used to predict whether the functional recovery after bone defect repair meets expectations.

[0069] In this embodiment of the invention, it is necessary to further explain that the acquisition method of the first predicted three-dimensional image of bone defect is as follows: loading the patient's two-dimensional craniofacial image data from the storage medium; selecting the healthy side of the patient's craniofacial region as a reference to create 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 location of the bone defect, and generating the first predicted three-dimensional image of bone defect; the acquisition method of the bone defect area image B is as follows: based on the anatomical structure of the craniofacial region, such as the frontal bone, parietal bone, temporal bone, maxilla, and mandible. The craniofacial region is divided into different functional areas, such as bones. The importance of each functional area to functional indicators, such as mastication, breathing, and vision, is assessed. Based on the needs of the functional areas, the morphology and size of the first predicted 3D image of the bone defect are adjusted, including adjusting the shape of the defect to match the surrounding bone structure and increasing or decreasing the size of the defect area according to functional needs, and the bone defect area image B is output. Maxillofacial surgeons or medical experts in related fields are invited to review the adjusted 3D image of the bone defect to ensure that it meets the anatomical structure and functional requirements. The approved bone defect area image B is used for subsequent steps.

[0070] Furthermore, the surface smoothness index SI is obtained as follows:

[0071] Let the set of points 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 each point (x q y q , z q Gaussian curvature K q ; through formula The surface smoothness index SI was calculated. This represents the average Gaussian curvature of all points.

[0072] Further, the function simulation quality index acquisition process comprises the following steps:

[0073] Step S11, data collection and preprocessing: collect the function indicators of the reconstructed craniofacial three-dimensional model, and set m function indicators, use i and j to represent the sequential number of the function indicators, i, j ∈ m, and i ≠ j; the normalization method used is linear normalization, which is used to scale each function indicator to between 0 and 1, and the quantization parameter of the i th function indicator is denoted as x i, and the quantization parameter of the j th function indicator is denoted as x j ;

[0074] Step S12, use the Pearson correlation coefficient to calculate the correlation between each function indicator, and denote the correlation coefficient of function indicator i and function indicator j as r ij ;

[0075] Step S13, set the base weight of the i th function 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 function indicator i ;

[0076] Step S14, weighted summation, calculate the function 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.

[0077] Further, the correlation coefficient is obtained in the following manner:

[0078] Perform n simulation tests, use k to represent the sequential number of the simulation test, record the quantization parameter of each function indicator, and normalize the quantization parameter; calculate the correlation coefficient r ij of function indicator i and function indicator j through the formula ; wherein x ij and x i (k) and x j (k) are the normalized values of function indicator i and function indicator j in the k th sample, respectively, and x i_ and x j_ are the normalized mean values of function indicator i and function indicator j, respectively.

[0079] Further, the simulation bone quality evaluation index FQI is obtained in the following manner:

[0080] 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 ; the design similarity is a value between 0 (completely dissimilar) and 1 (completely identical);

[0081] analyze the porosity connectivity of the simulated bone to be implanted, and output a porosity connectivity parameter kx; the porosity connectivity is obtained based on the complexity of the porosity network and the number of connected paths, and the porosity connectivity is a value between 0 (completely disconnected) and 1 (completely connected);

[0082] analyze the simulated bone material to be implanted, and output a mechanical stability parameter lw; the mechanical stability parameter represents the stability of the simulated bone material to be implanted when subjected to mechanical load, and 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);

[0083] input the design similarity, the porosity connectivity parameter and the mechanical stability parameter into the simulated bone quality evaluation model, and output a simulated bone quality evaluation index; the simulated bone quality 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.

[0084] Further, 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 the simulated bone to be implanted 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, and the simulated bone to be implanted is output.

[0085] Further, 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 the simulated bone to be implanted 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, and the simulated bone to be implanted is output.

[0086] Example 2

[0087] The embodiment of the present application provides a building process of building a craniofacial digital twin model, including the following steps:

[0088] Data acquisition: use 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; combine motion capture technology or real-time imaging technology to collect dynamic data of the craniofacial region;

[0089] Three-dimensional modeling: Use medical image processing software to process the collected data, extract the structures such as bones and soft tissues of the craniofacial region; use three-dimensional modeling software to construct a three-dimensional model of the craniofacial region based on the extracted data, and ensure the accuracy and details of the model during modeling to reflect the real anatomical structure;

[0090] Digital twin platform construction: Import the three-dimensional model of the craniofacial region into the simulation software to obtain the digital twin model of the craniofacial region; set physical properties (such as density, elastic modulus, etc.) and boundary conditions (such as constraints, loads, etc.);

[0091] Simulation and verification: Perform simulation calculations to simulate various functional activities of the craniofacial region (such as mastication, mouth opening, etc. craniofacial muscle movement), predict the response and changes of the digital twin model of the craniofacial region, and verify the accuracy and reliability of the digital twin model of the craniofacial region by comparing with real data; output the verified digital twin model of the craniofacial region.

[0092] In the embodiments of the present application, it needs to be further explained that setting simulation parameters includes: setting reasonable mastication force size and direction according to the patient's age, gender, mastication habit, combined with biomechanical principles; considering the airway structure of the nasal cavity and oral cavity, setting parameters such as airflow velocity and flow during breathing to simulate respiratory function; setting muscle contraction force, movement range, speed parameters according to the anatomical structure and functional characteristics of the muscle to simulate the dynamic movement of the craniofacial region.

[0093] In the embodiments of the present application, it needs to be further explained that for functional indicators such as mastication efficiency, respiratory patency, craniofacial movement coordination and visual abnormality, a quantitative evaluation method of functional indicators is designed, and the present application does not make a unique limitation on the quantitative evaluation method of functional indicators; for example, the mastication efficiency is evaluated by calculating the food crushing rate during mastication; the respiratory patency is evaluated by simulating the airway resistance during breathing; the craniofacial movement coordination is evaluated by measuring the joint movement trajectory and muscle contraction coordination; the visual abnormality is evaluated by simulating the changes of the visual system.

[0094] In the embodiments of the present application, it needs to be further explained that the similarity (such as error percentage) between the digital twin model of the craniofacial region and the real anatomical structure, and the accuracy influence coefficient of the simulation results and experimental data are analyzed; a linear normalization formula is used to convert the quantitative parameters to a value between 0 and 1, where 0 represents the worst (such as completely inconsistent), and 1 represents the best (such as completely consistent).

[0095] Summary: Digital twin models can receive real-time data from the physical world and perform corresponding analysis and prediction; in the craniofacial test, the changes of the craniofacial are observed and analyzed in real time, and adjusted and optimized as needed; through the digital twin model, the craniofacial test can reduce the risk and cost.

[0096] Finally: The above is only the preferred embodiment of the present application and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A digital simulation-based craniofacial prosthesis system, characterized by, The application relates to a skull-jaw-face bone defect reconstruction method and device. The data acquisition module performs CT and MRI scanning on a patient to obtain two-dimensional skull-jaw-face image data of the patient; The three-dimensional reconstruction module is used for converting the two-dimensional skull-jaw-face image data into a three-dimensional model and outputting a skull-jaw-face three-dimensional model A of the patient; The bone defect area acquisition module is used for acquiring 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; the bone defect area image B is placed in the skull-jaw-face three-dimensional model A to obtain a reconstructed skull-jaw-face three-dimensional model, the function index of the reconstructed skull-jaw-face three-dimensional model is predicted through simulation test, 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 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 for acquiring the surface smoothness index SI of the bone defect area image B, the simulation test analysis unit is used for acquiring the simulation bone quality evaluation index FQI, and the simulation bone quality analysis unit is used for acquiring the simulation bone quality evaluation index FQI of the to-be-implanted simulation bone. The simulation test analysis unit comprises the following contents: A skull-jaw-face digital twin model is built; simulation simulation parameters are set according to the actual movement and function demand of the skull-jaw-face; the simulation simulation parameters are input into the skull-jaw-face digital twin model, and simulation test is started; The performance of the skull-jaw-face in the simulation test is observed, and the quantitative parameters of the function index of the bone defect repair area are recorded; The quantitative parameters of the function index are jointly analyzed, the simulation bone quality evaluation index is output, and whether the function recovery after the bone defect repair meets the expectation is predicted based on the function simulation quality index. The function simulation quality index acquisition process comprises the following steps: The function index of the reconstructed skull-jaw-face three-dimensional model is collected, and m function indexes are set, wherein i and j represent the sequential numbers of the function indexes, i, j [m], and i [j. The normalization method used is linear normalization, which scales each functional indicator to between 0 and 1. The quantization parameter of the i-th functional indicator is denoted as x. i The quantitative parameter of the j-th functional indicator is denoted as x. j The Pearson correlation coefficient is used to calculate the correlation between the functional indicators. The correlation coefficient between functional indicator i and functional indicator j is denoted as r. ij ;set up The base weight of the i-th function index is w 0i , the base weight is adjusted using the correlation coefficient, according to the formula The weight w i of the i-th function index is output; the function simulation quality index Gz is calculated by 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; The availability evaluation module jointly analyzes the surface smoothness index, the function simulation quality index and the simulation bone mass evaluation index, and outputs a bone reconstruction availability coefficient Ks; the bone reconstruction availability coefficient Ks is obtained through a formula The bone reconstruction availability coefficient Ks is obtained through joint analysis. The availability judgment module is used for judging the relationship between the bone reconstruction availability coefficient and the corresponding threshold Tza; if the bone reconstruction availability coefficient exceeds the threshold Tza, 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.

2. The digital simulation-based 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 preliminarily predicts the shape and size of the bone defect area by mirror flipping with the undamaged side as the reference based on the mirror symmetry of the skull-jaw-face of the patient, and outputs a first predicted bone defect three-dimensional image; The region adjustment unit divides the skull-jaw-face into a plurality of functional regions according to the anatomical structure and function demand, positions 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 function of the functional region, ensures that the reconstructed bone structure meets the function demand, and outputs the bone defect area image B.

3. The digitally simulated craniofacial repair system of claim 1, wherein, The surface smoothness index SI is obtained in the following manner: Let the set of points on the surface of the bone defect region image B be where q = 1, 2, …, P, where P represents the total number of points; The Gaussian curvature K of each point is calculated q The surface smoothness index SI is calculated by the formula representing the average of the Gaussian curvature of all points.​ 4. The digitally simulated craniofacial repair system of claim 3, wherein, The correlation coefficient is obtained in the following manner: Perform n simulation tests, denoted by k, to represent the sequential number of the simulation tests. Record the quantification parameters of each functional indicator and normalize the quantification parameters. Then, use the formula... The correlation coefficient r between functional index i and functional index j was calculated. ij ; where x i (k) and x j (k) These are the normalized values ​​of functional index i and functional index j in the k-th sample, respectively, x i_ and x j_ These are the normalized means of functional indicators i and j, respectively.

5. The digitally simulated craniofacial repair system of claim 1, wherein, The simulation bone quality evaluation index FQI is obtained in the following manner: A three-dimensional image of the simulation bone to be implanted is scanned, and a design similarity of the three-dimensional image of the simulation bone and the bone defect region image B is calculated, denoted as xs; The pore connectivity of the simulation bone to be implanted is analyzed, and a pore connectivity parameter kx is outputted; The material of the simulation bone to be implanted is analyzed, and a mechanical stability parameter lw is outputted; 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, and c represent the influence indexes of each term respectively, and a, b, and c are adjusted according to specific application scenarios and requirements to reflect the importance of different parameters in evaluation.

6. 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 region image B is combined with the 3D printing software to design the simulation bone to be implanted which fits the shape of the bone defect of the patient, and 3D printing is performed; otherwise, the bone defect region image B is regenerated; the bone defect region image B is combined with the 3D printing software to design the bone implant model which fits the shape of the bone defect of the patient, and 3D printing is performed, and the simulation bone to be implanted is outputted.

7. The digitally simulated craniofacial repair system of claim 1, wherein, When the surface smoothness index and the functional simulation quality index meet the preset requirements at the same time, the bone defect region image B is combined with the 3D printing software to design the simulation bone to be implanted which fits the shape of the bone defect of the patient, and 3D printing is performed; Otherwise, the bone defect region image B is regenerated; the bone defect region image B is combined with the 3D printing software to design the bone implant model which fits the shape of the bone defect of the patient, and 3D printing is performed, and the simulation bone to be implanted is outputted; according to the clinical requirements and the patient's condition, a 3D printing ceramic material is selected.

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