Breast reconstruction preoperative auxiliary decision-making system and method based on three-dimensional scanning imaging

Abstract

The invention discloses a breast reconstruction preoperative auxiliary decision-making system and method based on three-dimensional scanning imaging, and the system comprises a collection and preparation module which is used for collecting and obtaining the target breast reconstruction data of a patient; the model building module is used for building a three-dimensional breast model based on the acquired imaging data of the breasts on the two sides; the difference calculation module is used for calculating the capacity difference of the breast models on the two sides to obtain a capacity difference value of the breast on the affected side relative to the breast on the healthy side; the index evaluation module is used for determining an expected three-dimensional breast model, taking the expected three-dimensional breast model as a model corresponding to the postoperative affected side breast, and performing evaluation of different dimensions according to the expected three-dimensional breast model and the original three-dimensional breast model corresponding to the healthy / affected side breast; and the decision optimization module is used for generating a preoperative evaluation scale corresponding to decision matching and updating and outputting an optimal target breast reconstruction scheme, so that the effectiveness of the preoperative auxiliary decision for breast reconstruction is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical equipment, and in particular to a preoperative decision-making auxiliary system and method for breast reconstruction based on three-dimensional scanning imaging. Background Art

[0002] With the development of medical technology, personalized medicine has received more and more attention. Under the premise of ensuring the safety of breast tumors, combining the concepts and methods of plastic surgery to perform breast reconstruction and beauty on patients has become a new trend and new direction in the development of breast surgery. Breast reconstruction refers to the restoration of normal breast appearance through autologous tissue transplantation or combined with artificial materials. Breast reconstruction technology not only focuses on the restoration of appearance, but also pays more attention to the improvement of the patient's overall rehabilitation quality and quality of life. Based on the latest expert consensus on breast tumor plastic surgery and breast reconstruction (2022 edition) published by the Breast Cancer Professional Committee of the Chinese Anti-Cancer Association and the Chinese expert consensus on accelerated recovery surgery for breast reconstruction (2022 edition), the surgical methods for breast reconstruction patients after breast cancer surgery were explored. At present, some researchers have conducted relevant research on patient decision-making assistance, but it is limited to text or oral. At present, most clinical surgical methods are based on the doctor's experience decision during the consultation or the patient's selection based on online information, which is easy to cause regret in the decision. There is no way to combine big data for comprehensive consideration. Decision plans are output through digital calculations, and there is a lack of personalized and precise plan assistance. Patients often lack intuitive effects and compliance with plans under multiple considerations during the decision-making process. Patients are not given an intuitive decision plan display, and the user experience is poor. Summary of the invention

[0003] The purpose of the present invention is to provide a preoperative decision-making support system for breast reconstruction based on three-dimensional scanning imaging, so as to improve the effectiveness of preoperative decision-making support for breast reconstruction and enhance user experience.

[0004] The present invention provides a preoperative decision-making auxiliary system for breast reconstruction based on three-dimensional scanning imaging, comprising:

[0005] An acquisition planning module is used to acquire and obtain target breast reconstruction data of the patient, wherein the target breast reconstruction data at least includes the electronic medical record EMR data corresponding to the hospitalization number or name of each patient and the imaging data of both breasts acquired through three-dimensional scanning;

[0006] A model building module is used to create a three-dimensional breast model including a healthy breast and an affected breast based on the collected imaging data of the bilateral breasts, and to display the 3D virtual effect of breast reconstruction presented by the three-dimensional breast model before and after the operation according to the target breast reconstruction data interface corresponding to each patient, and to display prompt information related to the target breast reconstruction of each patient before and after the operation on the interface;

[0007] A difference calculation module is used to obtain the external contour of the patient's breast based on three-dimensional scanning imaging, and calculate the volume difference of the breast models on both sides before surgery to obtain the volume difference between the affected breast and the healthy breast, and select and determine the volume of the target reconstructed breast and the surgical reference plan based on the volume difference;

[0008] An index evaluation module is used to determine an expected three-dimensional breast model according to the volume of the target reconstructed breast, use the expected three-dimensional breast model as the model corresponding to the affected breast after surgery, and perform evaluations of different dimensions based on the expected three-dimensional breast model and the original three-dimensional breast models corresponding to the healthy / affected breasts, wherein the different dimensions at least include symmetry and postoperative effect prediction evaluation;

[0009] The decision optimization module is used to comprehensively judge whether the expected three-dimensional breast model matches the preset decision model based on the evaluation results of different dimensions, generate a preoperative evaluation scale corresponding to the decision matching, and update and output the optimal target reconstructed breast volume and surgical reference plan.

[0010] Preferably, the acquisition planning module includes:

[0011] An electronic medical record query unit, used to log in to the medical record homepage to query the electronic medical record EMR data, the electronic medical record EMR data including the patient's age, BMW constitution, past medical history, family history, smoking history and estimated costs;

[0012] The laboratory query unit is used to connect to the laboratory management system LIS through the laboratory system interface to obtain the inspection report of the target object, wherein the inspection report includes cardiopulmonary function information, coagulation value and BMI index;

[0013] The medical image query unit is used to connect to the medical image system DICOM through the Web API, establish a connection between the current electronic medical record page and the medical image system, obtain chest and abdominal CT, and measure the blood vessel diameter and blood volume flow of the target object;

[0014] The data aggregation unit is used to aggregate the electronic medical record EMR data, examination and test reports, and chest and abdominal CT data to obtain the target breast reconstruction data of the current patient.

[0015] Preferably, the model building module includes:

[0016] A parameter definition unit, used for extracting breast characteristic parameters through medical images and performing parameter definition, wherein the breast characteristics include the length of R line, H line, L line, Q line, and II line, and nipple diameter;

[0017] A software selection unit, used for selecting mathematical modeling software according to breast characteristic parameters to perform three-dimensional modeling and data analysis, and generate a target breast model corresponding to both breasts;

[0018] A basic shape creation unit, used for taking a basic model of a breast according to a basic geometric shape of a mathematical modeling software, and adjusting a size and a proportion of the model according to an R line, an H line, and an L line;

[0019] An adjustment unit, used to adjust the inclination angle of the model according to the Q line, adjust the circumference of the model according to the Π line to ensure that the circumference of the target breast model is consistent with that of the actual breast, and adjust the position and diameter of the nipple to make the target breast model match the size and position of the actual nipple;

[0020] A verification and optimization unit is used to compare the established target breast model with the actual breast image or data to check the accuracy of the model, perform iterative optimization according to requirements, and adjust the parameters of the target breast model to better match the actual data;

[0021] The basic geometric shapes include a sphere and an ellipsoid, the R line represents the distance from the breast base to the nipple, the H line represents the vertical height of the breast, the L line represents the lateral length of the breast base, the Q line represents the inclination of the breast, and the Π line represents the circumference of the breast.

[0022] Preferably, the difference calculation module includes:

[0023] A voxelization unit, used for acquiring three-dimensional image data in the target breast reconstruction data, and converting the three-dimensional image data into a voxel grid after preprocessing;

[0024] A segmentation and labeling unit, used for distinguishing the target breast tissue from the background and non-breast tissue by using an image segmentation technology, and labeling the voxels of the target breast tissue;

[0025] A volume calculation unit is used to calculate the number of all voxels marked as target breast tissues and multiply the volume of a single voxel, and to add up the volumes of all voxels corresponding to a single breast to obtain the total volume of the corresponding single breast;

[0026] In three-dimensional space, the volume is obtained by calculating the sum of all voxels, and the calculation formula is as follows:

[0027]

[0028] Where V is the volume, vi is the volume of the i-th voxel, and n is the total number of voxels.

[0029] Preferably, the difference calculation module further includes:

[0030] A mirror image overlapping unit is used to mirror the three-dimensional model of the healthy breast and overlap the three-dimensional breast model of the healthy breast with the three-dimensional breast model of the affected breast;

[0031] A volume difference calculation unit is used to calculate the volume difference between the two sides of the three-dimensional breast model, that is, the volume difference, and output the breast volume difference predicted by PABVD;

[0032] The target breast reconstruction unit is used to select the closest reconstructed breast site volume PPV according to the calculated PABVD to determine the surgical reference plan and volume of the target breast reconstruction.

[0033] Preferably, the indicator evaluation module includes:

[0034] A symmetry evaluation unit is used to compare the expected three-dimensional breast model with the original three-dimensional breast model corresponding to the healthy side breast to evaluate the symmetry of the two;

[0035] The effect evaluation unit is used to compare the expected three-dimensional breast model with the original three-dimensional breast model corresponding to the affected breast to predict and evaluate the effect of the current model.

[0036] Preferably, the preset decision model extracts the influencing factors related to the current patient health index and the estimated cost influencing factors of each patient in the target breast reconstruction data, and comprehensively inputs all the influencing factors into the neural network to predict different target breast reconstructions to match the current patient health status and economic ability, and obtains the initial reference surgical plan for the target breast reconstruction.

[0037] The present invention also provides a method for assisting decision-making before breast reconstruction surgery based on three-dimensional scanning imaging, which is applicable to the system for assisting decision-making before breast reconstruction surgery based on three-dimensional scanning imaging as described in an embodiment of the present invention, comprising:

[0038] Collecting and obtaining target breast reconstruction data of the patient, wherein the target breast reconstruction data at least includes the electronic medical record (EMR) data corresponding to the hospitalization number or name of each patient and the imaging data of both breasts obtained by three-dimensional scanning;

[0039] Based on the collected imaging data of the bilateral breasts, a three-dimensional breast model including the healthy breast and the affected breast is created, and the 3D virtual effect of breast reconstruction presented by the three-dimensional breast model before and after the operation is displayed according to the target breast reconstruction data interface corresponding to each patient, and prompt information related to the target breast reconstruction of each patient before and after the operation is displayed on the interface;

[0040] The external contour of the patient's breast is obtained based on three-dimensional scanning imaging, and the volume difference of the breast models on both sides is calculated before surgery to obtain the volume difference between the affected breast and the healthy breast, and the volume of the target reconstructed breast and the surgical reference plan are selected and determined based on the volume difference;

[0041] Determine an expected three-dimensional breast model according to the volume of the target reconstructed breast, use the expected three-dimensional breast model as the model corresponding to the affected breast after surgery, and perform evaluations of different dimensions based on the expected three-dimensional breast model and the three-dimensional breast models corresponding to the original healthy / affected breasts, wherein the different dimensions at least include symmetry and postoperative effect prediction evaluation;

[0042] Based on the evaluation results of different dimensions, a comprehensive judgment is made as to whether the expected three-dimensional breast model matches the preset decision model, a preoperative evaluation scale corresponding to the decision matching is generated, and the optimal target reconstructed breast volume and surgical reference plan are updated and output.

[0043] The present invention also provides an electronic device, comprising:

[0044] A memory, the memory being used to store a processing program;

[0045] A processor, wherein when executing the processing program, the processor implements the preoperative auxiliary decision method for breast reconstruction based on three-dimensional scanning imaging as described in an embodiment of the present invention.

[0046] The present invention also provides a computer-readable medium storing a computer program, characterized in that when the computer program is executed by one or more processors, it implements the preoperative decision-making assistance method for breast reconstruction based on three-dimensional scanning imaging as described in an embodiment of the present invention.

[0047] With respect to the prior art, the present invention has the following beneficial effects:

[0048] The present invention proposes a preoperative evaluation system for breast reconstruction based on 3D scanning imaging. By collecting the patient's electronic medical records, laboratory test data and 3D scanning image data, the system can fully understand the patient's health status and breast morphology, which is helpful to establish a more accurate model and formulate a more appropriate surgical plan; using the collected imaging data, a 3D model including the healthy breast and the affected breast is created, which can intuitively display the breast morphology before and after the operation, helping doctors and patients to better understand the effect of the operation; by calculating the volume difference of the breast models on both sides, the system can accurately determine the volume difference of the affected breast relative to the healthy breast, which is helpful to select the appropriate breast reconstruction surgery method and target breast volume. Ensure the symmetry and effect of the breast after surgery; determine the expected three-dimensional breast model based on the volume of the target reconstructed breast, and compare it with the original breast model for symmetry and postoperative effect prediction and evaluation, which helps predict the results of the surgery and discover possible problems in advance; combined with the patient's health index and estimated cost influencing factors, the system can generate a preoperative evaluation scale corresponding to the decision matching, and update and output the optimal target breast reconstruction surgery plan and target breast volume, which helps to control the cost of surgery while meeting the needs of patients; through neural network analysis of all influencing factors, predict the matching degree of different target breasts with the current patient's health status and economic ability, which helps to provide personalized surgical recommendations for each patient. The specific advantages are as follows:

[0049] 1. Improve surgical accuracy and effect prediction: By integrating big data and digital computing, the system can provide each patient with a personalized surgical plan based on their unique health status and expected results, reducing the deviation caused by reliance on doctor's experience or patient's non-professional information search, and improving the scientificity and accuracy of decision-making.

[0050] 2. Personalized decision support: The system generates a preoperative assessment scale corresponding to the decision matching based on the patient's health index and estimated cost influencing factors, and provides the optimal target breast reconstruction recommendation. This personalized decision support can help doctors and patients choose the most suitable surgical plan, taking into account both health and economic factors.

[0051] 3. Comprehensive preoperative evaluation: The acquisition module integrates electronic medical records, laboratory test data and medical imaging data to provide doctors with a comprehensive patient health profile. Based on this data, the model building module can create an accurate three-dimensional breast model to further analyze symmetry and postoperative effects.

[0052] 4. Optimize surgical planning and risk management: The indicator evaluation module not only considers symmetry, but also conducts postoperative effect prediction and evaluation to help doctors identify possible risks and complications in advance and take preventive measures. The decision optimization module combines neural network algorithms to provide doctors with a scientific basis to select the best reconstruction surgery plan and target breast volume. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a principle block diagram of a preoperative decision-making support system for breast reconstruction based on three-dimensional scanning imaging in one embodiment of the present invention;

[0054] Figure 2 This is an example diagram of a query process of a preoperative decision support system for breast reconstruction based on three-dimensional scanning imaging in one embodiment of the present invention;

[0055] Figure 3 The figure is a schematic diagram of the steps of a method for assisting decision-making before breast reconstruction surgery based on three-dimensional scanning imaging in one embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0058] It should be noted that the concepts such as "once" and "second" mentioned in the present application are only used to distinguish different systems, modules or units, and are not used to limit the order or interdependence of the functions performed by these systems, modules or units.

[0059] It should be noted that the modifications of "one" and "plurality" mentioned in the disclosure of this application are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0060] Embodiment 1

[0061] Under the premise of ensuring the safety of breast tumors, combining the concepts and methods of plastic surgery to perform breast reconstruction and beauty treatments on patients has become a new trend and direction in the development of breast surgery. Breast reconstruction refers to the restoration of normal breast appearance through autologous tissue transplantation or combined with artificial materials. Breast reconstruction technology not only focuses on the restoration of appearance, but also pays more attention to the improvement of the patient's overall recovery quality and quality of life.

[0062] The surgical methods of breast reconstruction are mostly decided by doctors' experience or selected by patients after browsing online information. There is a lack of personalized and accurate program assistance. Patients often lack intuitive effects and multiple considerations during decision-making, which easily leads to regretful decisions. The present invention also provides a preoperative decision-making assistance system for breast reconstruction based on three-dimensional scanning imaging. Figure 1 As shown, including:

[0063] An acquisition planning module is used to acquire and obtain target breast reconstruction data of the patient, wherein the target breast reconstruction data at least includes the electronic medical record EMR data corresponding to the hospitalization number or name of each patient and the imaging data of both breasts acquired through three-dimensional scanning;

[0064] A model building module is used to create a three-dimensional breast model including a healthy breast and an affected breast based on the collected imaging data of the bilateral breasts, and to display the 3D virtual effect of breast reconstruction presented by the three-dimensional breast model before and after the operation according to the target breast reconstruction data interface corresponding to each patient, and to display the prompt information related to the target breast reconstruction of each patient before and after the operation on the interface, such as preoperative patient education showing the 3D breast reconstruction model before and after the operation, and informing the patient of postoperative adjuvant treatment, rehabilitation care and complication risks;

[0065] A difference calculation module is used to obtain the external contour of the patient's breast based on three-dimensional scanning imaging, and calculate the volume difference of the breast models on both sides before surgery to obtain the volume difference between the affected breast and the healthy breast, and select and determine the volume of the target reconstructed breast and the surgical reference plan based on the volume difference;

[0066] An index evaluation module is used to determine the expected three-dimensional breast model according to the volume of the target reconstructed breast, use the expected three-dimensional breast model as the model corresponding to the affected breast after surgery, and perform evaluations in different dimensions based on the expected three-dimensional breast model and the three-dimensional breast models corresponding to the original healthy / affected breasts, wherein the different dimensions at least include symmetry and postoperative effect prediction evaluation, or evaluate the patient's economic status and psychological expectations, match the health index, economic expectations with the surgical plan, and produce a preoperative evaluation scale and recommend a surgical plan;

[0067] The decision optimization module is used to comprehensively judge whether the expected three-dimensional breast model matches the preset decision model according to the evaluation results of different dimensions, generate a preoperative evaluation scale corresponding to the decision matching, and update and output the optimal target breast reconstruction volume and surgical reference plan, wherein the preset decision model extracts the influencing factors related to the current patient health index and the estimated cost influencing factors of each patient in the target breast reconstruction data, and comprehensively inputs all influencing factors into the neural network to predict different target breast reconstructions to match the current patient health status and economic ability, and obtain the initial reference surgical plan for the target breast reconstruction, such as the display plan generated by configuring the reconstruction size or the autologous tissue size. The above module combines the patient's physical condition, economic situation, surgical needs, etc. for comprehensive consideration, hoping to provide information under big data, combine the patient's comprehensive literacy and needs, and provide patients with intuitive virtual imaging and options that meet the requirements through digital calculations, while informing patients of possible foreseen problems and preparations, helping patients to intuitively select effects and plans, and reducing their decision regrets.

[0068] like Figure 2 As shown, in one embodiment, the acquisition planning module includes:

[0069] An electronic medical record query unit, used to log in to the medical record homepage to query the electronic medical record EMR data, the electronic medical record EMR data including the patient's age, BMW constitution, past medical history, family history, smoking history and estimated costs;

[0070] The laboratory query unit is used to connect to the laboratory management system LIS through the laboratory system interface to obtain the inspection report of the target object, wherein the inspection report includes cardiopulmonary function information, coagulation value and BMI index;

[0071] The medical image query unit is used to connect to the medical image system DICOM through the Web API, establish a connection between the current electronic medical record page and the medical image system, obtain chest and abdominal CT, and measure the blood vessel diameter and blood volume flow of the target object;

[0072] The data aggregation unit is used to aggregate the electronic medical record EMR data, examination and test reports, and chest and abdominal CT data to obtain the target breast reconstruction data of the current patient. It can be understood that in this embodiment, the preoperative evaluation system for breast reconstruction is logged in, the hospital number / name is entered to query the patient, the electronic medical record is queried, the medical record homepage is obtained, the laboratory system is queried, the examination and test reports are obtained, the heart, coagulation, tumor type staging and treatment conditions are evaluated, the medical imaging system is queried through the web api to measure the blood vessel diameter and blood volume flow, the preoperative patient education is displayed before and after the operation. 3D models of breast reconstruction are displayed, and postoperative adjuvant therapy, rehabilitation care and complication risks are informed, the economic status and psychological expectations of the patient are evaluated, the health index, economic expectations and surgical plans are matched, and a preoperative evaluation scale and a recommended surgical plan are produced.

[0073] In one embodiment, the model building module includes:

[0074] A parameter definition unit, used for extracting breast characteristic parameters through medical images and performing parameter definition, wherein the breast characteristics include the lengths of R-line, H-line, L-line, Q-line, and II-line, and the nipple diameter, which can be obtained through medical images (such as MRI or CT scans) or through actual measurements;

[0075] A software selection unit is used to select mathematical modeling software for three-dimensional modeling and data analysis according to breast characteristic parameters to generate a target breast model corresponding to both breasts. The mathematical modeling software includes MATLAB, Mathematica, AutoCAD, SolidWorks, etc.;

[0076] A basic shape creation unit, used for taking a basic model of a breast according to a basic geometric shape of a mathematical modeling software, and adjusting a size and a proportion of the model according to an R line, an H line, and an L line;

[0077] An adjustment unit is used to adjust the tilt angle of the model according to the Q line, adjust the circumference of the model according to the Π line to ensure that the target breast model is consistent with the circumference of the actual breast, adjust the position and diameter of the nipple to make the target breast model match the size and position of the actual nipple, and can also add skin texture and color to make the model more realistic;

[0078] A verification and optimization unit is used to compare the established target breast model with the actual breast image or data to check the accuracy of the model, perform iterative optimization according to requirements, and adjust the parameters of the target breast model to better match the actual data;

[0079] The basic geometric shapes include a sphere and an ellipsoid, the R line represents the distance from the breast base to the nipple, the H line represents the vertical height of the breast, the L line represents the lateral length of the breast base, the Q line represents the inclination of the breast, and the Π line represents the circumference of the breast.

[0080] The MATLAB code example is as follows:

[0081] Creating a simple 3D breast model

[0082] Parameter Definition

[0083] R=10;%R line length

[0084] H=12;%H line length

[0085] L=15;%L line length

[0086] Q=5;%Q line length

[0087] Pi_line=35;%PI line length

[0088] nipple_diameter=1;%nipple diameter

[0089] Create the basic shape of the breast model (here an ellipsoid is used as an example)

[0090] [X,Y,Z]=ellipsoid(50,50,50,[L / 2,H / 2,R / 2],'center');

[0091] Display Model

[0092] figure;

[0093] surf(X,Y,Z);

[0094] axis equal;

[0095] xlabel('X');ylabel('Y');zlabel('Z');

[0096] title('3D breast model');

[0097] Add the nipple (simplified as a small sphere)

[0098] nipple_radius=nipple_diameter / 2;

[0099] [theta,phi]=meshgrid(linspace(0,2*pi,50),linspace(0,pi,50));

[0100] r = nipple_radius*sin(phi);

[0101] [Xnipple,Ynipple,Znipple]=sph2cart(theta,phi,r);

[0102] hold on;

[0103] surf(Xnipple,Ynipple,Znipple,'r');

[0104] hold off; This code example is only used to illustrate how to create a basic 3D model in MATLAB. In actual applications, more detailed adjustments and optimizations are required based on specific data and requirements.

[0105] In one embodiment, the specific process of the difference calculation module used in this embodiment is as follows:

[0106] The difference calculation module includes:

[0107] The voxelization unit is used to obtain the three-dimensional image data in the target breast reconstruction data, and convert the three-dimensional image data into a voxel grid after preprocessing; it can be understood that, in this embodiment, first, a three-dimensional scanner is used to scan the patient's bilateral breasts to obtain their accurate three-dimensional data. The scanned data is imported into a dedicated computer software, such as Materialise's Mimics or other medical image processing software. The acquired three-dimensional image data is preprocessed as necessary, including denoising, contrast enhancement, segmentation, etc., to ensure the accuracy of subsequent volume calculations. The continuous three-dimensional image data is converted into a voxel grid. Each voxel represents a tiny cubic space, the size of which is determined by the scanning resolution.

[0108] A segmentation and labeling unit, which is used to distinguish the target breast tissue from the background and non-breast tissue by image segmentation technology, and to label the voxels of the target breast tissue, so that in the software, the image is optimized by tools such as threshold segmentation and region growing to ensure that the breast tissue is accurately segmented and identified, using image segmentation techniques such as threshold processing, region growing or deep learning algorithms;

[0109] The volume calculation unit is used to calculate the number of voxels marked as target breast tissue and multiply it by the volume of a single voxel. The volumes of all voxels corresponding to one breast are added together to obtain the total volume of the corresponding breast. The volume of a single voxel is the product of its physical size in three-dimensional space, which is usually determined by the resolution of the scanning device. Using software tools, the volume of each breast is calculated based on the processed three-dimensional model. This is usually achieved by calculating the total number of pixels or voxels (three-dimensional pixels) and multiplying it by the volume of a single pixel;

[0110] In three-dimensional space, the volume is obtained by calculating the sum of all voxels, and the calculation formula is as follows:

[0111]

[0112] Where V is the volume, vi is the volume of the i-th voxel, and n is the total number of voxels.

[0113] Here is an example: suppose we have a 3D scan dataset where each voxel has a side length of 1 mm (i.e., a volume of 1 cubic millimeter). Through image segmentation, we determine that the total number of voxels in breast tissue is 2,500,000. The formula for calculating volume is: V = N × Vvoxel, where V is the volume, N is the number of voxels, and Vvoxel is the volume of a single voxel. In this example, the volume of each voxel is 1 mm 3 , so the total volume V is: V = 2,500,000 × 1mm 3 =2,500,000mm 3 .

[0114] Since 1cm 3 =1,000mm 3 , the volume can be converted to cubic centimeters: V = 2,500,000 mm 3 ÷1,000=2,500cm 3 , therefore, the volume of the breast is 2,500 cubic centimeters. This process can be automated in various 3D image processing software, such as MATLAB, Python (using libraries such as SimpleITK or nibabel), or professional medical imaging software such as Mimics.

[0115] Furthermore, the difference calculation module further includes: a mirror overlapping unit, which is used for: in order to evaluate symmetry, the software can mirror the three-dimensional model of the healthy breast and overlap the three-dimensional breast model of the healthy breast with the three-dimensional breast model of the affected breast;

[0116] A volume difference calculation unit is used to calculate the volume difference between the two sides of the three-dimensional breast model, that is, the volume difference, and output the breast volume difference predicted by PABVD;

[0117] Determine the target breast reconstruction unit, which is used to select the closest reconstruction volume PPV based on the calculated PABVD to determine the reference plan for breast reconstruction surgery and the target breast volume. The reference plan for breast reconstruction surgery can use autologous tissue transplantation or combined with artificial materials.

[0118] An example is as follows: Assume that after 3D scanning and software processing, the following data is calculated: healthy breast volume: 300ml, affected breast volume: 280ml, calculated volume difference (PABVD): 300ml-280ml=20ml, 300ml-280ml=20ml. Based on this result, a reconstructive prosthesis with a volume of 20ml is selected to supplement the missing part of the affected breast, thereby restoring the symmetry of the bilateral breasts as much as possible. Through the above modules or steps, the breast volume difference can be accurately calculated, and the surgical planning can be carried out accordingly to achieve the best postoperative effect.

[0119] For example, the reference scheme for breast reconstruction surgery adopted in this embodiment is as follows: 1. Implants: 1) expander implantation + prosthesis implantation; 2) prosthesis implantation; 3) autologous tissue (in the selection of autologous flap donor sites, the principles of blood supply priority, economy and donor site conservation should be followed. The patient's body shape, breast morphology and donor site conditions are three important considerations): Autologous flap breast reconstruction technology mainly adopts three types of autologous tissue flap technologies: ① Pedicled tissue flap technology. The traditional pedicled flap technology is mainly based on the latissimus dorsi flap (LDF), single-pedicle or double-pedicle TRAM technology. ② Free tissue flap technology, including free deep inferior epigastric perforator (DIEP), superficial inferior epigastric artery flap (SIEA), free transverse rectus abdominis musculocutaneous flaps (TRAM), superior gluteal artery perforator flap (SGAP) and profunda artery perforator flap (PAP), etc. ③ Autologous tissue flap transplantation combined with prosthesis implantation technology, mainly latissimus dorsi muscle (skin) flap combined with reconstruction implantation technology.

[0120] In one embodiment, the indicator evaluation module includes:

[0121] A symmetry evaluation unit is used to compare the expected three-dimensional breast model with the original three-dimensional breast model corresponding to the healthy side breast to evaluate the symmetry of the two;

[0122] The effect evaluation unit is used to compare the expected three-dimensional breast model with the original three-dimensional breast model corresponding to the affected breast to predict and evaluate the effect of the current model.

[0123] Embodiment 2

[0124] Based on the same inventive concept, the present invention provides a preoperative decision-making assistance method for breast reconstruction based on three-dimensional scanning imaging, which is applicable to the preoperative decision-making assistance system for breast reconstruction based on three-dimensional scanning imaging described in Example 1. Figure 3 As shown, including:

[0125] S1: Collecting and obtaining target breast reconstruction data of the patient, wherein the target breast reconstruction data at least includes the electronic medical record EMR data corresponding to the hospitalization number or name of each patient and the imaging data of both breasts obtained by three-dimensional scanning;

[0126] S2: Based on the collected imaging data of the bilateral breasts, a three-dimensional breast model including the healthy breast and the affected breast is created, and the 3D virtual effect of breast reconstruction presented by the three-dimensional breast model before and after the operation is displayed according to the target breast reconstruction data interface corresponding to each patient, and prompt information related to the target breast reconstruction of each patient before and after the operation is displayed on the interface;

[0127] S3: Based on three-dimensional scanning imaging, the external contour of the patient's breast is obtained, and the volume difference of the breast models on both sides is calculated before the operation to obtain the volume difference between the affected breast and the healthy breast, and the volume and surgical procedure of the target reconstructed breast, i.e., the reference plan for breast reconstruction surgery, is selected and determined according to the volume difference;

[0128] S4: determining an expected three-dimensional breast model according to the volume of the target reconstructed breast, using the expected three-dimensional breast model as a model corresponding to the affected breast after surgery, and performing evaluations of different dimensions based on the expected three-dimensional breast model and the original three-dimensional breast models corresponding to the healthy / affected breasts, wherein the different dimensions at least include symmetry and postoperative effect prediction evaluation;

[0129] S5: Based on the evaluation results of different dimensions, comprehensively judge whether the expected three-dimensional breast model matches the preset decision model, generate a preoperative evaluation scale corresponding to the decision matching, and update and output the optimal target reconstructed breast volume and breast reconstruction surgery plan.

[0130] It should be noted that the division of the modules in this system / system embodiment is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. And these modules can all be implemented in the form of software calling through processing elements; they can also be all implemented in the form of hardware; some units can also be implemented in the form of processing elements calling software, and some units can be implemented in the form of hardware. The above steps are based on the system implementation provided in the previous embodiments, so they will not be repeated here.

[0131] Embodiment 3

[0132] Based on the same inventive concept, in some embodiments of the present application, an electronic device is also provided. The electronic device includes a memory and a processor, wherein the memory is used to store a processing program, and the processor executes the processing program according to instructions. When the processor executes the processing program, the preoperative decision-making auxiliary method for breast reconstruction based on three-dimensional scanning imaging in the aforementioned embodiment is implemented.

[0133] In some embodiments of the present application, a readable storage medium is also provided, which may be a non-volatile readable storage medium or a volatile readable storage medium. The readable storage medium stores instructions, and when the instructions are executed on a computer, an electronic device including the readable storage medium executes the aforementioned preoperative decision-making assistance method for breast reconstruction based on three-dimensional scanning imaging.

[0134] It is understandable that, for the aforementioned breast reconstruction preoperative decision-making assistance method based on three-dimensional scanning imaging, if it is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0135] Computer readable storage media may include data signals propagated in baseband or as part of a carrier wave, wherein readable program codes are carried. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, system, or device. The program codes contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0136] The program code involved in executing the technical solution disclosed in this application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Python, C++, etc., and also conventional procedural programming languages ​​such as C language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0137] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A preoperative decision-making support system for breast reconstruction based on three-dimensional scanning imaging, characterized in that: include: An acquisition planning module is used to acquire and obtain target breast reconstruction data of the patient, wherein the target breast reconstruction data at least includes the electronic medical record EMR data corresponding to the hospitalization number or name of each patient and the imaging data of both breasts acquired through three-dimensional scanning; A model building module is used to create a three-dimensional breast model including a healthy breast and an affected breast based on the collected imaging data of the bilateral breasts, and to display the 3D virtual effect of breast reconstruction presented by the three-dimensional breast model before and after the operation according to the target breast reconstruction data interface corresponding to each patient, and to display prompt information related to the target breast reconstruction of each patient before and after the operation on the interface; A difference calculation module is used to obtain the external contour of the patient's breast based on three-dimensional scanning imaging, and calculate the volume difference of the breast models on both sides before surgery to obtain the volume difference between the affected breast and the healthy breast, and select and determine the volume of the target reconstructed breast and the surgical reference plan based on the volume difference; An index evaluation module is used to determine an expected three-dimensional breast model according to the volume of the target reconstructed breast, use the expected three-dimensional breast model as the model corresponding to the affected breast after surgery, and perform evaluations of different dimensions based on the expected three-dimensional breast model and the original three-dimensional breast models corresponding to the healthy / affected breasts, wherein the different dimensions at least include symmetry and postoperative effect prediction evaluation; The decision optimization module is used to comprehensively judge whether the expected three-dimensional breast model matches the preset decision model based on the evaluation results of different dimensions, generate a preoperative evaluation scale corresponding to the decision matching, and update and output the optimal target reconstructed breast volume and surgical reference plan.

2. The breast reconstruction preoperative decision-making support system based on three-dimensional scanning imaging according to claim 1, characterized in that: The acquisition planning module includes: An electronic medical record query unit, used to log in to the medical record homepage to query the electronic medical record EMR data, the electronic medical record EMR data including the patient's age, BMW constitution, past medical history, family history, smoking history and estimated costs; The laboratory query unit is used to connect to the laboratory management system LIS through the laboratory system interface to obtain the inspection report of the target object, wherein the inspection report includes cardiopulmonary function information, coagulation value and BMI index; The medical image query unit is used to connect to the medical image system DICOM through the Web API, establish a connection between the current electronic medical record page and the medical image system, obtain chest and abdominal CT, and measure the blood vessel diameter and blood volume flow of the target object; The data aggregation unit is used to aggregate the electronic medical record EMR data, examination and test reports, and chest and abdominal CT data to obtain the target breast reconstruction data of the current patient.

3. The breast reconstruction preoperative decision support system based on three-dimensional scanning imaging according to claim 1, characterized in that: The model building module includes: A parameter definition unit, used for extracting breast characteristic parameters through medical images and performing parameter definition, wherein the breast characteristics include the length of R line, H line, L line, Q line, and II line, and nipple diameter; A software selection unit, used for selecting mathematical modeling software according to breast characteristic parameters to perform three-dimensional modeling and data analysis, and generate a target breast model corresponding to both breasts; A basic shape creation unit, used for taking a basic model of a breast according to a basic geometric shape of a mathematical modeling software, and adjusting a size and a proportion of the model according to an R line, an H line, and an L line; An adjustment unit, used to adjust the inclination angle of the model according to the Q line, adjust the circumference of the model according to the Π line to ensure that the circumference of the target breast model is consistent with that of the actual breast, and adjust the position and diameter of the nipple to make the target breast model match the size and position of the actual nipple; A verification and optimization unit is used to compare the established target breast model with the actual breast image or data to check the accuracy of the model, perform iterative optimization according to requirements, and adjust the parameters of the target breast model to better match the actual data; The basic geometric shapes include a sphere and an ellipsoid, the R line represents the distance from the breast base to the nipple, the H line represents the vertical height of the breast, the L line represents the lateral length of the breast base, the Q line represents the inclination of the breast, and the Π line represents the circumference of the breast.

4. The breast reconstruction preoperative decision support system based on three-dimensional scanning imaging according to claim 1, characterized in that: The difference calculation module includes: A voxelization unit, used for acquiring three-dimensional image data in the target breast reconstruction data, and converting the three-dimensional image data into a voxel grid after preprocessing; A segmentation and labeling unit, used for distinguishing the target breast tissue from the background and non-breast tissue by using an image segmentation technology, and labeling the voxels of the target breast tissue; A volume calculation unit is used to calculate the number of all voxels marked as target breast tissues and multiply the volume of a single voxel, and to add up the volumes of all voxels corresponding to a single breast to obtain the total volume of the corresponding single breast; In three-dimensional space, the volume is obtained by calculating the sum of all voxels, and the calculation formula is as follows: Where V is the volume, vi is the volume of the i-th voxel, and n is the total number of voxels.

5. The breast reconstruction preoperative decision-making support system based on three-dimensional scanning imaging according to claim 1, characterized in that: The difference calculation module also includes: A mirror image overlapping unit is used to mirror the three-dimensional model of the healthy breast and overlap the three-dimensional breast model of the healthy breast with the three-dimensional breast model of the affected breast; A volume difference calculation unit is used to calculate the volume difference between the two sides of the three-dimensional breast model, that is, the volume difference, and output the breast volume difference predicted by PABVD; The target breast reconstruction unit is used to select the closest reconstructed breast volume PPV according to the calculated PABVD to determine the surgical reference plan and volume of the target breast reconstruction.

6. The breast reconstruction preoperative decision support system based on three-dimensional scanning imaging according to claim 1, characterized in that: The indicator evaluation module includes: A symmetry evaluation unit is used to compare the expected three-dimensional breast model with the original three-dimensional breast model corresponding to the healthy side breast to evaluate the symmetry of the two; The effect evaluation unit is used to compare the expected three-dimensional breast model with the original three-dimensional breast model corresponding to the affected breast to predict and evaluate the effect of the current model.

7. The breast reconstruction preoperative decision support system based on three-dimensional scanning imaging according to claim 1, characterized in that: The preset decision model extracts the influencing factors related to the current patient health index and the estimated cost influencing factors of each patient from the target breast reconstruction data, and comprehensively inputs all the influencing factors into the neural network to predict different target breast reconstructions to match the current patient health status and economic ability, and obtains the initial reference surgical plan for the target breast reconstruction.

8. A method for assisting decision-making before breast reconstruction surgery based on three-dimensional scanning imaging, applicable to the system for assisting decision-making before breast reconstruction surgery based on three-dimensional scanning imaging as claimed in any one of claims 1 to 7, characterized in that: include: Collecting and obtaining target breast reconstruction data of the patient, wherein the target breast reconstruction data at least includes the electronic medical record (EMR) data corresponding to the hospitalization number or name of each patient and the imaging data of both breasts obtained by three-dimensional scanning; Based on the collected imaging data of the bilateral breasts, a three-dimensional breast model including the healthy breast and the affected breast is created, and the 3D virtual effect of breast reconstruction presented by the three-dimensional breast model before and after the operation is displayed according to the target breast reconstruction data interface corresponding to each patient, and prompt information related to the target breast reconstruction of each patient before and after the operation is displayed on the interface; The external contour of the patient's breast is obtained based on three-dimensional scanning imaging, and the volume difference of the breast models on both sides is calculated before surgery to obtain the volume difference between the affected breast and the healthy breast, and the volume of the target reconstructed breast and the surgical reference plan are selected and determined based on the volume difference; Determine an expected three-dimensional breast model according to the volume of the target reconstructed breast, use the expected three-dimensional breast model as the model corresponding to the affected breast after surgery, and perform evaluations of different dimensions based on the expected three-dimensional breast model and the three-dimensional breast models corresponding to the original healthy / affected breasts, wherein the different dimensions at least include symmetry and postoperative effect prediction evaluation; Based on the evaluation results of different dimensions, a comprehensive judgment is made as to whether the expected three-dimensional breast model matches the preset decision model, a preoperative evaluation scale corresponding to the decision matching is generated, and the optimal target reconstructed breast volume and surgical reference plan are updated and output.

9. An electronic device, characterized in that: include: A memory, the memory being used to store a processing program; A processor, wherein when executing the processing program, the processor implements the preoperative decision-making auxiliary method for breast reconstruction based on three-dimensional scanning imaging as claimed in claim 8.

10. A computer readable medium storing a computer program, characterized in that: When the computer program is executed by one or more processors, the method for assisting decision-making before breast reconstruction surgery based on three-dimensional scanning imaging as claimed in claim 8 is implemented.

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