Orthopedic surgery risk assessment method and system

Abstract

The invention relates to the technical field of medical risk assessment, in particular to an orthopedic surgery risk assessment method and system. According to the method, the cortex thickness data of the multiple measurement points of the target bone area are accurately analyzed, so that the local thickness mutation part can be effectively identified, the intraoperative stress concentration area is accurately judged in combination with intraoperative intraosseous pressure data, and more comprehensive bone tissue stress adaptive capacity evaluation is ensured to be obtained in the preoperative stage. The local pressure change is monitored in the intraoperative stage, so that the mutation frequency of the stress concentration area is accurately screened, and the high-risk area of postoperative infection can be identified by combining the analysis of the tissue fluid permeation trend in the initial postoperative stage. In the postoperative stage, in combination with walking rhythm data, through the change trend of stride frequency fluctuation, step length variation and stride time stability, the overlapping condition of a stress area and an infection risk area is deeply analyzed, and a walking rhythm abnormal stage is accurately identified, so that a more targeted postoperative recovery evaluation system is established.

Description

Technical Field

[0001] The present invention relates to the technical field of medical risk assessment, and in particular to an orthopedic surgery risk assessment method and system. Background Art

[0002] The field of medical risk assessment technology includes technical methods for analyzing, predicting and managing the health risks that patients may face during diagnosis and treatment. The core content of this technical field includes the identification and evaluation of risk factors based on medical records, preoperative examination results, physiological parameters and related medical indicators. Medical risk assessment as a whole covers statistical analysis, risk model construction, application of machine learning algorithms and development of decision support systems, mainly used to predict surgical risks, drug side effects, disease progression trends and potential complications during hospitalization.

[0003] Among them, the orthopedic surgery risk assessment method refers to a technical means of evaluating the patient's postoperative complications, recovery status and surgical success rate in a quantitative or graded manner by systematically analyzing the patient's preoperative health status, imaging data, past medical history and intraoperative monitoring data. This method covers aspects such as bone density measurement based on imaging analysis, preoperative blood index screening, intraoperative physiological parameter monitoring and postoperative rehabilitation process data evaluation. By constructing a preoperative risk prediction model, combining patient characteristic parameters for data calculation, and using a special orthopedic database for comparative analysis, individualized preoperative risk assessment results are provided.

[0004] Existing technologies mainly rely on one-way analysis of preoperative health status, imaging data, medical history, and intraoperative monitoring data. The assessment of postoperative recovery is relatively limited, and it is difficult to achieve a systematic risk assessment across stages. Image analysis mainly focuses on bone density measurement, and fails to fully utilize the local change information of cortical bone thickness, resulting in limited accuracy of preoperative tolerance assessment. Although intraoperative monitoring covers physiological parameters, it has weak ability to identify sudden changes in local pressure and stress concentration areas, and fails to effectively predict high-risk areas that may cause tissue damage during surgery. Postoperative evaluation relies on rehabilitation process data, but lacks a systematic analysis of abnormal gait rhythm, making it difficult to accurately identify the limited recovery caused by preoperative or intraoperative risk factors during walking. Due to the lack of comprehensive analysis methods between multidimensional data, the correlation between preoperative, intraoperative and postoperative data is weak, making it difficult to achieve accurate surgical risk grading and individualized rehabilitation program formulation, resulting in certain limitations in postoperative infection risk control, gait stability recovery, and overall surgical prognosis evaluation. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an orthopedic surgery risk assessment method and system.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a method for risk assessment of orthopedic surgery, comprising the following steps: S1: Obtain cortical thickness data of multiple measurement points in the target bone area, establish a cortical thickness gradient distribution, screen the sites with local cortical thickness mutations, and generate bone cortical thickness mutation areas; S2: Obtain intraoperative bone pressure data of the portion corresponding to the thickness mutation region of the bone cortex, identify the local pressure change in the thickness mutation region, determine the stress adaptability of the thickness mutation region under intraoperative force changes, and obtain the intraoperative stress concentration region; S3: Screening the sites where the mutation frequency in the intraoperative stress concentration area exceeds the frequency threshold, comparing the local tissue fluid penetration trend in the early postoperative period, determining the sites with abnormal penetration and limited tissue repair, and obtaining the postoperative infection risk areas; S4: Obtain the data of the fluctuation rate of the gait frequency, the variability of the step length and the stability of the stride time during the patient's postoperative walking process, compare the overlap between the area where the force exceeds the force threshold during walking and the postoperative infection risk area, identify the stage of abnormal fluctuation of the gait rhythm, and obtain the analysis results of the abnormal gait rhythm after surgery; S5: Based on the postoperative gait rhythm abnormality analysis result, the corresponding surgical risk levels are divided to evaluate the surgical risk and generate an orthopedic surgery risk assessment result.

[0007] As a further scheme of the present invention, the bone cortical thickness mutation area includes the thickness mutation site, thickness gradient distribution, and local thickness change rate; the intraoperative stress concentration area includes the pressure mutation point, pressure gradient change trend, and stress adaptability assessment; the postoperative infection risk area includes the pressure mutation frequency distribution, abnormal tissue fluid infiltration site, and limited tissue repair area; the postoperative walking rhythm abnormality analysis results include the step frequency fluctuation range, step length variation range, and gait stability trend; the orthopedic surgery risk assessment results include the preoperative tolerance score, intraoperative stress load score, postoperative walking stability score, and risk level classification.

[0008] As a further solution of the present invention, the step of obtaining the bone cortical thickness mutation area is specifically: S111: obtaining cortical thickness data of multiple measurement points in the target bone region, including the backbone, joint end, weight-bearing area, and designated stress concentration area, measuring the cortical thickness value of each point, and establishing a measurement point index to obtain stored thickness data; S112: Based on the stored thickness data, the formula is used: ; Calculate measurement points Thickness variation rate at , and obtain the cortical thickness gradient distribution information; in, and Respectively indicate the measurement points and The cortical thickness, It is the measuring point and The spatial distance between is the three-dimensional coordinate value of the measurement point, It is the measuring point The three-dimensional coordinate value of S113: According to the cortical thickness gradient distribution information, the measurement points whose thickness change rate exceeds the set change threshold are screened, and the location area of ​​the measurement points is marked to generate a bone cortical thickness mutation area.

[0009] As a further solution of the present invention, the step of obtaining the stress concentration area during the operation is specifically as follows: S211: Obtain intra-osseous pressure data of the part corresponding to the bone cortical thickness mutation area during the operation, using the formula: ; Calculate the pressure gradient value of adjacent measuring points ; in, , , It is the measuring point exist , , The pressure component in the direction, , , The adjacent measuring points exist , , The pressure component in the direction, , , The adjacent measuring points and The spatial coordinate difference between ; S212: identifying the local pressure change in the thickness mutation area based on the pressure gradient value, screening the local pressure mutation point and analyzing the pressure fluctuation rate to obtain the local pressure mutation point identification result; S213: Determine the stress adaptability of the thickness mutation area in the local pressure mutation point identification result under intraoperative force changes to obtain the intraoperative stress concentration area.

[0010] As a further solution of the present invention, the step of obtaining the postoperative infection risk area is specifically as follows: S311: calling the intraoperative stress concentration area, screening the site where the mutation frequency exceeds the frequency threshold, obtaining the intraoperative pressure data of the implant fixation area, recording the intraoperative pressure change of the measuring point, and comparing the local tissue fluid permeation trend in the early postoperative period, extracting the permeation change rate in the time series, screening the tissue fluid permeation abnormal site corresponding to the pressure mutation point, and establishing the tissue fluid permeation distribution information in the early postoperative period; S312: calling the tissue fluid permeation distribution information in the early postoperative period, calculating the standard deviation of the tissue fluid permeation rate at the measuring point, analyzing the tissue adaptability in the stress concentration area, comparing the deviation of the permeation rate at each measuring point with the normal tissue physiological range, screening the measuring points whose permeation rate deviates from the normal permeation range, and identifying the corresponding local pressure mutation site, obtaining the tissue damage interval caused by the local pressure mutation, and establishing the tissue damage area distribution information; S313: Determine whether the tissue damage area distribution information contains abnormal permeability and limited tissue repair, compare the liquid permeability rate, stability parameters and permeability gradient changes between the damaged area and the normal postoperative repair area, screen the tissue damage area with limited repair, and obtain the postoperative infection risk area.

[0011] As a further solution of the present invention, the steps for obtaining the postoperative abnormal gait rhythm analysis results are specifically as follows: S411: Obtain the data of the fluctuation rate of the step frequency, the variability of the step length and the stability of the stride time during the patient's walking after surgery, identify the area where the force exceeds the force threshold during the walking process based on the force conditions at multiple time points during the walking process, and perform spatial overlap analysis with the postoperative infection risk area, calculate the overlap degree and regional distribution of the two, and obtain force overlap information; S412: Based on the force overlap information, the formula is used: ; Calculate the The fluctuation value of walking rhythm at each time point ; in, Representative Time point Dimensional walking rhythm parameters, Representative A point in time, The number of dimensions representing the walking rhythm parameters, It's at the time Next, gait parameters The numerical value of It's time point The time value of S413: Based on the gait rhythm fluctuation value, the stage of abnormal gait rhythm fluctuation is identified, and characteristic parameters of the cadence fluctuation rate, step length variability and stride time stability data in the abnormal stage are extracted, and combined with the patient's postoperative walking data, the postoperative gait rhythm abnormality analysis results are obtained.

[0012] As a further solution of the present invention, the steps for obtaining the orthopedic surgery risk assessment result are specifically as follows: S511: Based on the analysis results of abnormal walking rhythm after surgery, the postoperative infection risk area and the intraoperative stress concentration area are called to analyze the preoperative bone tissue tolerance, intraoperative local stress adaptability and postoperative walking recovery. The formula is: ; Calculating the Orthopaedic Surgery Global Score ; in, is the weight coefficient, is the standardized score of bone tissue tolerance before surgery, is the standardized score of intraoperative local stress adaptation, is the standardized score of postoperative walking recovery. The sampling points correspond to the preoperative bone tissue tolerance, intraoperative local stress adaptation, and postoperative walking recovery; S512: Generating an orthopedic surgery risk assessment result according to the corresponding risk level divided according to the overall orthopedic surgery score.

[0013] An orthopedic surgery risk assessment system, the orthopedic surgery risk assessment system is used to perform the orthopedic surgery risk assessment method, the system comprising: The bone cortical thickness mutation region identification module obtains the cortical thickness data of multiple measurement points in the target bone region, establishes the cortical thickness gradient distribution, selects the local cortical thickness mutation site, and generates the bone cortical thickness mutation region; The intraoperative stress concentration area analysis module obtains intraoperative bone pressure data of the corresponding part of the bone cortical thickness mutation area, identifies the local pressure change in the thickness mutation area, determines the stress adaptability of the thickness mutation area under the intraoperative force change, and obtains the intraoperative stress concentration area; The postoperative infection risk area assessment module selects the parts in the intraoperative stress concentration area where the mutation frequency exceeds the frequency threshold, compares the local tissue fluid penetration trend in the early postoperative period, determines the parts with abnormal penetration and limited tissue repair, and obtains the postoperative infection risk area; The postoperative walking rhythm abnormality analysis module obtains the data of the patient's step frequency fluctuation rate, step length variability and stride time stability during the patient's postoperative walking process, compares the overlap between the area where the force exceeds the force threshold during walking and the postoperative infection risk area, identifies the stage of abnormal walking rhythm fluctuation, and obtains the postoperative walking rhythm abnormality analysis results; The orthopedic surgery risk assessment module divides the corresponding surgical risk levels based on the postoperative gait rhythm abnormality analysis results and generates an orthopedic surgery risk assessment result.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by accurately analyzing the cortical thickness data of multiple measurement points in the target bone area, the local thickness mutation site can be effectively identified, and combined with the intraoperative bone pressure data, the intraoperative stress concentration area can be accurately judged to ensure a more comprehensive assessment of the stress adaptability of bone tissue in the preoperative stage. The monitoring of local pressure changes in the intraoperative stage enables the mutation frequency of the stress concentration area to be accurately screened, and combined with the analysis of the early postoperative tissue fluid penetration trend, it is possible to identify the high-risk area for postoperative infection. In the postoperative stage, combined with the walking rhythm data, through the changing trends of step frequency fluctuations, step length variation and stride time stability, the overlap between the stress area and the infection risk area is deeply analyzed, and the abnormal walking rhythm stage is accurately identified, thereby establishing a more targeted postoperative recovery evaluation system. Comprehensive preoperative bone tissue tolerance, intraoperative local stress adaptability and postoperative walking recovery, a standardized scoring system is used to quantify the overall surgical risk, and risk levels are divided based on the scoring results to provide more individualized preoperative decision support. A systematic evaluation method constructed based on four key dimensions: changes in cortical thickness, pressure mutation characteristics, tissue fluid infiltration trends, and gait rhythm fluctuations. This method can identify potential risks earlier and optimize postoperative rehabilitation plans. Compared with traditional methods, it has significant advantages in the accuracy of risk prediction, the depth of data utilization, and the comprehensiveness of postoperative recovery assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the workflow of the present invention; Figure 2 A flow chart for obtaining a bone cortical thickness mutation region for the present invention; Figure 3 A flow chart for obtaining the intraoperative stress concentration area for the present invention; Figure 4 A flow chart for obtaining postoperative infection risk areas for the present invention; Figure 5 A flowchart of the present invention for obtaining the analysis results of abnormal walking rhythm after surgery; Figure 6 The present invention is a flow chart for obtaining orthopedic surgery risk assessment results. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0017] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0018] See also Figure 1 The present invention provides a technical solution: a method for risk assessment of orthopedic surgery, comprising the following steps: S1: Obtain cortical thickness data of multiple measurement points in the target bone area, establish a cortical thickness gradient distribution, screen the sites with local cortical thickness mutations, and generate bone cortical thickness mutation areas; S2: Obtain intraoperative intraosseous pressure data of the corresponding part of the cortical bone thickness mutation area, identify the local pressure change in the thickness mutation area, determine the stress adaptability of the thickness mutation area under intraoperative force changes, and obtain the intraoperative stress concentration area; S3: Screen the areas where the mutation frequency exceeds the frequency threshold in the stress concentration area during surgery, compare the local tissue fluid penetration trend in the early postoperative period, determine the areas with abnormal penetration and limited tissue repair, and obtain the postoperative infection risk areas; S4: Obtain the data on the fluctuation rate of gait frequency, variability of step length and stability of stride time during the patient's postoperative walking process, compare the overlap between the area where the force exceeds the force threshold during walking and the area at risk of postoperative infection, identify the stage of abnormal fluctuation of gait rhythm, and obtain the analysis results of abnormal gait rhythm after surgery; S5: Based on the analysis results of postoperative abnormal gait rhythm, the corresponding surgical risk levels are divided to evaluate the surgical risk and generate orthopedic surgical risk assessment results; The areas of cortical bone thickness mutation include thickness mutation sites, thickness gradient distribution, and local thickness change rate. The areas of intraoperative stress concentration include pressure mutation points, pressure gradient change trends, and stress adaptability assessment. The areas of postoperative infection risk include pressure mutation frequency distribution, abnormal sites of tissue fluid infiltration, and areas of restricted tissue repair. The results of postoperative gait rhythm abnormality analysis include cadence fluctuation range, step length variation range, and gait stability trend. The results of orthopedic surgery risk assessment include preoperative tolerance score, intraoperative stress load score, postoperative gait stability score, and risk level classification.

[0019] See also Figure 2 The specific steps for obtaining the bone cortical thickness mutation area are as follows: S111: obtaining cortical thickness data of multiple measurement points in the target bone region, including the backbone, joint end, weight-bearing area, and designated stress concentration area, measuring the cortical thickness value of each point, and establishing a measurement point index to obtain stored thickness data; First, a high-resolution CT scanner is used to scan the target bone area to obtain the three-dimensional image data of the bone. Then, the three-dimensional image data is reconstructed using professional medical image processing software to generate a three-dimensional model of the bone. On the model, the positions of the backbone, joint end, weight-bearing area and stress concentration area are determined. Then, several measurement points are selected in these areas. For example, in the backbone area, a measurement point is selected every 5 mm; at the joint end, key parts are selected as measurement points according to the anatomical structure; in the weight-bearing area and stress concentration area, the part with the greatest force is selected as the measurement point. For each measurement point, the measurement tool of the image processing software is used to measure the thickness of the cortical bone, record the measurement results, and establish a measurement point index. The coordinates, region and thickness data of each measurement point are stored in the database. For example, measurement point A is located in the backbone area, with coordinates (x1, y1, z1) and a thickness of 2.5 mm; measurement point B is located at the joint end, with coordinates (x2, y2, z2) and a thickness of 3.0 mm. Through the above steps, the cortical thickness data of each measurement point in the target bone area is obtained and stored.

[0020] S112: Based on the stored thickness data, use the formula: ; Calculate measurement points Thickness variation rate at , and obtain the cortical thickness gradient distribution information; in, and Respectively indicate the measurement points and The cortical thickness is obtained through CT image data, measured using image processing software, and the cortical thickness value at the measuring point is taken. It is the measuring point and The spatial distance between them is calculated using the three-dimensional coordinates of each measuring point. It is the measuring point The three-dimensional coordinate values ​​are obtained by reconstructing the model through CT images. The model is established after CT scanning and the specific coordinate information of the measurement points is extracted in combination with the local coordinate system of the bone. It is the measuring point The three-dimensional coordinate values ​​of the measurement point Adjacent,is obtained through the CT image reconstruction model, which is established after CT scanning,and the specific coordinate information of the measurement points is extracted in combination with the local coordinate system of the bone,which is used to calculate the spatial distance between the measurement points. is the absolute difference in thickness between adjacent measuring points.

[0021] For example, the coordinates of measurement point A and measurement point B are (10, 20, 30) and (13, 24, 32), and their cortical thicknesses are 2.5 mm and 3.0 mm, respectively. Then calculate: , , by calculating the thickness change rate of all adjacent measuring points, it provides a basis for subsequent analysis.

[0022] S113: According to the cortical thickness gradient distribution information, the measurement points whose thickness change rate exceeds the set change threshold are selected, and the location area of ​​the measurement points is marked to generate a bone cortical thickness mutation area; Call the cortical thickness gradient distribution map to filter out the measurement points whose thickness change rate exceeds the set threshold. First, determine a reasonable threshold , the threshold can be determined based on clinical experience or statistical analysis, for example, mm / mm, then, traverse the thickness change rate of all measurement points , for each , if its value is greater than , it is considered that there is a mutation in cortical thickness at the measurement point, and these measurement points are marked, and their spatial coordinates and the area they belong to are recorded. For example, the thickness change rate of measurement point C is 0.1mm / mm, which is greater than the threshold value of 0.08mm / mm, so measurement point C is marked as a mutation point. Finally, based on these marked measurement points, a distribution map of bone cortical thickness mutation areas is generated. This map shows the areas in the bone where the cortical thickness changes abnormally, providing a reference for clinical diagnosis and treatment. Among them, The threshold value of thickness change rate can be obtained based on large-scale data statistics, such as the average value plus two times the standard deviation, or can be set based on the experience of medical experts. In this example, it is set to 0.08mm / mm. The marking measurement point refers to the thickness change rate. Exceeding the threshold The measurement points are marked and the coordinate information is stored. This result shows that by calculating the thickness change rate of adjacent measurement points, the local cortical thickness mutation area of ​​the bone can be effectively identified, and this data can be used to further analyze the bone strength distribution characteristics.

[0023] See also Figure 3 ,The specific steps for obtaining the stress concentration area during surgery are: S211: Obtain intraoperative bone pressure data corresponding to the area of ​​bone cortical thickness mutation using the formula: ; Calculate the pressure gradient value of adjacent measuring points ; in, , , It is the measuring point exist , , The pressure component in the direction is obtained by the pressure sensor and the unit is mmHg. , , The adjacent measuring points exist , , The pressure component in the direction is obtained by the pressure sensor. , , The adjacent measuring points and The spatial coordinate difference between them is obtained by reconstructing the three-dimensional model through CT images.

[0024] For example, suppose the measurement point and The coordinates are (10,20,30) mm and (13,24,32) mm, and the pressure values ​​are 35.2 mmHg and 38.6 mmHg, respectively. Then calculate: ; ; ; After calculating the pressure gradient values ​​of all adjacent measurement points, the pressure gradient distribution is established. The specific steps are as follows: sort the coordinates of all measurement points and the corresponding pressure data according to the spatial position to ensure the continuity of the gradient calculation; for each pair of adjacent measurement points, calculate their , , The gradient value of the direction is calculated and recorded in the database; all the calculated gradient values ​​are mapped to the three-dimensional coordinate system of the bone to construct a complete pressure gradient distribution; the pressure gradient distribution is represented by a three-dimensional color map or vector field to intuitively show the spatial variation of the intraosseous pressure during the operation. For example, a heat map is used to represent the magnitude of the gradient value, the red area represents the area with a higher gradient value, and the blue area represents the area with a lower gradient; finally, a complete pressure gradient distribution is established, which is used to identify the trend of intraosseous pressure changes during the operation and provide data support for subsequent local pressure analysis.

[0025] S212: identifying the local pressure change in the thickness mutation area based on the pressure gradient value, screening the local pressure mutation point and analyzing the pressure fluctuation rate to obtain the local pressure mutation point identification result; Call the pressure gradient distribution, analyze the change of local pressure in the thickness mutation area, select the measurement points whose pressure gradient values ​​exceed the set threshold, record their spatial coordinates, and calculate the pressure fluctuation rate of these points. First, set the pressure gradient threshold, such as 1.0mmHg / mm, and select the measurement points that exceed the threshold. For example, at the measurement point The pressure gradient value calculated at the point is 1.13 mmHg / mm, which is greater than the threshold. The measurement point is marked and its spatial coordinates (13, 24, 32) mm are stored. Subsequently, the pressure fluctuation rate of the point is calculated. Assuming that the pressure at the point is continuously monitored during the operation, the pressure is 38.6 mmHg at the initial moment and rises to 40.2 mmHg after 5 seconds. Then the calculation is: By calculating the pressure fluctuation rates of all measurement points exceeding the threshold, the local pressure fluctuation rate is obtained, and the distribution of local pressure mutation points is established.

[0026] S213: determining the stress adaptability of the thickness mutation area in the local pressure mutation point identification result under the intraoperative force change, and obtaining the intraoperative stress concentration area; The distribution of local pressure mutation points is called to determine the stress adaptability of the thickness mutation area under intraoperative force changes. First, the spatial distribution of mutation points is counted and the density of mutation points is analyzed. For example, if 7 pressure mutation points are detected in a 10mm×10mm area, the density of mutation points is calculated: Then, the average pressure fluctuation rate in different regions is calculated, for example , , At the three mutation points, the pressure fluctuation rates were measured to be 0.32 mmHg / s, 0.45 mmHg / s, and 0.28 mmHg / s, respectively. The regional average pressure fluctuation rate is calculated as: If the pressure fluctuation rate of the area is higher than the intraoperative safety benchmark value (such as 0.3 mmHg / s), it is determined that the stress adaptability of the area under intraoperative force changes is weak, and the area is screened as an intraoperative stress concentration area.

[0027] See also Figure 4 , the specific steps for obtaining the postoperative infection risk area are: S311: calling the intraoperative stress concentration area, screening the site where the mutation frequency exceeds the frequency threshold, obtaining the intraoperative pressure data of the implant fixation area, recording the intraoperative pressure change of the measuring point, and comparing the local tissue fluid penetration trend in the early postoperative period, extracting the penetration change rate in the time series, screening the tissue fluid penetration abnormal site corresponding to the pressure mutation point, and establishing the tissue fluid penetration distribution information in the early postoperative period; First, based on the intraoperative pressure data, the pressure changes of all measurement points in the stress concentration area are extracted, and a curve of pressure change over time is constructed to detect stress mutation points in the area. (Unit: Hz), that is, the number of times the pressure changes by more than the set amplitude per unit time, defining the pressure change rate ,when Exceeding the set pressure change threshold When , it is recorded as a mutation. , in the time interval Internal statistics of mutation times , get its mutation frequency: , if the mutation frequency of a measurement point satisfy , then mark the measurement point and store its spatial coordinates. Then, obtain the intraoperative pressure data of the implant fixation area where the measurement point is located, and construct the tissue fluid permeability change curve of the point in the early postoperative period. Set the measurement cycle ,exist Internal comparison of the permeability of the measurement point , get its time series permeability change rate , determine whether there is abnormal permeability. Set the normal permeability range ,filter The measurement points beyond this range are stored with their positions and pressure mutation characteristics to establish the early postoperative tissue fluid permeability distribution. Representative measurement point The mutation frequency at , in Hz; Representative measurement point The number of mutations at is calculated by the curve of pressure changing with time; Represents the measurement time interval, set by experiment, unit is s; Represents the set mutation frequency threshold, which is determined by historical data analysis; Represents the rate of pressure change, obtained through pressure data at adjacent time points; Represents the set pressure change threshold; Representative measurement point The tissue fluid permeability at the site was obtained through postoperative monitoring data, in mL / s; Represents the rate of change of tissue fluid permeability, calculated from postoperative time series data, unit: mL / (s²); Represents the normal range of tissue fluid permeability, measured from healthy tissue samples.

[0028] S312: calling the tissue fluid permeation distribution information in the early postoperative period, calculating the standard deviation of the tissue fluid permeation rate at the measuring point, analyzing the tissue adaptability in the stress concentration area, comparing the deviation of the permeation rate of each measuring point with the normal tissue physiological range, screening the measuring points whose permeation rate deviates from the normal permeation range, and identifying the corresponding local pressure mutation site, obtaining the tissue damage interval caused by the local pressure mutation, and establishing the tissue damage area distribution information; Based on the tissue fluid permeability distribution in the early postoperative period, the permeability rate of all measurement points was extracted. , get its mean and standard deviation , to determine the fluctuation of tissue fluid permeability rate, the calculation formula is as follows: , set the normal tissue fluid penetration rate range , obtain the permeability deviation of each measurement point , filter out the deviations greater than the set threshold The measurement points are matched with the corresponding local pressure mutation sites to obtain the tissue damage interval caused by the local pressure mutation and establish the tissue damage area distribution. Represents the standard deviation of tissue fluid permeation rate, which measures the degree of fluctuation of permeation rate between different measurement points; Represents the total number of measurement points; represents the average permeability rate of all measurement points; Representative measurement point The permeability deviation at ; Represents the set abnormal deviation threshold.

[0029] S313: Determine whether the tissue damage area distribution information has permeability abnormalities and tissue repair restriction, compare the liquid permeation rate, stability parameters and permeation gradient changes of the damaged area and the normal repair area after surgery, screen the tissue damage area with restricted repair, and obtain the postoperative infection risk area; First, based on the distribution of tissue damage area, the tissue fluid permeation rate at the measurement point in the damage area is extracted. , obtain the permeability stability parameters of the area , the calculation formula is as follows: , setting the permeability stability threshold ,like , then there is permeability abnormality in this area, and the permeability gradient change between the damaged area and the normal repair area is further calculated : .in, represents the permeability stability parameter of the damaged area; Represents the total number of measurement points within the damage area; Represents the measurement point within the damaged area The penetration rate; represents the average penetration rate of the damaged area; represents the abnormal threshold of osmotic stability; represents the change in the permeability gradient in the damaged area; and Represent the highest and lowest permeability rates in the damaged area, respectively; Represents the average distance between measurement points. If the damaged area meets and If it is higher than the set threshold, it is determined that tissue repair in the area is restricted, and the restricted area is further screened out to obtain the postoperative infection risk area.

[0030] See also Figure 5 The specific steps for obtaining the results of postoperative abnormal walking rhythm analysis are as follows: S411: Obtain the data of the fluctuation rate of the step frequency, the variability of the step length and the stability of the stride time during the patient's walking after surgery, identify the area where the force exceeds the force threshold during the walking process based on the force conditions at different time points during the walking process, and perform spatial overlap analysis with the postoperative infection risk area, calculate the overlap degree and regional distribution of the two, and obtain the force overlap information; To obtain the data on the fluctuation rate of gait frequency, variability of stride length and stability of stride time during the patient's postoperative walking process, it is necessary to perform dynamic gait monitoring on the patient after surgery. By setting multiple detection points during the walking process, the gait frequency, stride length and stride time at different time points during the walking process are collected, and their changes are recorded. The gait frequency fluctuation rate can be calculated by detecting the rate of change of the number of steps per minute during the walking process, and the variability of the stride length is obtained by calculating the ratio of the standard deviation of the continuous step length to the average step length. The stability of the stride time can be obtained by calculating the time difference between two consecutive steps. Assuming that the gait frequency data of a patient within 10 seconds during walking are [92, 95, 93, 94, 97, 96, 98, 99, 100, 101] respectively, the gait frequency fluctuation rate can be calculated as the sum of the squares of the deviations from the average value at each time point, taking the mean and then taking the square root, the gait frequency fluctuation rate is calculated to be approximately 2.69, the stride length variability and stride time stability data were calculated by the same method. Next, the force conditions at different time points during walking need to be analyzed. First, a pressure sensing device is laid on the sole of the patient's shoe or on the ground to record the pressure distribution in different areas of the sole during walking and compare it with the preset force threshold. Assuming that the threshold is set to 30N / cm², the pressure data [28, 32, 35, 30, 33, 29, 31, 36, 34, 32] are measured, and the area exceeding 30N / cm² is marked as a high-force area. The spatial overlap between the high-force area and the postoperative infection risk area is calculated. Assuming that the postoperative infection risk area accounts for 20%, the high-force area accounts for 25%, and the overlapping area between the two accounts for 15%, the overlap is calculated as 15 / (20+25−15)=0.5, which is the force threshold overlap.

[0031] S412: Based on the force overlap information, the formula is used: ; Calculate the The fluctuation value of walking rhythm at each time point ; in, Representative Time point The dimensional walking rhythm parameters (including cadence fluctuation, stride length variability and stride time stability) are measured and recorded by gait monitoring equipment. The stride length variability can be obtained by normalizing the stride length data after calculating the standard deviation. Representative The time points, i.e. the time series of gait parameter measurements, can be directly recorded and acquired through time synchronization equipment. The number of dimensions representing walking rhythm parameters, namely the total number of cadence fluctuations, stride length variability, and stride time stability. It's at the time Next, gait parameters (parameters such as step frequency fluctuation, step length variability, stride time stability, etc.) It's time point The specific time value represents the continuous time points recorded during the gait monitoring process. Represents the change in walking rhythm parameters at adjacent time points, which is obtained by the difference between the parameter data at two time points. Represents the time interval between adjacent time points.

[0032] The values ​​of step frequency fluctuation rate, step length variability and stride time stability at multiple time points are shown in the following table. Table 1 Monitoring data of walking rhythm parameters: ; According to the data in Table 1, calculate the walking rhythm fluctuation value at the second time point: ; The walking rhythm fluctuation values ​​at other time points are calculated using this method, and finally the walking rhythm fluctuation trend data are obtained, indicating the changes in the walking rhythm fluctuation.

[0033] S413: Based on the gait rhythm fluctuation value, the stage of abnormal gait rhythm fluctuation is identified, and characteristic parameters of the gait frequency fluctuation rate, step length variability and stride time stability data in the abnormal stage are extracted, and combined with the patient's postoperative walking data, the postoperative gait rhythm abnormality analysis result is obtained; By counting the normal gait rhythm fluctuation range of the patient, the range of the mean value plus or minus the standard deviation is used as the benchmark value. Assuming that the calculated average value of the normal gait rhythm fluctuation value is 0.25 and the standard deviation is 0.05, the abnormal judgment threshold is set to [0.15, 0.35]. When the gait rhythm fluctuation value exceeds this range, it is considered that the gait rhythm has abnormal fluctuations. By calculating the gait rhythm fluctuation value, if the calculated values ​​at time points 4 and 5 are 0.38 and 0.41 respectively, both exceeding the threshold range, the gait rhythm at time points 4 and 5 is marked as an abnormal stage, and the characteristic parameters of step frequency fluctuation rate, step length variability and stride time stability in the abnormal stage are further extracted. For example, the step length variation at time point 4 is 0.15, the step frequency fluctuation is 3.2, and the stride time stability is 0.11, while the step length variation at time point 5 is 0.18, the step frequency fluctuation is 3.5, and the stride time stability is 0.13. The calculated walking rhythm fluctuation value range is [0.15, 0.41]. Points outside the normal range are identified as abnormal gait. The walking rhythm fluctuation values ​​at time points 4 and 5 are 0.38 and 0.41, respectively, both exceeding the baseline value of 0.35, which means that the patient's walking rhythm at these time points during the postoperative rehabilitation process has a large fluctuation. This result can be used to further adjust the patient's rehabilitation training plan. Finally, these characteristic parameters are integrated to obtain the analysis results of postoperative walking rhythm abnormality.

[0034] See also Figure 6 , the specific steps for obtaining the risk assessment results of orthopedic surgery are as follows: S511: Based on the analysis results of abnormal walking rhythm after surgery, the postoperative infection risk area and the intraoperative stress concentration area are called to analyze the preoperative bone tissue tolerance, intraoperative local stress adaptability and postoperative walking recovery. The formula is: ; Calculating the Orthopaedic Surgery Global Score ; in, The value range is 0-1, indicating the overall recovery of the patient after surgery. is the weight coefficient, ranging from 0.1 to 0.5. The specific value is set according to bone density, stress concentration during surgery, and gait recovery after surgery. The setting is based on the following: The value is set to 0.5 when the bone quality is poor (less than 0.6 g / cm²), 0.3 when the bone density is 0.6-1.0 g / cm², and 0.1 when the bone density is above 1.0 g / cm². The value is set according to the local stress concentration during the operation. If the local stress exceeds 2.5MPa, it is set to 0.5; if the local stress is between 1.5-2.5MPa, it is set to 0.3; and if the local stress is less than 1.5MPa, it is set to 0.1. The value is set according to the postoperative walking recovery. If the cadence fluctuation rate is greater than 0.3 Hz, the step length variability is greater than 5 cm, and the stride time stability is greater than 10%, it is set to 0.5. If the cadence fluctuation rate is 0.1-0.3 Hz, the step length variability is 2-5 cm, and the stride time stability is 5-10%, it is set to 0.3. If it is below this range, it is set to 0.1. It is the standardized score of bone tissue tolerance before surgery. The unit is dimensionless and is derived from the conversion score of bone density and trabecular distribution data. The range is 0-1. It is the standardized score of intraoperative local stress adaptation, with dimensionless units, converted from intraoperative pressure measurement data, ranging from 0 to 1. It is a standardized score for postoperative walking recovery. The unit is dimensionless and the score is converted from gait monitoring data. The range is 0-1. are the number of data points, corresponding to the sampling points of preoperative bone tissue tolerance, intraoperative local stress adaptation, and postoperative walking recovery.

[0035] If the patient's preoperative bone density is 0.7g / cm², trabecular volume ratio is 0.25, intraoperative stress peak is 2.6MPa, postoperative cadence fluctuation is 0.35Hz, step length variation is 6cm, and stride time stability is 11%, then the corresponding weights are: (bone density 0.7g / cm²), (Intraoperative stress 2.6MPa), (abnormal walking recovery after surgery), if the number of data points is 4: ; ; ; ; The patient's surgical risk score was 0.955.

[0036] S512: According to the overall score of orthopedic surgery, the corresponding risk level is divided to generate the orthopedic surgery risk assessment result; Based on the overall score of orthopedic surgery , set the risk level classification standard, and the low risk interval is set as , the medium risk interval is set as , the high risk interval is set as According to the calculation results in paragraph 1, the patient's surgical risk score is 0.955, which is in the low risk range. Therefore, the surgical risk assessment result of this patient is judged to be low risk. Combined with the postoperative gait rhythm data, if the patient's gait rhythm fluctuation remains stable within 2 weeks after surgery, that is, the gait frequency fluctuation rate remains at 0.1-0.3Hz, the step length variability remains at 2-5cm, and the stride time stability remains at 5-10%, then the low risk assessment result is maintained. If the gait abnormality persists for more than 2 weeks during the postoperative recovery process, that is, the gait frequency fluctuation rate exceeds 0.3Hz, the step length variability exceeds 5cm, and the stride time stability exceeds 10%, then according to the risk adjustment rules, the surgical risk assessment result may be adjusted from low risk to medium risk, and finally the orthopedic surgery risk assessment result is obtained.

[0037] An orthopedic surgery risk assessment system is used to implement the orthopedic surgery risk assessment method. The system includes: The bone cortical thickness mutation region identification module obtains the cortical thickness data of multiple measurement points in the target bone region, establishes the cortical thickness gradient distribution, selects the local cortical thickness mutation site, and generates the bone cortical thickness mutation region; The intraoperative stress concentration area analysis module obtains intraoperative bone pressure data corresponding to the area of ​​cortical bone thickness mutation, identifies the local pressure change in the area of ​​thickness mutation, determines the stress adaptability of the area of ​​thickness mutation under intraoperative force changes, and obtains the intraoperative stress concentration area; The postoperative infection risk area assessment module screens the areas where the mutation frequency exceeds the frequency threshold in the intraoperative stress concentration area, compares the local tissue fluid penetration trend in the early postoperative period, determines the areas with abnormal penetration and limited tissue repair, and obtains the postoperative infection risk area; The postoperative walking rhythm abnormality analysis module obtains the data of the patient's step frequency fluctuation rate, step length variability and stride time stability during the postoperative walking process, compares the overlap between the area where the force exceeds the force threshold during walking and the postoperative infection risk area, identifies the stage of abnormal walking rhythm fluctuation, and obtains the postoperative walking rhythm abnormality analysis results; The orthopedic surgery risk assessment module divides the corresponding surgical risk levels based on the postoperative gait rhythm abnormality analysis results and generates orthopedic surgery risk assessment results.

[0038] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for risk assessment of orthopedic surgery, characterized in that: The following steps are involved: S1: Obtain cortical thickness data of multiple measurement points in the target bone area, establish a cortical thickness gradient distribution, screen the sites with local cortical thickness mutations, and generate bone cortical thickness mutation areas; S2: Obtain intraoperative bone pressure data of the portion corresponding to the thickness mutation region of the bone cortex, identify the local pressure change in the thickness mutation region, determine the stress adaptability of the thickness mutation region under intraoperative force changes, and obtain the intraoperative stress concentration region; S3: Screening the sites where the mutation frequency in the intraoperative stress concentration area exceeds the frequency threshold, comparing the local tissue fluid penetration trend in the early postoperative period, determining the sites with abnormal penetration and limited tissue repair, and obtaining the postoperative infection risk areas; S4: Obtain the data of the fluctuation rate of the gait frequency, the variability of the step length and the stability of the stride time during the patient's postoperative walking process, compare the overlap between the area where the force exceeds the force threshold during walking and the postoperative infection risk area, identify the stage of abnormal fluctuation of the gait rhythm, and obtain the analysis results of the abnormal gait rhythm after surgery; S5: Based on the postoperative gait rhythm abnormality analysis result, the corresponding surgical risk levels are divided to evaluate the surgical risk and generate an orthopedic surgery risk assessment result.

2. The orthopedic surgery risk assessment method according to claim 1, characterized in that: The bone cortical thickness mutation area includes the thickness mutation site, thickness gradient distribution, and local thickness change rate; the intraoperative stress concentration area includes the pressure mutation point, pressure gradient change trend, and stress adaptability assessment; the postoperative infection risk area includes the pressure mutation frequency distribution, abnormal tissue fluid infiltration site, and limited tissue repair area; the postoperative walking rhythm abnormality analysis results include the step frequency fluctuation range, step length variation range, and gait stability trend; the orthopedic surgery risk assessment results include the preoperative tolerance score, intraoperative stress load score, postoperative walking stability score, and risk level classification.

3. The orthopedic surgery risk assessment method according to claim 2, characterized in that: The steps for obtaining the bone cortical thickness mutation region are specifically as follows: S111: obtaining cortical thickness data of multiple measurement points in the target bone region, including the backbone, joint end, weight-bearing area, and designated stress concentration area, measuring the cortical thickness value of each point, and establishing a measurement point index to obtain stored thickness data; S112: Based on the stored thickness data, the formula is used: ； Calculate measurement points Thickness variation rate at , and obtain the cortical thickness gradient distribution information; in, and Respectively indicate the measurement points and The cortical thickness, It is the measuring point and The spatial distance between It is the measuring point The three-dimensional coordinate values ​​of It is the measuring point The three-dimensional coordinate value of S113: According to the cortical thickness gradient distribution information, the measurement points whose thickness change rate exceeds the set change threshold are screened, and the location area of ​​the measurement points is marked to generate a bone cortical thickness mutation area.

4. The orthopedic surgery risk assessment method according to claim 3, characterized in that: The steps for obtaining the stress concentration area during the operation are specifically as follows: S211: Obtain intra-osseous pressure data of the part corresponding to the bone cortical thickness mutation area during the operation, using the formula: ； Calculate the pressure gradient value of adjacent measuring points ; in, , , It is the measuring point exist , , The pressure component in the direction, , , The adjacent measuring points exist , , The pressure component in the direction, , , The adjacent measuring points and The spatial coordinate difference between ; S212: identifying the local pressure change in the thickness mutation area based on the pressure gradient value, screening the local pressure mutation point and analyzing the pressure fluctuation rate to obtain the local pressure mutation point identification result; S213: Determine the stress adaptability of the thickness mutation area in the local pressure mutation point identification result under intraoperative force changes to obtain the intraoperative stress concentration area.

5. The orthopedic surgery risk assessment method according to claim 4, characterized in that: The specific steps for obtaining the postoperative infection risk area are: S311: calling the intraoperative stress concentration area, screening the site where the mutation frequency exceeds the frequency threshold, obtaining the intraoperative pressure data of the implant fixation area, recording the intraoperative pressure change of the measuring point, and comparing the local tissue fluid permeation trend in the early postoperative period, extracting the permeation change rate in the time series, screening the tissue fluid permeation abnormal site corresponding to the pressure mutation point, and establishing the tissue fluid permeation distribution information in the early postoperative period; S312: calling the tissue fluid permeation distribution information in the early postoperative period, calculating the standard deviation of the tissue fluid permeation rate at the measuring point, analyzing the tissue adaptability in the stress concentration area, comparing the deviation of the permeation rate at each measuring point with the normal tissue physiological range, screening the measuring points whose permeation rate deviates from the normal permeation range, and identifying the corresponding local pressure mutation site, obtaining the tissue damage interval caused by the local pressure mutation, and establishing the tissue damage area distribution information; S313: Determine whether the tissue damage area distribution information contains abnormal permeability and limited tissue repair, compare the liquid permeability rate, stability parameters and permeability gradient changes between the damaged area and the normal postoperative repair area, screen the tissue damage area with limited repair, and obtain the postoperative infection risk area.

6. The orthopedic surgery risk assessment method according to claim 5, characterized in that: The steps for obtaining the postoperative abnormal gait rhythm analysis results are specifically as follows: S411: Obtain the data of the fluctuation rate of the step frequency, the variability of the step length and the stability of the stride time during the patient's walking after surgery, identify the area where the force exceeds the force threshold during the walking process based on the force conditions at multiple time points during the walking process, and perform spatial overlap analysis with the postoperative infection risk area, calculate the overlap degree and regional distribution of the two, and obtain force overlap information; S412: Based on the force overlap information, the formula is used: ； Calculate the The fluctuation value of walking rhythm at each time point ; in, Representative Time point Dimensional walking rhythm parameters, Representative A point in time, The number of dimensions representing the walking rhythm parameters, It's at the time Next, gait parameters The numerical value of It's time point The time value of S413: Based on the gait rhythm fluctuation value, the stage of abnormal gait rhythm fluctuation is identified, and characteristic parameters of the cadence fluctuation rate, step length variability and stride time stability data in the abnormal stage are extracted, and combined with the patient's postoperative walking data, the postoperative gait rhythm abnormality analysis results are obtained.

7. The orthopedic surgery risk assessment method according to claim 6, characterized in that: The steps for obtaining the orthopedic surgery risk assessment results are specifically as follows: S511: Based on the analysis results of abnormal walking rhythm after surgery, the postoperative infection risk area and the intraoperative stress concentration area are called to analyze the preoperative bone tissue tolerance, intraoperative local stress adaptability and postoperative walking recovery. The formula is: ； Calculating the Orthopaedic Surgery Global Score ; in, is the weight coefficient, is the standardized score of bone tissue tolerance before surgery, is the standardized score of intraoperative local stress adaptation, is the standardized score of postoperative walking recovery. The sampling points correspond to the preoperative bone tissue tolerance, intraoperative local stress adaptation, and postoperative walking recovery; S512: Generating an orthopedic surgery risk assessment result according to the corresponding risk level divided according to the overall orthopedic surgery score.

8. An orthopedic surgery risk assessment system, characterized in that: According to the orthopedic surgery risk assessment method according to any one of claims 1 to 7, the system comprises: The bone cortical thickness mutation region identification module obtains the cortical thickness data of multiple measurement points in the target bone region, establishes the cortical thickness gradient distribution, selects the local cortical thickness mutation site, and generates the bone cortical thickness mutation region; The intraoperative stress concentration area analysis module obtains intraoperative bone pressure data of the corresponding part of the bone cortical thickness mutation area, identifies the local pressure change in the thickness mutation area, determines the stress adaptability of the thickness mutation area under the intraoperative force change, and obtains the intraoperative stress concentration area; The postoperative infection risk area assessment module selects the parts in the intraoperative stress concentration area where the mutation frequency exceeds the frequency threshold, compares the local tissue fluid penetration trend in the early postoperative period, determines the parts with abnormal penetration and limited tissue repair, and obtains the postoperative infection risk area; The postoperative walking rhythm abnormality analysis module obtains the data of the patient's step frequency fluctuation rate, step length variability and stride time stability during the patient's postoperative walking process, compares the overlap between the area where the force exceeds the force threshold during walking and the postoperative infection risk area, identifies the stage of abnormal walking rhythm fluctuation, and obtains the postoperative walking rhythm abnormality analysis results; The orthopedic surgery risk assessment module divides the corresponding surgical risk levels based on the postoperative gait rhythm abnormality analysis results and generates an orthopedic surgery risk assessment result.

Images