中国骨伤2025，Vol.38Issue(1)：31-40,10.DOI:10.12200/j.issn.1003-0034.20240601
人机交互CT影像AI识别定位技术在C1型桡骨远端骨折的初步应用
Preliminary application of human-computer interaction CT imaging AI recognition and positioning technology in the treatment of type C1 distal radius fractures
摘要
Abstract
Objective To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures.Methods Based on relevant inclusion and exclusion criteria,14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed,comprising 3 males and 11 females(aged from 27 to 82 years).The data were assigned randomized identifiers.A senior orthopedic physician reviewed the films and measured the ulnar deviation angle,radial height,palmar inclination angle,intra-articular step,and intra-articular gap for each case on the hospital's imaging system.Based on the reduction standard for distal radius fractures,cases were divided into reduction group and non-reduction group.Then,the data were sequentially imported into a human-computer interaction intelligent software,where a junior orthopedic physician analyzed the same radiological parameters,categorized cases,and measured fracture de-tails.The categorization results from the software were consistent with manual classifications(6 reduction cases and 8 non-re-duction cases).For non-reduction cases,the software performed further analyses,including bone segmentation and fracture recognition,generating 8 diagnostic reports containing fracture recognition information.For the 6 reduction cases,the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software,respec-tively.Bone segments requiring reduction were identified,verified by two senior physicians,and measured for displacement and rotation along the X(inward and outward),Z(front and back),and Y(up and down)axes.The AI software generated com-prehensive diagnostic reports for these cases,which included all measurements and fracture recognition details.Results Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups,with iden-tical data distributions.A paired sample t-test revealed no statistically significant differences(P＞0.05)between the manual and software-based measurements for ulnar deviation angle,radial ulnar bone height,palmar inclination angle,intra-articular step,and joint space.In fracture recognition,the AI software correctly identified 10 C-type fractures and 4 B-type fractures.For the 6 reduction cases,a total of 24 bone fragments were analyzed across both methods.After verification,it was found that the bone fragments identified by the two methods were consistent.A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X,Y,and Z axes were consistent between the two methods.No statistically significant differences(P＞0.05)were found between manual and software measurements for these parameters.Conclusion Hu-man-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in i-dentifying and locating type C1 distal radius fractures on CT imaging.关键词
桡骨远端骨折/人机交互/计算机断层扫描/AI识别定位Key words
Distal radius fracture/Human-Computer interaction/Computed tomography(CT)/AI-powered geolo-cation identification分类
医药卫生引用本文复制引用
成永忠,尹晓冬,刘飞,邓新恒,王朝鲁,崔书克,李永耀,闫威..人机交互CT影像AI识别定位技术在C1型桡骨远端骨折的初步应用[J].中国骨伤,2025,38(1):31-40,10.基金项目
中国中医科学院科技创新工程(编号:CI2021A02008) （编号:CI2021A02008）
首都临床特色诊疗技术研究及转化应用项目(编号:Z221100007422075) （编号:Z221100007422075）
中国中医科学院望京医院高水平中医医院建设项目中医药临床循证研究专项(编号:WJYY-XZKT-2023-14)China Academy of Chinese Medical Sciences Innovation and Technology Development Project(No.CI2021A02008) （编号:WJYY-XZKT-2023-14）
