目的 为提高反肩置换术术前规划的精准度和效率,本研究开发了"E骨"—反肩置换术一站式术前规划系统.方法 利用nnU-net深度神经网络进行肩胛骨分割,获得精确的肩胛骨分割结果;结合骨密度、上下倾角和入钉长度3个关键因素自动定位基座,并计算出手术规划所需定量参数;结合关节盂形态和基座定位信息生成个性化导板;编写系统界面,将各部分功能模块化组装便于使用,提供交互操作与规划结果显示的功能.结果 构建出"E骨"术前规划系统.本系统与Mimics系统相比,减少了规划过程中繁琐的手动调整,平均入钉长度规划结果长于Mimics系统,且规划时间缩短86%.本系统肩胛骨分割精度达到99.93%,较Mimics更高.结论 本研究为反肩置换术提供了一套一站式的高效、精准的术前规划方案,具有广泛的临床应用前景.
Objective To develop the'E-Bone',a comprehensive one-stop preoperative planning system for reverse total shoulder arthroplasty with improved accuracy and efficiency.Methods The nnU-net deep neural network was utilized for scapula segmentation to obtain precise scapula segmentation results.Based on the 3 key factors,namely bone density,upward and downward angle and nail length,the base was automatically positioned.The quantitative parameters required for surgical planning were calculated.A personalized guide plate was generated by combining glenoid morphology and base positioning information.The system interface was developed to modularize various functions for easy use,providing interactive operation and real-time display.Results Compared with the Mimics system,the'E-bone'preoperative planning system reduced complex manual adjustments during the planning process.The average planned nail length was longer than that of the Mimics system,and the planning time was reduced by 86%.The scapula segmentation accuracy of this system reached 99.93%,better than that of Mimics to achieve a higher precision.Conclusion The"E-bone"system provides a one-stop,efficient,and accurate preoperative planning system for reverse shoulder replacement and potentially broader clinical applications.
李穆;米昀;沈世文;吴心远;严静东;陈滨;曹蕾
南方医科大学南方医院 信息中心,广东 广州 510515南方医科大学 生物医学工程学院//广东省医学图像处理重点实验室//广东省医学成像与诊断技术工程实验室,广东 广州 510515南京大学医学院附属金陵医院(东部战区总医院)骨科,江苏 南京 210002南方医科大学南方医院 骨科-创伤骨科,广东 广州 510515||南方医科大学 第一临床医学院,广东 广州 510515南方医科大学南方医院 骨科-创伤骨科,广东 广州 510515
一站式;反肩置换术;术前规划系统;肩胛骨分割;基座定位
one-stop surgical planning;reverse total shoulder arthroplasty;preoperative planning system;scapula segmentation;base positioning
《南方医科大学学报》 2024 (005)
967-973 / 7
国家自然科学基金(12272164) Supported by National Natural Science Foundation of China(12272164).
10.12122/j.issn.1673-4254.2024.05.19
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