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["E骨”——一种用于反式全肩关节置换术的一站式术前规划系统]

[The "E-bone" - a one-stop preoperative planning system for reverse total shoulder arthroplasty].

作者信息

Li M, Mi Y, Shen S, Wu X, Yan J, Chen B, Cao L

机构信息

Department of Information, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.

School of Biomedical Engineering//Guangdong Provincial Key Laboratory of Medical Image Processing//Guangdong Provincial Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510515, China.

出版信息

Nan Fang Yi Ke Da Xue Xue Bao. 2024 May 20;44(5):967-973. doi: 10.12122/j.issn.1673-4254.2024.05.19.

Abstract

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.

摘要

目的

开发“E 型骨”系统,这是一种用于反式全肩关节置换术的综合性一站式术前规划系统,具有更高的准确性和效率。

方法

利用 nnU-net 深度神经网络进行肩胛骨分割,以获得精确的肩胛骨分割结果。基于骨密度、上下角度和钉长这三个关键因素,自动进行基座定位。计算手术规划所需的定量参数。通过结合关节盂形态和基座定位信息生成个性化导板。开发系统界面,将各种功能模块化以便于使用,提供交互式操作和实时显示。

结果

与 Mimics 系统相比,“E 型骨”术前规划系统减少了规划过程中复杂的手动调整。平均规划钉长比 Mimics 系统更长,规划时间减少了 86%。该系统的肩胛骨分割准确率达到 99.93%,优于 Mimics 系统,实现了更高的精度。

结论

“E 型骨”系统为反式肩关节置换提供了一站式、高效且准确的术前规划系统,并具有潜在的更广泛临床应用前景。

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本文引用的文献

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nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation.
Nat Methods. 2021 Feb;18(2):203-211. doi: 10.1038/s41592-020-01008-z. Epub 2020 Dec 7.
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Reverse total shoulder arthroplasty: an imaging overview.
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The reverse shoulder arthroplasty angle: a new measurement of glenoid inclination for reverse shoulder arthroplasty.
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Factors contributing to glenoid baseplate micromotion in reverse shoulder arthroplasty: a biomechanical study.
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