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基于机器人辅助手术的实验研究：下肢骨折复位手术规划导航系统

Experimental research based on robot-assisted surgery: Lower limb fracture reduction surgery planning navigation system.

作者信息

Du Hanwen, Wu Geyang, Hu Ying, He Yucheng, Zhang Peng

机构信息

Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China.

University of Chinese Academy of Sciences Beijing China.

出版信息

Health Sci Rep. 2024 Apr 22;7(4):e2033. doi: 10.1002/hsr2.2033. eCollection 2024 Apr.

DOI:10.1002/hsr2.2033
PMID:38655421
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11035755/
Abstract

BACKGROUND AND AIMS

Lower extremity fracture reduction surgery is a key step in the treatment of lower extremity fractures. How to ensure high precision of fracture reduction while reducing secondary trauma during reduction is a difficult problem in current surgery.

METHODS

First, segmentation and three-dimensional reconstruction are performed based on fracture computed tomography images. A cross-sectional point cloud extraction algorithm based on the normal filtering of the long axis of the bone is designed to obtain the cross-sectional point clouds of the distal bone and the proximal bone, and the optimal reset target pose of the broken bone is obtained by using the iterative closest point algorithm. Then, the optimal reset sequence of reset parameters was determined, combined with the broken bone collision detection algorithm, a surgical planning algorithm for lower limb fracture reset was proposed, which can effectively reduce the reset force while ensuring the accuracy of the reset process without collision.

RESULTS

The average error of the reduction of the model bone was within 1.0 mm. The reduction operation using the planning and navigation system of lower extremity fracture reduction surgery can effectively reduce the reduction force. At the same time, it can better ensure the smooth change of the reduction force.

CONCLUSION

Planning and navigation system of lower extremity fracture reduction surgery is feasible and effective.

摘要

背景与目的

下肢骨折复位手术是治疗下肢骨折的关键步骤。如何在减少复位过程中二次创伤的同时确保骨折复位的高精度是当前手术中的一个难题。

方法

首先，基于骨折计算机断层扫描图像进行分割和三维重建。设计一种基于骨骼长轴法线滤波的横截面点云提取算法，以获取远端骨骼和近端骨骼的横截面点云，并通过迭代最近点算法获得骨折的最佳复位目标姿态。然后，确定复位参数的最佳复位顺序，结合骨折碰撞检测算法，提出一种下肢骨折复位手术规划算法，该算法在确保复位过程准确性且无碰撞的同时，能有效降低复位力。

结果

模型骨复位的平均误差在1.0毫米以内。使用下肢骨折复位手术规划与导航系统进行复位操作可有效降低复位力。同时，能更好地确保复位力的平稳变化。

结论

下肢骨折复位手术规划与导航系统是可行且有效的。

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本文引用的文献

1
A Bibliometric Analysis of the Field of Computer-Assisted Orthopedic Surgery during 2002-2021.2002-2021 年计算机辅助骨科手术领域的文献计量分析。
Clin Orthop Surg. 2023 Apr;15(2):227-233. doi: 10.4055/cios21217. Epub 2022 Aug 16.
2
Design and evaluation of an intelligent reduction robot system for the minimally invasive reduction in pelvic fractures.智能骨盆骨折微创复位机器人系统的设计与评估
J Orthop Surg Res. 2022 Apr 4;17(1):205. doi: 10.1186/s13018-022-03089-2.
3
Anatomically Parameterized Statistical Shape Model: Explaining Morphometry Through Statistical Learning.
解剖参数化统计形状模型：通过统计学习解释形态计量学。
IEEE Trans Biomed Eng. 2022 Sep;69(9):2733-2744. doi: 10.1109/TBME.2022.3152833. Epub 2022 Aug 19.
4
Augmented Reality Assisted Surgical Navigation System for Epidural Needle Intervention.增强现实辅助的硬膜外针介入手术导航系统。
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:4705-4708. doi: 10.1109/EMBC46164.2021.9629804.
5
A system for 3D reconstruction of comminuted tibial plafond bone fractures.粉碎性胫骨平台骨折的 3D 重建系统。
Comput Med Imaging Graph. 2021 Apr;89:101884. doi: 10.1016/j.compmedimag.2021.101884. Epub 2021 Feb 26.
6
Estimating Reference Bony Shape Models for Orthognathic Surgical Planning Using 3D Point-Cloud Deep Learning.利用 3D 点云深度学习技术估算正颌手术规划中的参考骨性形态模型。
IEEE J Biomed Health Inform. 2021 Aug;25(8):2958-2966. doi: 10.1109/JBHI.2021.3054494. Epub 2021 Aug 5.
7
Fracture reduction planning and guidance in orthopaedic trauma surgery via multi-body image registration.通过多体图像配准实现骨科创伤手术中的骨折复位规划与引导
Med Image Anal. 2021 Feb;68:101917. doi: 10.1016/j.media.2020.101917. Epub 2020 Nov 30.
8
Indirect visual guided fracture reduction robot based on external markers.基于外部标记的间接可视引导骨折复位机器人。
Int J Med Robot. 2021 Feb;17(1):1-11. doi: 10.1002/rcs.2162. Epub 2020 Sep 12.
9
A review of computer-assisted orthopaedic surgery systems.计算机辅助骨科手术系统综述。
Int J Med Robot. 2020 Oct;16(5):1-28. doi: 10.1002/rcs.2118. Epub 2020 Jul 7.
10
Surgical Navigation in Orthopedics: Workflow and System Review.骨科手术导航：工作流程和系统评价。
Adv Exp Med Biol. 2018;1093:47-63. doi: 10.1007/978-981-13-1396-7_4.