Du Hailong, Hu Lei, Li Changsheng, He Chunqing, Zhang Lihai, Tang Peifu
Department of Orthopaedics, Chinese PLA General Hospital, Beijing, People's Republic of China.
Int J Med Robot. 2015 Mar;11(1):58-66. doi: 10.1002/rcs.1573. Epub 2014 Feb 12.
Balancing reduction accuracy with soft-tissue preservation is a challenge in orthopaedics. Computer-assisted orthopaedic surgery (CAOS) can improve accuracy and reduce radiation exposure. However, previous reports have not summarized the fracture patterns to which CAOS has been applied.
We used a CAOS system and a stereolithography model to define a new fracture classification. Twenty reduction tests were performed to evaluate the effectiveness of preoperative trajectory planning.
Twenty tests ran automatically and smoothly. Only three slight scratches occurred. Seventy-six path points represented displacement deviations of < 2 mm (average < 1 mm) and angulation deviation of < 1.5°.
Because of the strength of muscles, mechanical sensors are used to prevent iatrogenic soft-tissue injury. Secondary fractures are prevented mainly through preoperative trajectory planning. Based on our data, a 1 mm gap between the edges of fractures spikes is sufficient to avoid emergency braking from spike interference.
在骨科领域，平衡复位精度与软组织保护是一项挑战。计算机辅助骨科手术（CAOS）可以提高精度并减少辐射暴露。然而，既往报告并未总结CAOS所应用的骨折类型。
我们使用CAOS系统和立体光刻模型定义了一种新的骨折分类。进行了20次复位测试以评估术前轨迹规划的有效性。
20次测试自动且顺利进行。仅出现三处轻微划痕。76个路径点代表位移偏差<2毫米（平均<1毫米）且成角偏差<1.5°。
由于肌肉力量的影响，使用机械传感器来防止医源性软组织损伤。主要通过术前轨迹规划来预防二次骨折。根据我们的数据，骨折钉尖边缘之间1毫米的间隙足以避免因钉尖干扰而紧急制动。
