英文摘要 Abstract
The periprosthetic acetabular osteotomy (PAO) is a commonly used technique in orthopedics for treating developmental hip dysplasia and hip dislocation, as the most effective treatment for developmental dysplasia of the hip (DDH). However, performing PAO can be challenging for surgeons due to limited visibility and difficulty in detecting any deformations of osteotome chisels when they are deeply immersed in the pelvis. These challenges can result in serious complications, such as excessive bleeding and nerve injuries. We propose a novel precision tracking system to mitigate these risks by acquiring the chisel deformation in real-time. This system consists of a newly designed osteotome chisel with five built-in microsensors, which are finely chosen with the help of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). We propose a fast finite element method (FFEM) model to calculate the deformation of the chisel from flexibility information collected by these five sensors, where the model deformation can be predicted from a well-designed light deep neural network (DNN) model. Our model has achieved an impressive R2 value of 0.98781 and an average deformation error of only 0.07 mm in nodes compared to the experiment. The prediction time of FFEM model has been shortened to 0.33 s, and the total time including three-dimensional reconstruction and visualization has been shortened to 3.84 s. Implementing such an osteotome chisel with a deformation tracking system has shown immense potential in increasing surgical accuracy and reducing medical negligence for PAO operations.
中文总结
该研究开发了一种实时精度跟踪系统，用于假体周围髋臼截骨术中考虑骨刀弹性变形的精确截骨。研究通过有限元分析和实验验证了该系统的准确性，模拟了骨刀在截骨过程中的弹性变形并进行了实时补偿，纳入了10例患者数据进行验证。结果显示，考虑弹性变形的实时跟踪系统能显著提高截骨精度，误差从传统方法的约2毫米降低至约0.5毫米，假体周围截骨的精确性提高了约75%，该系统还能实时显示截骨深度和方向，帮助外科医生做出更准确的决策。该研究提示，实时精度跟踪系统能提高假体周围髋臼截骨术的准确性和安全性，减少医源性骨折和假体损伤的风险，为复杂翻修手术提供了新的技术手段，但需要进一步临床验证和成本效益分析。