基于有限元数据集建立髋臼周围截骨术的骨刀变形预测模型  

Predictive Modeling of Bone Knife Deformation in Periacetabular Osteotomy Based on Finite Element Dataset

作　　者：李玉梅[1] 韩阳 卢鼎 LI Yumei;HAN Yang;LU Ding(Beijing Key Laboratory of High Dynamic Navigation Technology,Key Laboratory of Modern Measurement&Control Technology,Ministry of Education,Beijing Information Science&Technology University,Beijing 100192,China)

机构地区：[1]北京信息科技大学高动态导航技术北京市重点实验室、现代测控技术教育部重点实验室,北京100192

出　　处：《医用生物力学》2024年第4期657-662,共6页Journal of Medical Biomechanics

摘　　要：目的建立一种用于髋臼周围截骨(periacetabular osteotomy,PAO)手术的骨刀变形预测模型,快速且精准地预测骨刀变形。方法建立包含皮质骨和松质骨的骨盆-骨刀有限元数值模型,分析节点应变与形变之间的相关性,并优选综合相关性最强的5个节点的应变作为输入,选择刀刃部分节点的位移增量作为输出。通过数据集训练模型后,采用基于有限元数据集的深度学习神经网络回归模型,建立骨刀应变-形变预测模型。在模型预测完成后,利用双目视觉定位系统确定截骨手术过程中骨刀的空间精确位置,以此对骨刀进行术中跟踪。结果预测模型的R^(2)为0.98781,骨刀离散成节点后的平均变形误差为0.07 mm。该预测模型能够快速且精确地获取骨刀变形,在降低PAO手术事故方面显示出巨大的潜力。结论建立的骨刀变形预测模型可通过骨刀的应变信息快速预测骨刀的变形,从而避免伤及组织周围神经和血管等组织,降低PAO术中难度和风险,并为临床应用提供理论支撑。Objective To establish a bone knife deformation prediction model for periacetabular osteotomy and quickly and accurately predict bone knife deformation.Methods A finite element numerical model of a pelvic bone knife containing both cortical and cancellous bones was established,and the correlation between nodal strain and deformation was analyzed.The strains of 5 nodes with the strongest integrated correlation were selected as the inputs,and the displacement increments of the nodes on the blade part were established as the outputs.After training the model with the dataset,a deep learning neural network regression model based on the finite element dataset was used to establish a prediction model for the strain deformation of the bone knife.After the model prediction was completed,a binocular visual localization system was used to determine the spatially accurate position of the bone knife during the osteotomy procedure as a means of intraoperative tracking of the bone knife.Results The R^(2) value of the prediction model was 0.98781 and the average deformation error after 657 discretizing the bone knife into nodes was 0.07 mm.The prediction model quickly and accurately acquired bone knife deformation and showed great potential for reducing PAO surgical accidents.Conclusions The bone knife deformation prediction model developed in this study rapidly predicted bone knife deformation from strain information.Thus,it can avoid injuring tissues,such as nerves and blood vessels around the tissue,reduce the difficulty and risk of periacetabular osteotomy,and provide theoretical support for clinical application.

关 键 词：截骨术 骨刀 变形预测 神经网络 有限元分析 

分 类 号：R318.01[医药卫生—生物医学工程]