Ramesh Angelika, Henckel Johann, Hart Alister, Di Laura Anna
Department of Mechanical Engineering, University College London, Gower Street, London, UK.
Royal National Orthopaedic Hospital NHS Trust, Brockley Hill, Stanmore, UK.
J Orthop Res. 2025 Jan;43(1):173-182. doi: 10.1002/jor.25971. Epub 2024 Sep 18.
Statistical shape modeling (SSM) offers the potential to describe the morphological differences in similar shapes using a compact number of variables. Its application in orthopedics is rapidly growing. In this study, an SSM of the intramedullary canal of the proximal femur was built, with the aim to better understanding the complexity of its shape which may, in turn, enhance the preoperative planning of total hip arthroplasty (THA). This includes the prediction of the prosthetic femoral version (PFV) which is known to be highly variable amongst patients who have undergone THA. The model was built on three dimensional (3D) models of 64 femoral canals which were generated from pelvic computed tomography images including the proximal femur in the field of view. Principal component analysis (PCA) was performed on the mean shape derived from the model and each segmented canal. Five prominent modes of variations representing approximately 84% of the total 3D variations in the population of shapes were found to capture variability in size, proximal torsion, intramedullary femoral anteversion, varus/valgus orientation, and distal femoral shaft twist/torsion, respectively. It was established that the intramedullary femoral canal is highly variable in its size, shape, and orientation between different subjects. PCA-driven SSM is beneficial for identifying patterns and extracting valuable features of the femoral canal.
统计形状建模(SSM)提供了使用少量紧凑变量来描述相似形状形态差异的潜力。它在骨科领域的应用正在迅速增长。在本研究中,构建了近端股骨髓内管的SSM,目的是更好地理解其形状的复杂性,这反过来可能会加强全髋关节置换术(THA)的术前规划。这包括预测假体股骨旋转角度(PFV),已知在接受THA的患者中PFV差异很大。该模型基于64个股骨髓内管的三维(3D)模型构建,这些模型由包含视野内近端股骨的骨盆计算机断层扫描图像生成。对从模型和每个分割的髓内管导出的平均形状进行主成分分析(PCA)。发现代表形状总体中3D总变化约84%的五种主要变化模式分别捕获了大小、近端扭转、股骨髓内前倾、内翻/外翻方向以及远端股骨干扭转/旋转的变异性。已确定不同个体之间的股骨髓内管在大小、形状和方向上具有高度变异性。PCA驱动的SSM有助于识别股骨髓内管的模式并提取有价值的特征。