Biomedical Engineering Department, Politecnico di Milano, 20133 Milan, Italy.
Ann Biomed Eng. 2010 May;38(5):1752-66. doi: 10.1007/s10439-010-9965-x. Epub 2010 Feb 23.
Bone morphology and morphometric measurements of the lower limb provide significant and useful information for computer-assisted orthopedic surgery planning and intervention, surgical follow-up evaluation, and personalized prosthesis design. Femoral head radius and center, neck axis and size, femoral offset and shaft axis are morphological and functional parameters of the proximal femur utilized both in diagnosis and therapy. Obtaining this information from image data without any operator supervision or manual editing remains a practical objective to avoid variability intrinsic in the manual analysis. In this article, we propose a heuristic method that automatically computes the proximal femur morphological parameters by processing the mesh surface of the femur. The surface data are sequentially processed using geometrical properties such as symmetries, asymmetries, and principal elongation directions. Numerical methods identify the axis of the shaft of femur (least squares cylinder fitting), the head surface and center (least squares sphere fitting), and the femur neck axis and radius (minimal area of the cross section by evolutionary optimization). The repeatability of the method was tested upon 20 femur (10 left + 10 right) surfaces reconstructed from CT scans taken on cadavers. The repeatability error of the automated computation of anatomical landmarks, angles, sizes, and axes was less than 1.5 mm, 2.5 degrees, 1.0 mm, and 3.5 mm, respectively. The computed parameters were in good agreement (landmark difference: <2.0 mm; angle difference: <2.0 degrees; axes difference: <2.5 degrees; size difference: <1.5 mm) with the corresponding reference parameters manually identified in the original CT images by medical experts. In conclusion, the proposed method can improve the degree of automation of model-based hip replacement surgical systems.
下肢骨骼形态和形态计量学测量为计算机辅助矫形外科手术规划和干预、手术随访评估和个性化假体设计提供了重要且有用的信息。股骨头半径和中心、颈轴和大小、股骨偏移和骨干轴是近端股骨的形态和功能参数,在诊断和治疗中都有应用。从无任何操作人员监督或手动编辑的图像数据中获取这些信息仍然是一个实际目标,以避免手动分析中固有的可变性。在本文中,我们提出了一种启发式方法,通过处理股骨的网格表面自动计算近端股骨的形态参数。表面数据使用几何属性(如对称、不对称和主伸长方向)依次进行处理。数值方法确定股骨骨干的轴(最小二乘圆柱拟合)、头部表面和中心(最小二乘球拟合)以及股骨颈轴和半径(通过进化优化的最小截面面积)。该方法的重复性在 20 个从尸体 CT 扫描重建的股骨(10 个左侧+10 个右侧)表面上进行了测试。解剖学标志、角度、大小和轴的自动计算的重复性误差分别小于 1.5 毫米、2.5 度、1.0 毫米和 3.5 毫米。计算出的参数与医学专家在原始 CT 图像中手动识别的相应参考参数非常吻合(标志差异:<2.0 毫米;角度差异:<2.0 度;轴差异:<2.5 度;大小差异:<1.5 毫米)。总之,该方法可以提高基于模型的髋关节置换手术系统的自动化程度。