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脑瘫患者股骨骨形态自动测量的设计与验证

Design and validation of automated femoral bone morphology measurements in cerebral palsy.

作者信息

Park Noyeol, Lee Jehee, Sung Ki Hyuk, Park Moon Seok, Koo Seungbum

机构信息

Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea.

出版信息

J Digit Imaging. 2014 Apr;27(2):262-9. doi: 10.1007/s10278-013-9643-2.

Abstract

Accurate quantification of bone morphology is important for monitoring the progress of bony deformation in patients with cerebral palsy. The purpose of the study was to develop an automatic bone morphology measurement method using one or two radiographs. The study focused on four morphologic measurements-neck-shaft angle, femoral anteversion, shaft bowing angle, and neck length. Fifty-four three-dimensional (3D) geometrical femur models were generated from the computed tomography (CT) of cerebral palsy patients. Principal component analysis was performed on the combined data of geometrical femur models and manual measurements of the four morphologic measurements to generate a statistical femur model. The 3D-2D registration of the statistical femur model for radiography computes four morphological measurements of the femur in the radiographs automatically. The prediction performance was tested here by means of leave-one-out cross-validation and was quantified by the intraclass correlation coefficient (ICC) and by measuring the absolute differences between automatic prediction from two radiographs and manual measurements using original CT images. For the neck-shaft angle, femoral anteversion, shaft bowing angle, and neck length, the ICCs were 0.812, 0.960, 0.834, and 0.750, respectively, and the mean absolute differences were 2.52°, 2.85°, 0.92°, and 1.88 mm, respectively. Four important dimensions of the femur could be predicted from two views with very good agreement with manual measurements from CT and hip radiographs. The proposed method can help young patients avoid instances of large radiation exposure from CT, and their femoral deformities can be quantified robustly and effectively from one or two radiograph(s).

摘要

准确量化骨形态对于监测脑瘫患者骨变形的进展非常重要。本研究的目的是开发一种使用一张或两张X线片的自动骨形态测量方法。该研究聚焦于四项形态学测量——颈干角、股骨前倾角、骨干弯曲角和颈长度。从脑瘫患者的计算机断层扫描(CT)中生成了54个三维(3D)几何股骨模型。对几何股骨模型的组合数据和四项形态学测量的手动测量结果进行主成分分析,以生成一个统计股骨模型。统计股骨模型与X线片的3D-2D配准可自动计算X线片中股骨的四项形态学测量值。在此通过留一法交叉验证测试预测性能,并通过组内相关系数(ICC)以及测量两张X线片的自动预测值与使用原始CT图像的手动测量值之间的绝对差异进行量化。对于颈干角、股骨前倾角、骨干弯曲角和颈长度,ICC分别为0.812、0.960、0.834和0.750,平均绝对差异分别为2.52°、2.85°、0.92°和1.88毫米。股骨的四个重要维度可以从两个视图中预测出来,与CT和髋部X线片的手动测量结果非常吻合。所提出的方法可以帮助年轻患者避免因CT检查而受到大量辐射,并且可以从一张或两张X线片中稳健而有效地量化他们的股骨畸形。

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