Boel F, de Vos-Jakobs S, Riedstra N S, Lindner C, Runhaar J, Bierma-Zeinstra S M A, Agricola R
Erasmus MC, Department of Orthopaedics and Sports Medicine, University Medical Center Rotterdam, Dr. Molewaterplein 40, 3015GD Rotterdam, the Netherlands.
The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Dr. Molewaterplein 40, 3015GD Rotterdam, the Netherlands.
Osteoarthr Imaging. 2024 Jun;4(2):100181. doi: 10.1016/j.ostima.2024.100181.
The aim of this study is to present a newly developed automated method to determine radiographic measurements of hip morphology on dual-energy x-ray absorptiometry (DXA) images. The secondary aim was to compare the performance of the automated and manual measurements.
30 DXA scans from 13-year-olds of the prospective population-based cohort study Generation R were randomly selected. The hip shape was outlined automatically using radiographic landmarks from which the acetabular depth-width ratio (ADR), acetabular index (AI), alpha angle (AA), Wiberg and lateral center edge angle (WCEA) (LCEA), extrusion index (EI), neck-shaft angle (NSA), and the triangular index (TI) were determined. Manual assessments were performed twice by two orthopedic surgeons. The agreement within and between observers and methods was visualized using Bland-Altman plots, and the reliability was studied using the intraclass correlation coefficient (ICC) with 95 % confidence intervals (CI).
The automated method was able to perform all radiographic hip morphology measurements. The intermethod reliability between the automated and manual measurements ranged from 0.57 to 0.96 and was comparable to or better than the manual interobserver reliability, except for the AI.
This open-access, automated method allows fast and reproducible calculation of radiographic measurements of hip morphology on right hip DXA images. It is a promising tool for performing automated radiographic measurements of hip morphology in large population studies and clinical practice.
本研究旨在介绍一种新开发的自动化方法,用于在双能X线吸收测定法(DXA)图像上确定髋关节形态的影像学测量值。次要目的是比较自动化测量和手动测量的性能。
从基于人群的前瞻性队列研究“R世代”中随机选择了30例13岁儿童的DXA扫描图像。利用影像学标志自动勾勒出髋关节形状,据此确定髋臼深度-宽度比(ADR)、髋臼指数(AI)、α角(AA)、维伯格角和外侧中心边缘角(WCEA)(LCEA)、挤压指数(EI)、颈干角(NSA)和三角形指数(TI)。由两名骨科医生进行两次手动评估。使用布兰德-奥特曼图直观显示观察者之间以及方法之间的一致性,并使用组内相关系数(ICC)及95%置信区间(CI)研究可靠性。
自动化方法能够完成所有髋关节形态的影像学测量。自动化测量和手动测量之间的方法间可靠性范围为0.57至0.96,除AI外,与手动观察者间可靠性相当或更好。
这种开放获取的自动化方法能够快速且可重复地计算右髋DXA图像上髋关节形态的影像学测量值。它是在大型人群研究和临床实践中进行髋关节形态自动化影像学测量的一种有前景的工具。