Correspondence model-based approach for evaluating static and dynamic joint distance measurements.

Abstract

Evaluations of 3D joint space measurements between study groups have traditionally relied on surface regional divisions, which attenuate the impact of shape on joint measurements. Advancements in morphometric analyses have enabled evaluation of population-based shape variations as they relate to disease progression and deformity. Specifically, correspondence model-based shape analyses offer co-registered landmarks that address shape variability in joint structures and can be utilized for comparison of joint space measurements. This study proposes a method using correspondence models to perform group-wise statistical analyses in static or quasi-static positions during movement, offering a more comprehensive assessment of joint space variability. The primary objective was to verify and validate the measurement methods of a developed open-source toolbox. Testing was performed with surface meshes of varying edge length (0.5-, 1-, and 2-mm) and with different expected joint space distances (1- and 4-mm). Validation testing of accuracy revealed <1% error for 0.5- and 1-mm mesh edge lengths for 4 mm joint space, sensitivity testing demonstrated best results for 0.5 mm edge length, and repeatable/reliable measurements yielded low coefficient of variation and high intraclass correlation coefficient. These findings support the use of correspondence model-based approaches for robust and accurate analysis of joint measurements related to anatomical features. This method addresses limitations in traditional techniques by incorporating shape variability, providing a practical tool for assessing joint-level disease and deformity. Future work will focus on evaluating the application of this approach in diverse clinical scenarios, including highly deformed joint structures.