An accuracy assessment of SlicerAutoscoperM - software for tracking skeletal structures in multi-plane videoradiography datasets.

Tracking skeletal joint kinematics in vivo with biplane videoradiography (BVR) can rigorously address a range of important questions in musculoskeletal research. Here we report on SlicerAutoscoperM (SAM), an upgrade of the markerless tracking software (Autoscoper) and its migration into the established computing environment of 3DSlicer and addition of a comprehensive pre-processing module to provide a standardized workflow. We present the accuracy and agreement in tracking four skeletal joints by four research groups. Accuracy was assessed by comparing marker-generated and SAM kinematics for bones of the foot, knee, shoulder, and wrist. Bland-Altman analyses quantified bias (mean error) and limits of agreement (LOA). Tracking accuracy was robust for all joints. In the foot, mean error (bias) was less than 0.5° (1.8°) and 0.8 mm (3.1 mm). In the knee, mean error was less than 1.0° (1.5°) and 0.4 mm (0.8 mm). In the shoulder, mean translational error for both the humerus and scapula was less than 0.2 mm (0.7 mm). Rotational error was highest in Roll and Pitch for the humerus, 1.9° (4.8°) and 1.7° (4.6°), respectively, and Yaw was 0.3° (2.1°). The scapula rotational bias was less than 0.2° (0.7°). In the wrist, the error was less than 0.05° (1.2°) and 0.5 mm (1.2 mm). Our data demonstrate that SAM is an accurate image-based skeletal motion tracking tool. With broad adoption, SAM will promote collaboration, simplify the harmonization of methods between study sites for large multi-center research studies, lower the entry bar for early-stage investigators, and facilitate translations toward clinical use.