Skin marker-based subject-specific spinal alignment modeling: A feasibility study

Abstract

Musculoskeletal models have the potential to improve diagnosis and optimize clinical treatment by predicting accurate outcomes on an individual basis. However, the subject-specific modeling of spinal alignment is often strongly simplified or is based on radiographic assessments, exposing subjects to unnecessary radiation. We therefore developed and introduced a novel skin marker-based approach for modeling subject-specific spinal alignment and evaluated its feasibility by comparing the predicted L1/L2 spinal loads during various functional activities with the loads predicted by the generically scaled models as well as with in vivo measured data obtained from the OrthoLoad database. Spinal loading simulations resulted in considerably higher compressive forces for both scaling approaches over all simulated activities, and AP shear forces that were closer or similar to the in vivo data for the subject-specific approach during upright standing activities and for the generic approach during activities that involved large flexions. These results underline the feasibility of the proposed method and associated workflow for inter- and intra-subject investigations using musculoskeletal simulations. When implemented into standard model scaling workflows, it is expected to improve the accuracy of muscle activity and joint loading simulations, which is crucial for investigations of treatment effects or pathology-dependent deviations.