Effects of Using Generic vs. Subject-Specific Muscle Properties on Spinal Load Prediction Across Different Posture Simulations.

Abstract

Subject-specific musculoskeletal models hold promise for adult spinal deformity management. However, fully subject-specific models require subject-specific soft-tissue properties not typically available in clinical settings. Models created using generic properties are more accessible but potentially less accurate. The objective of this study was to identify which biomechanical properties of muscle function, and in which specific body positions, exhibit significant differences when implementing generic versus subject-specific properties. Using OpenSim, we analyzed 250 subject-specific models, focusing on four muscle parameters: geometry-path, maximum-isometric-force, optimal-fiber-length, and tendon-slack-length across 11 postures, encompassing standing and flexed postures. A linear mixed-effects model evaluated the impact of muscle parameters on spinal compression loads. Differences in compression load between the models with subject-specific and generic data were compared statistically using non-parametric methods. Subject-specific geometry-path and maximum-isometric-force significantly influenced spinal compression loads, with mean differences of 13 % and 8 %, respectively. Differences were posture-dependent (geometry-path p < 0.001; max-isometric-force p = 0.005). Optimal-fiber-length (p = 0.053) and tendon-slack-length (p = 0.680) showed minimal impact (∼1% difference). Flexed postures were more sensitive to generic muscle parameters, with mean differences of 17 % (geometry-path) and 6 % (max-isometric-force), compared to standing (6 % and 4 %, respectively). The pronounced deviations observed in flexion simulations emphasized the necessity of subject-specific data in such simulations. However, when subject-specific data is not available, simulations based on standing postures are the least affected by the use of generic properties.