Healthy morphological variability in sagittal alignment modulates loading patterns in musculoskeletal spine modelling

Spinal sagittal alignment (SSA) is a primary determinant of spinal loading and stability. While biomechanical research frequently addresses major spinal deformities, the impact of healthy morphological variability remains underrepresented in musculoskeletal modelling, as conventional models typically assume a generic, “one-size-fits-all” curvature for non-deformed alignments. Using SSA4MSK tool, an open-source standalone Matlab application here introduced for the automatic integration of subject-specific SSA into OpenSim musculoskeletal models, this study quantifies the bias in spinal load estimation introduced by adopting a generic rather than subject-specific alignment. The analysis is conducted across the healthy morphological spectrum described by the Roussouly types (RT1–RT4) classification. The study also characterises how spinal load distribution differs across morphotypes along the thoracolumbar chain.Through a virtual cohort of 1586 models derived from 122 female subjects, models with generic alignment were found to introduce systematic bias in intervertebral joint compression of up to ±15%. For flat profiles (RT1), generic models underestimate compression by up to 80N, for hyperlordotic profiles (RT4), generic models overestimate compression with deviations scaling with upper body mass and sensitivity coefficients reaching 2N/kg. Conversely, generic models proved largely valid for intermediate morphotypes (RT2, RT3). Across RT1-RT4 the lumbar apex position substantially modulates anteroposterior shear forces, even at comparable global lordosis magnitudes, with inter-morphotype variations exceeding 0.24N per unit body weight at L1L2 and L3L4. These findings demonstrate that generic alignment does not adequately represent spinal load variability across the healthy alignment spectrum, particularly for flat and hyperlordotic profiles, and that SSA4MSK provides a robust framework to address this limitation. • SSA4MSK tool automates subject-specific spinal alignment into MSK Opensim models. • Generic spine profile shows 15% bias in compression vs. flat/hyper-curved spines. • Thoracolumbar junction is the most sensitive to healthy alignment variability. • Apex position modulates L1L2 and L3L4 shear by up to 0.24N/uBW at equal lordosis. • Mass-sensitivity in load estimations increases from flat to hyperlordotic spines.