Understanding spine biomechanics is essential for maintaining posture under static and dynamic conditions, relying on a balance of muscular and gravitational forces. Computational musculoskeletal (MSK) models are increasingly being used in biomechanical research as non-invasive alternatives to in vivo and in vitro methods. Two main MSK modeling strategies are multibody (MB) models, which simplify the spine using rigid vertebrae and intervertebral joints to study muscle recruitment, and finite element (FE) models, which provide detailed tissue representation but often rely on oversimplified loading conditions. Recently, coupled (C) models integrating MB and FE approaches have emerged, though they face technical integration challenges. This literature review examines thoracolumbar MSK modeling methods-MB, FE, and C-to outline current practices, evaluate model capabilities, and inform future research and development. Most reviewed models have been published since 2016, reflecting the growing interest and advances in computational spine biomechanics. While certain modeling choices (e.g., the representation of body weight) are consistent across studies, considerable variability remains in other aspects (e.g., the depiction of muscular architecture, including the selection of muscle groups and the number of fascicles used). Despite being critical for model credibility, validation is often constrained by the limited availability of experimental data. Finally, the review highlights emerging directions such as modeling more complex functional tasks, personalizing anatomical and mechanical properties, and promoting Open Science to enhance reproducibility and collaboration in the field.
Carpenedo et al. (Fri,) studied this question.