Subject-specific biomechanics of trunk: musculoskeletal scaling, internal loads and intradiscal pressure estimation

Abstract

Development of a subject-specific computational musculoskeletal trunk model (accounting for age, sex, body weight and body height), estimation of muscle forces and internal loads as well as subsequent validation by comparison with measured intradiscal pressure in various lifting tasks are novel, important and challenging. The objective of the present study is twofold. First, it aims to update and personalize the passive and active structures in an existing musculoskeletal kinematics-driven finite element model. The scaling scheme used an existing imaging database and biomechanical principles to adjust muscle geometries/cross-sectional-areas and passive joint geometry/properties in accordance with subjects' sex, age, body weight and body height. Second, using predictions of a detailed passive finite element model of the ligamentous lumbar spine, a novel nonlinear regression equation was proposed that relates the intradiscal pressure (IDP) at the L4-L5 disc to its compression force and intersegmental flexion rotation. Predicted IDPs and muscle activities of the personalized models under various tasks are found in good-to-excellent agreement with reported measurements. Results indicate the importance of personal parameters when computing muscle forces and spinal loads especially at larger trunk flexion angles as minor changes in individual parameters yielded up to 30 % differences in spinal forces. For more accurate subject-specific estimation of spinal loads and muscle activities, such a comprehensive trunk model should be used that accounts for subject's personalized features on active musculature and passive spinal structure.

Effects of sex, age, body height and body weight on spinal loads: Sensitivity analyses in a subject-specific trunk musculoskeletal model

“…The development and validation of a nonlinear FE, subject-specific, musculoskeletal model of the trunk for symmetric-asymmetric tasks are reported elsewhere (Ghezelbash et al, 2016).…”

“…To estimate muscle forces, the musculoskeletal trunk model is driven by measured kinematics while minimizing sum of squared muscle stresses (Arjmand et al, 2010;. Moreover, to adjust the model in accordance with subject's personal parameters (age, sex, BH and BW), we use a physiological-based scaling method that modifies both muscle architecture (geometry and area of muscles) and passive joint properties in accordance with imaging studies Shi et al, 2014) and biomechanical principles (Ghezelbash et al, 2016).…”

“…Thoracolumbar (T11-S1) rotations in each task are partitioned between its motion segments; 6.0% at the T11-T12, 10.9% at the T12-L1, 14.1% at the L1-L2, 13.2% at the L2-L3, 16.9% at the L3-L4, 20.1% at the L4-L5, and finally 18.7% at the L5-S1 (Gercek et al, 2008;Ghezelbash et al, 2016;Hajibozorgi and Arjmand, 2015).…”

“…Shortcomings: Apart from limited in vivo studies available for validation (Dreischarf et al, 2016) and the limitations (e.g., neglecting intra-abdominal pressure and coactivity) noted elsewhere El-Rich et al, 2004;Ghezelbash et al, 2015;Ghezelbash et al, 2016), the model did not converge in taller, older, obese and female individuals with load in hands (≥5 kg) at large flexion angles (≥70 o ) since in contrast to spinal loads, the contribution of BH to the required moments is not negligible, and muscles in females could not counterbalance the induced required moments. In accordance with the input data used Pries et al, 2015;Shi et al, 2014) and to avoid spinal disorders observed at older ages, we chose the range of 35-60 years that also covers active working ages.…”

“…To adequately account for the overweight and obese individuals, we initially develop a novel technique to estimate segmental weight distribution along the trunk (T1 to L5) as BW alters. Moreover, using an updated validated nonlinear finite element (FE) subjectspecific trunk musculoskeletal model (Ghezelbash et al, 2016) in conjunction with personalized spinal kinematics (with respect to age and sex) (Pries et al, 2015), we evaluate spinal loads and sensitivities therein as individual parameters alter in a full factorial simulation (90 cases) taking 4 independent factors (age, sex, BH and BW) in five sagittally symmetric tasks. In accordance with earlier studies, we hypothesize that spinal loads are much more sensitive to variations in BW than in sex, BH and age.…”