In Silico Pelvis and Sacroiliac Joint Motion: Refining a Model of the Human Osteoligamentous Pelvis for Assessing Physiological Load Deformation Using an Inverted Validation Approach

Abstract

Introduction. Computational modeling of the human pelvis using the finite elements (FE) method has become increasingly important to understand the mechanisms of load distribution under both healthy and pathologically altered conditions and to develop and assess novel treatment strategies. The number of accurate and validated FE models is however small, and given models fail resembling the physiologic joint motion in particular of the sacroiliac joint. This study is aimed at using an inverted validation approach, using in vitro load deformation data to refine an existing FE model under the same mode of load application and to parametrically assess the influence of altered morphology and mechanical data on the kinematics of the model. Materials and Methods. An osteoligamentous FE model of the pelvis including the fifth lumbar vertebra was used, with highly accurate representations of ligament orientations. Material properties were altered parametrically for bone, cartilage, and ligaments, followed by changes in bone geometry (solid versus 3 and 2 mm shell) and material models (linear elastic, viscoelastic, and hyperelastic isotropic), and the effects of varying ligament fiber orientations were assessed. Results. Elastic modulus changes were more decisive in both linear elastic and viscoelastic bone, cartilage, and ligaments models, especially if shell geometries were used for the pelvic bones. Viscoelastic material properties gave more realistic results. Surprisingly little change was observed as a consequence of altering SIJ ligament orientations. Validation with in vitro experiments using cadavers showed close correlations for movements especially for 3 mm shell viscoelastic model. Discussion. This study has used an inverted validation approach to refine an existing FE model, to give realistic and accurate load deformation data of the osteoligamentous pelvis and showed which variation in the outcomes of the models are attributed to altered material properties and models. The given approach furthermore shows the value of accurate validation and of using the validation data to fine tune FE models.