Scoliosis Induction in the Porcine Spine Using a Growth-Modulating Posterior Tether: Finite Element Model Development and Calibration

Abstract Purpose Predictable correction of early onset scoliosis through mechanical modulation of endochondral growth requires understanding vertebral stress–growth relationships. Here, we develop image-based finite element models (FEMs) to estimate vertebral stress–growth relationships under prescribed loading conditions using a porcine model of spine deformity induced mechanically via a posterolateral tether, assuming that, after initial tether-induced elastic deformation, subsequent deformity develops solely from vertebral endochondral growth against the tether and elastic anatomical structures. Methods Image-based FEMs were generated to simulate juvenile Yorkshire pigs instrumented with a posterolateral tether implant which applied asymmetric force across the spine. FEM growth parameters were calibrated to best match in vivo data using landmark points obtained from 3D imaging for each pig. Results Asymmetric stresses generated by loading of the posterolateral offset cable produced multi-planar spine deformity. Calibrated FEMs achieved moderate agreement with frontal plane projections of the deformity: Cobb angle (MAE = 4.6–8.5° across all pigs and timepoints) and anatomic landmark point correspondence (MAE = 2.1–2.9 mm), but sagittal plane agreement was more limited, partly attributable to variability in positioning during imaging. FEM-derived vertebral body growth rates were reduced for vertebrae along the concavity of the deformity. Conclusion Image-based FEMs estimated vertebral stress–growth relationships and reproduced deformity with comparable Cobb angle error to an existing parametric FE model (current 2.5 ± 1.6° vs. reported ~ 2.0 ± 2.4° in a single-pig matched comparison) with realistic baseline IVD stresses (current ~ 0.45 MPa vs. reported 0.48 MPa in the growth plate). With expanded validation, such models may support preclinical evaluation of implant designs and surgical configurations prior to in vivo testing.