Subject-Specific Finite Element Analysis of the Foot Using a Simplified Parametric Bone Model from Weight-Bearing Radiographs.

Abstract

Purpose: Analyzing foot biomechanics is essential for understanding plantar load distribution, particularly in relation to structural variations, including deformities such as flat foot and high arch, relative to the normal arch. Finite element analysis (FEA) is widely used to model foot biomechanics; however, traditional FEA approaches rely on detailed anatomical data from computed tomography (CT) scans, which are costly, expose subjects to radiation, and require substantial computational resources.

Methods: This proof-of-concept study presents a novel pipeline for generating a simplified, parametric 3D foot bone model from weight-bearing X-ray images in four views: lateral, dorsoplantar, anteroposterior, and hindfoot alignment. Image-derived bone lengths, angles, and offsets defined geometric primitives for constructing a personalized bone assembly, which was embedded into the subject's scanned foot surface and evaluated using FEA under static standing conditions. Plantar pressure served as the primary validation metric, comparing results from the simplified model with experimental measurements and a CT-based model.

Results: The simplified model reproduced the experimental plantar pressure pattern with relative errors of 4.38, 8.33, and 3.66% in the hindfoot, midfoot, and forefoot, respectively, while reducing computation time by approximately 90%. A supplementary evaluation across four additional subjects with various foot conditions showed consistent performance, with less than 9% deviation in regional peak pressure compared with experimental measurements.

Conclusion: These findings demonstrate the feasibility of X-ray-based parametric modeling as a lightweight and scalable alternative for personalized foot analysis, with potential applications in rapid orthotic and insole design, subject-specific assessment in low-resource settings, and large-scale biomechanical screening.