The finite element (FE) method is a cornerstone of patient-specific biomechanical analysis, yet most workflows assign isotropic linear elastic behaviour, and neglect bone's intrinsic anisotropic and non-linear response to load. We present PBMGA (Python-based Bone material grouping and anisotropy), a novel open-source tool that automates the calculation and element-specific assignment of non-linear and transversely isotropic (and, in principle, more general anisotropic) bone material parameters using user-defined equations. PBMGA integrates three customisable material grouping strategies: Percentual Thresholding, Adaptive Clustering, and Equidistant Grouping, to compress the number of unique material sets, significantly reducing computational complexity in downstream FE simulations without compromising accuracy. Its modular architecture supports seamless integration with existing preprocessing workflows and scalable analysis of large clinical datasets. By combining accurate material modelling with high-throughput capability, PBMGA enhances biomechanical prediction and paves the way for more efficient clinical diagnostics and treatment planning.
Strack et al. (2026) studied this question.