A Probabilistic Method to Model Progressive Metatarsal Displacement and Stiffness During Fatigue Testing.

Area of Science:

• Biomechanics
• Computational modeling
• Materials science

Background:

• Bone stress injuries (BSI) are common, particularly in metatarsals, but their underlying fatigue mechanisms are not fully understood.
• Current methods for studying bone fatigue often rely on physical testing, which can be time-consuming and resource-intensive.

Purpose of the Study:

• To develop and validate an adaptive finite element (FE) algorithm capable of simulating fatigue displacements and progressive stiffness loss in metatarsals.
• To investigate the influence of microdamage accumulation parameters on bone fatigue behavior.

Main Methods:

• Generated specimen-specific FE models from CT scans of 22 human metatarsals.
• Developed a custom program to iteratively simulate cyclic loading, incorporating progressive stiffness loss via a Weibull distribution for microdamage accumulation.
• Validated simulation results against experimental data from uniaxial compression testing until failure.

Main Results:

• The adaptive FE simulations accurately replicated experimental trends in metatarsal stiffness and displacement changes during fatigue testing.
• Simulated displacement at failure closely matched experimentally measured values.
• Key parameters influencing fatigue life, displacement, and stiffness loss rate included the Weibull scatter variable (m) and critical strain value.

Conclusions:

• The developed adaptive simulation method provides a novel and accurate approach to understanding bone fatigue mechanisms and predicting BSI.
• This computational method can reduce reliance on physical testing, facilitate hypothesis generation regarding damage accumulation, and potentially be integrated into clinical predictive algorithms.