Morphological human bone features and demography controlling damage accumulation and fracture: a finite element study

Abstract

Prediction of bone fracture risk is clinically challenging. Computational modeling plays a vital role in understanding bone structure and diagnosing bone diseases, leading to novel therapies. The research objectives were to demonstrate the anisotropic structure of the bone at the micro-level taking into consideration the density and subject demography, such as age, gender, body mass index (BMI), height, weight, and their roles in damage accumulation. Out of 438 developed 3D bone models at the micro-level, 46.12% were female. The age distribution ranged from 23 to 95 years. The research unfolds in two phases: micro-morphological features examination and stress distribution investigation. Models were developed using Mimics 22.0 and SolidWorks. The anisotropic material properties were defined before importing into Ansys for simulation. Computational simulations further uncovered variations in maximum von-Misses stress, highlighting that young Black males experienced the highest stress at 127.852 ± 10.035 MPa, while elderly Caucasian females exhibited the least stress at 97.224 ± 14.504 MPa. Furthermore, age-related variations in stress levels for both normal and osteoporotic bone micro models were elucidated, emphasizing the intricate interplay of demographic factors in bone biomechanics. Additionally, a prediction equation for bone density incorporating demographic variables was proposed, offering a personalized modeling approach. In general, this study, which carefully examines the complexities of how bones behave at the micro-level, emphasizes the need for an enhanced approach in orthopedics. We suggest taking individual characteristics into account to make therapeutic interventions more precise and effective.