A mechanostatistical approach to cortical bone remodelling: an equine model.

The study presents a mechanostatistical model to understand the remodelling process of cortical bone (hard outer surface bone), using data from live horses. The focus was on exploring the relationship between mechanical stress and bone growth, and translating these findings for human applications.

Equine Model

• This study employs an equine model due to the anatomical similarities between horse and human Haversian systems. This structure, also known as the Osteon, is the fundamental functional unit in many bones, including that of humans.
• Equine models, particularly their third metacarpal bone, offer availability of live bone strain and biomarker data. This is valuable for investigating bone responses to mechanical stresses.
• Equine models are also endorsed by the US Federal Drugs Administration for comparative joint research, emphasizing the relevance of this model to human conditions.

Methodology & Results

• The researchers utilized micro-computed tomography imaged specimens from the equine third metacarpal bone. The images allowed them to measure and model the intricate structures within the bone.
• The study uses the Frost-based ‘mechanostat’, a concept that describes how mechanical forces dictate bone growth and remodeling. This information was combined with live strain gauges and biomarkers from the horses to estimate bone growth rates.
• The team gave a description of the ‘cutting cone’ phenomenon – where Haversian canals create tunnels and replace bone – as part of their modeling.
• The scientists developed a partial least squares regression (PLSR) surrogate model from training data. These data were gathered from finite element simulations with variable loads. Finite element simulations are a common computational method to model stress patterns in rigid structures.
• The PLSR model demonstrated high accuracy in predicting bone microstructure and the homogenised Young’s modulus (a measure of stiffness of an elastic material). The error percentages were less than 2.2% and 0.6% respectively.

Implication

• The creation of this model provides valuable insights into bone remodeling, which is essential for understanding bone health, bone diseases or conditions, and the development of potential treatments or preventive measures.
• By accurately predicting changes in bone structure and mechanical properties, the findings from this study could provide a basis for more detailed examinations of bone diseases like osteoporosis or aid in the development of orthopedic solutions.