Comparison of Two Different Finite Element Modeling Pipelines for Virtual Mechanical Testing of The Distal Third Metacarpal Bone In Thoroughbred Racehorses.

Overview

• This study compares two finite element analysis (FEA) modeling methods for predicting bone strain in a specific horse bone to help identify racehorses at risk of fractures.
• The goal was to evaluate whether a simpler, faster modeling approach could produce results comparable to a more complex, detailed method.

Background

• Condyle fractures in the third metacarpal bone (MC3) are common and severe injuries in Thoroughbred racehorses.
• Currently, identifying horses at risk is subjective and lacks objective measurement tools.
• Standing computed tomography (sCT) offers a non-invasive way to capture detailed images of the distal MC3 bone in live horses.
• Using sCT data, patient-specific finite element analysis (FEA) can simulate mechanical behavior and predict subchondral bone strain, potentially an objective marker for fracture risk.

Objectives of the Study

• Compare two independently developed FEA pipelines based on sCT imaging:

• UWMSN Pipeline: Models the full 3D distal MC3 bone.
• UMELB Pipeline: Uses simpler 2D modeling from single sCT slices.

Methods

• Four MC3 condyles from four different Thoroughbred racehorses were selected.
• Each condyle was modeled using both FEA pipelines.
• Predicted subchondral strains from the two pipelines were compared and analyzed.

Results

• The UMELB pipeline predicted lower subchondral bone strain compared to the UWMSN pipeline.
• The difference is likely due to UMELB’s simpler modeling approach, which limits the modes of deformation it can capture.
• The UWMSN pipeline successfully identified horses with higher subchondral strain and potentially higher fatigue damage.
• The UWMSN approach, while more accurate, requires significantly more computational resources and processing time.

Conclusions and Implications

• The detailed 3D UWMSN modeling approach is accurate and capable of distinguishing horses at high risk due to elevated bone strain, but is resource-intensive.
• The simpler UMELB pipeline, though less precise, shows promise as a faster, less laborious method.
• With further refinement and clinical validation, UMELB could serve as an efficient screening tool for assessing fracture risk in racehorses based on subchondral strain predictions.
• This research supports the potential to improve objective evaluation of fracture risk in racehorses using patient-specific imaging and modeling techniques.