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Scientific reports2025; 16(1); 1166; doi: 10.1038/s41598-025-30921-6

Standing CT-based finite element models efficiently identify regions of high mechanical strain in equine metacarpal subchondral bone.

Abstract: Stress fractures are common in racehorses, with the metacarpophalangeal (MCP) joint being the most frequently affected site as it is subjected to high-magnitude and high-rate cyclic loads during training and racing. These loads lead to repeated compressive stresses, resulting in subchondral bone (SCB) sclerosis, fatigue microcracks, and matrix damage that can progress to parasagittal fractures or palmar osteochondral disease (POD). The present study developed joint-specific 3D FE models and slice-based FE models using standing CT images for three trained racehorses, each presenting distinct SCB conditions common in racehorses as identified by their CT images: (1) biaxial sclerotic condylar SCB with no visible lesions: BS, (2) focal lytic SCB with associated sclerosis in the PSG: LGL, and (3) focal lytic SCB with associated sclerosis in the condyles: BCL. Both models predicted similar overall patterns of SCB stress and strain, identifying peak tensile and compressive strains in the PSGs and condyles, while minimal strains were observed over the sagittal ridge. The 3D models predicted a larger volume of highly strained bone compared to slice-based models, particularly in the horse with biaxial sclerosis. Both 3D and slice-based FE models demonstrated strong agreement in identifying the PSG and midcondyles as high-strain regions. The sensitivity analysis showed that variations in input parameters had minimal impact on the results, indicating the robustness of slice-based models. Despite being less detailed, slice-based models were much faster and more straightforward to develop and provided stress and strain patterns comparable to 3D models. These findings suggest that slice-based models offer a valuable tool for rapid assessment of biomechanical behaviour in equine fetlock joints, particularly for identifying regions at high-risk of failure in the clinical setting.
© 2025. The Author(s).
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Publication Date: 2025-12-11 PubMed ID: 41381693PubMed Central: PMC12789503DOI: 10.1038/s41598-025-30921-6Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

Overview

  • This study developed and compared 3D and slice-based finite element (FE) models from standing CT images to identify areas of high mechanical strain in the subchondral bone of equine metacarpal joints.
  • The goal was to determine if quicker, less complex slice-based models could effectively detect high-strain regions linked to stress fractures and bone damage in racehorses, which experience heavy joint loading.

Background and Rationale

  • Racehorses often suffer stress fractures, particularly in the metacarpophalangeal (MCP) joint, due to repetitive large and rapid loads during training and racing.
  • The MCP joint is vulnerable because the high-magnitude cyclic loading causes compressive stresses in the subchondral bone (SCB), leading to sclerosis (hardening), microcracks, and eventually larger bone lesions or fractures.
  • Understanding which regions within the SCB are subjected to high strain is important for predicting injury risk and managing equine athlete health.
  • Finite element (FE) modeling is a computational technique that can estimate internal bone stresses and strains from imaging data, helping identify these high-risk regions.
  • Traditional 3D FE models are detailed but time-consuming to build and analyze, while slice-based FE models simplify the structure into sectional slices, which is faster and easier.

Study Design and Methods

  • The researchers used standing CT scans of the MCP joints from three trained racehorses, each displaying different SCB pathologies commonly seen in racehorses:
    • Horse 1: Biaxial sclerotic condylar SCB without visible lesions (BS).
    • Horse 2: Focal lytic SCB with associated sclerosis in the parasagittal groove (PSG) (LGL).
    • Horse 3: Focal lytic SCB with associated sclerosis in the condyles (BCL).
  • They developed two types of FE models from the CT images for each horse:
    • Joint-specific full 3D FE models capturing the detailed geometry of the MCP joint.
    • Slice-based FE models focusing on sectional slices through the bone.
  • The models estimated patterns of stress and strain within the SCB under loading conditions representative of the standing joint.
  • A sensitivity analysis tested the influence of variations in input parameters on model results to assess robustness.

Key Findings

  • Both 3D and slice-based models predicted similar overall spatial patterns of stress and strain:
    • Peak tensile and compressive strains were consistently located in the parasagittal grooves (PSGs) and condyles.
    • The sagittal ridge showed minimal strains in all models and cases.
  • The 3D models predicted a greater volume of highly strained bone, especially in the horse with biaxial sclerosis, indicating more detailed stress distribution representation.
  • Strong agreement existed between the two modeling approaches in pinpointing the PSG and midcondyles as regions of high mechanical strain, which are clinically relevant locations for stress fracture development.
  • The sensitivity analysis demonstrated that reasonable variations in input parameters minimally affected strain predictions, indicating that slice-based models are robust despite their simplifications.
  • Slice-based FE models were much faster and easier to develop compared to full 3D models, yet provided comparable stress-strain pattern insights relevant for clinical evaluation.

Implications and Conclusion

  • Slice-based FE models from standing CT scans offer a practical and efficient tool for rapid biomechanical assessment of equine MCP joints, helping identify regions at high risk of failure.
  • This approach could support clinicians in monitoring racehorses for early signs of stress-related bone damage, potentially allowing for quicker intervention to prevent severe fractures.
  • While 3D FE models provide more detailed volumetric information, slice-based models balance accuracy and resource demands, making them suitable for clinical settings where speed and simplicity are valuable.
  • Future work might refine slice-based models further or integrate both modeling strategies to optimize diagnosis and treatment planning in equine sports medicine.

Cite This Article

APA
Malekipour F, Whitton RC, Muir P, Lee PV. (2025). Standing CT-based finite element models efficiently identify regions of high mechanical strain in equine metacarpal subchondral bone. Sci Rep, 16(1), 1166. https://doi.org/10.1038/s41598-025-30921-6

Publication

Scientific reports
ISSN: 2045-2322
NlmUniqueID: 101563288
Country: England
Language: English
Volume: 16
Issue: 1
Pages: 1166
PII: 1166

Researcher Affiliations

Malekipour, Fatemeh
  • Department of Biomedical Engineering, University of Melbourne, Parkville, VIC, 3010, Australia.
Whitton, R Chris
  • Equine Centre, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Werribee, VIC, 3030, Australia.
Muir, Peter
  • Department of Surgical Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, USA.
Lee, Peter Vee-Sin
  • Department of Biomedical Engineering, University of Melbourne, Parkville, VIC, 3010, Australia. pvlee@unimelb.edu.au.

MeSH Terms

  • Horses
  • Animals
  • Metacarpal Bones / diagnostic imaging
  • Finite Element Analysis
  • Stress, Mechanical
  • Tomography, X-Ray Computed / methods
  • Metacarpophalangeal Joint / diagnostic imaging
  • Biomechanical Phenomena
  • Fractures, Stress / diagnostic imaging
  • Fractures, Stress / veterinary
  • Horse Diseases / diagnostic imaging

Conflict of Interest Statement

Declarations. Competing interests: Peter Muir is a Founder of Asto CT, a subsidiary of Centaur Health Holdings Inc. and the founder of Eclipse Consulting LLC.

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