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Home / Equine Research Bank / PLoS One / Computed tomographic imaging of subchondral fatigue cracks i...
PloS one2014; 9(7); e101230; doi: 10.1371/journal.pone.0101230

Computed tomographic imaging of subchondral fatigue cracks in the distal end of the third metacarpal bone in the thoroughbred racehorse can predict crack micromotion in an ex-vivo model.

Abstract: Articular stress fracture arising from the distal end of the third metacarpal bone (MC3) is a common serious injury in Thoroughbred racehorses. Currently, there is no method for predicting fracture risk clinically. We describe an ex-vivo biomechanical model in which we measured subchondral crack micromotion under compressive loading that modeled high speed running. Using this model, we determined the relationship between subchondral crack dimensions measured using computed tomography (CT) and crack micromotion. Thoracic limbs from 40 Thoroughbred racehorses that had sustained a catastrophic injury were studied. Limbs were radiographed and examined using CT. Parasagittal subchondral fatigue crack dimensions were measured on CT images using image analysis software. MC3 bones with fatigue cracks were tested using five cycles of compressive loading at -7,500N (38 condyles, 18 horses). Crack motion was recorded using an extensometer. Mechanical testing was validated using bones with 3 mm and 5 mm deep parasagittal subchondral slots that modeled naturally occurring fatigue cracks. After testing, subchondral crack density was determined histologically. Creation of parasagittal subchondral slots induced significant micromotion during loading (p<0.001). In our biomechanical model, we found a significant positive correlation between extensometer micromotion and parasagittal crack area derived from reconstructed CT images (SR = 0.32, p<0.05). Correlations with transverse and frontal plane crack lengths were not significant. Histologic fatigue damage was not significantly correlated with crack dimensions determined by CT or extensometer micromotion. Bones with parasagittal crack area measurements above 30 mm2 may have a high risk of crack propagation and condylar fracture in vivo because of crack micromotion. In conclusion, our results suggest that CT could be used to quantify subchondral fatigue crack dimensions in racing Thoroughbred horses in-vivo to assess risk of condylar fracture. Horses with parasagittal crack arrays that exceed 30 mm2 may have a high risk for development of condylar fracture.
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Publication Date: 2014-07-31 PubMed ID: 25077477PubMed Central: PMC4117462DOI: 10.1371/journal.pone.0101230Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • Non-U.S. Gov't
  • Validation Study

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.

This research investigates the use of computed tomographic (CT) imaging for predicting fracture risks in thoroughbred racehorses. The researchers established a significant correlation between the dimensions of subchondral fatigue cracks, as captured by CT images, and micromotion of these cracks under high-speed running simulations.

Studying the Third Metacarpal Bone (MC3)

  • The study focuses on racing thoroughbreds’ third metacarpal bone — a common site for serious injury in these animals.
  • The researchers use an ex-vivo (external to the living organism) biomechanical model to simulate running conditions and monitor crack micromotion.
  • They collected limbs from 40 thoroughbred racehorses that suffered catastrophic injuries, then examined and radiographed them.

Measurement Techniques

  • The measurement of parasagittal subchondral fatigue crack dimensions was done through CT imaging and assisted by image analysis software.
  • The team applied five cycles of compressive loading to the MC3 bones at -7,500N, a state simulating running stress.
  • An extensometer, a device used to measure changes in object length, was employed to record crack motion.
  • Validation of mechanical testing was carried out through the creation of 3mm and 5mm deep parasagittal subchondral fatigue cracks, which mimic natural fatigue cracks.

Correlation between Extensometer Micromotion and Crack Area

  • They discovered a significant correlation between micromotion, recorded by an extensometer, and the parasagittal crack area as captured by CT imaging.
  • No significant correlations were found with transverse and frontal plane crack lengths.
  • Histological (the study of microscopic anatomy of cells) damage was not significantly correlated with crack dimensions or extensometer micromotion.
  • Horses with parasagittal crack area measurements exceeding 30 mm2 may be at high risk of incurring a condylar fracture due to crack micromotion.

Implications for Predicting Fracture Risk

  • The findings suggest that CT imaging can quantify subchondral fatigue crack dimensions in Thoroughbred racehorses, which could help assess the risk of condylar fractures.
  • If a horse’s parasagittal crack area exceeds 30 mm2, they may have a higher risk of developing such fractures, providing a possible measurement standard for preventive care.

Cite This Article

APA
Dubois MS, Morello S, Rayment K, Markel MD, Vanderby R, Kalscheur VL, Hao Z, McCabe RP, Marquis P, Muir P. (2014). Computed tomographic imaging of subchondral fatigue cracks in the distal end of the third metacarpal bone in the thoroughbred racehorse can predict crack micromotion in an ex-vivo model. PLoS One, 9(7), e101230. https://doi.org/10.1371/journal.pone.0101230

Publication

PloS one
ISSN: 1932-6203
NlmUniqueID: 101285081
Country: United States
Language: English
Volume: 9
Issue: 7
Pages: e101230
PII: e101230

Researcher Affiliations

Dubois, Marie-Soleil
  • Comparative Orthopaedic Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Morello, Samantha
  • Comparative Orthopaedic Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Rayment, Kelsey
  • Comparative Orthopaedic Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Markel, Mark D
  • Comparative Orthopaedic Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Vanderby, Ray
  • Department of Orthopedics & Rehabilitation, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Kalscheur, Vicki L
  • Comparative Orthopaedic Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Hao, Zhengling
  • Comparative Orthopaedic Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
McCabe, Ronald P
  • Department of Orthopedics & Rehabilitation, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Marquis, Patricia
  • Comparative Orthopaedic Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America; Gulfstream Park, Hallandale Beach, Florida, United States of America.
Muir, Peter
  • Comparative Orthopaedic Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

MeSH Terms

  • Animals
  • Fractures, Bone / diagnostic imaging
  • Fractures, Bone / physiopathology
  • Horses
  • In Vitro Techniques
  • Metacarpal Bones / diagnostic imaging
  • Metacarpal Bones / injuries
  • Metacarpal Bones / physiopathology
  • Motion
  • Stress, Physiological
  • Tomography, X-Ray Computed / methods

Conflict of Interest Statement

Please note that although Patricia Marquis is affiliated with the Gulfstream Park company in Florida, this does not alter the authors' adherence to PLOS ONE policies on sharing of data and materials.

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Citations

This article has been cited 7 times.
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