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Equine veterinary journal2017; 49(5); 681-687; doi: 10.1111/evj.12672

Modelling the effect of race surface and racehorse limb parameters on in silico fetlock motion and propensity for injury.

Abstract: The metacarpophalangeal joint (fetlock) is the most commonly affected site of racehorse injury, with multiple observed pathologies consistent with extreme fetlock dorsiflexion. Race surface mechanics affect musculoskeletal structure loading and injury risk because surface forces applied to the hoof affect limb motions. Race surface mechanics are a function of controllable factors. Thus, race surface design has the potential to reduce the incidence of musculoskeletal injury through modulation of limb motions. However, the relationship between race surface mechanics and racehorse limb motions is unknown. Objective: To determine the effect of changing race surface and racehorse limb model parameters on distal limb motions. Methods: Sensitivity analysis of in silico fetlock motion to changes in race surface and racehorse limb parameters using a validated, integrated racehorse and race surface computational model. Methods: Fetlock motions were determined during gallop stance from simulations on virtual surfaces with differing average vertical stiffness, upper layer (e.g. cushion) depth and linear stiffness, horizontal friction, tendon and ligament mechanics, as well as fetlock position at heel strike. Results: Upper layer depth produced the greatest change in fetlock motion, with lesser depths yielding greater fetlock dorsiflexion. Lesser fetlock changes were observed for changes in lower layer (e.g. base or pad) mechanics (nonlinear), as well as palmar ligament and tendon stiffness. Horizontal friction and fetlock position contributed less than 1° change in fetlock motion. Conclusions: Simulated fetlock motions are specific to one horse's anatomy reflected in the computational model. Anatomical differences among horses may affect the magnitude of limb flexion, but will likely have similar limb motion responses to varied surface mechanics. Conclusions: Race surface parameters affected by maintenance produced greater changes in fetlock motion than other parameters studied. Simulations can provide evidence to inform race surface design and management to reduce the incidence of injury.
Publication Date: 2017-03-09 PubMed ID: 28128865DOI: 10.1111/evj.12672Google Scholar: Lookup
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  • Journal Article

Summary

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The research article presents a computational model to analyze the impact of racehorse surface and limb characteristics on the movement of the metacarpophalangeal joint (fetlock) and the risk for injury. The model identifies surface layer depth as the primary factor influencing the range of fetlock motion, a key driver of common racehorse injuries.

Understanding the Research

  • This research focuses on understanding the potential risks to a racehorse’s metacarpophalangeal joint, commonly referred to as the fetlock, which is the most frequent site of injury in racehorses. These injuries are often associated with extreme dorsiflexion, or backward bending, of the fetlock.
  • One of the major factors contributing to these injuries is the mechanics of the race surface which the horse runs on as it influences the forces exerted on the horse’s limbs and how those limbs move in response.
  • The researchers endeavored to determine how changes in race surface and the horse’s limb parameters can affect the movement of the lower limb region. To achieve this, they used a computational model of both a racehorse and the race surface.

Research Methodology

  • A sensitivity analysis was conducted to see how changes in different parameters like the average vertical stiffness of the surface, depth and linear stiffness of the upper layer (cushion), horizontal friction, and the mechanics of ligaments and tendons affect the fetlock motions during galloping.
  • The position of the fetlock at the time of heel strike was also considered as a parameter in the simulations.

Research Findings

  • The most significant change in fetlock motion was due to the depth of the upper layer of the racing surface- shallow depths resulted in greater dorsiflexion of the fetlock.
  • Changes in other parameters like the mechanics of the lower surface layer (e.g., base or pad) and the stiffness of ligaments and tendons in the palmar region resulted in less significant changes in the movement of the fetlock.
  • Horizontal friction and the position of the fetlock at heel strike had negligible effects on the fetlock motion (<1° change).

Conclusions and Implications

  • While the study reflects the physiology of one horse, anatomical differences among horses may lead to variations in the degree of limb flexion, but they would likely respond similarly to changes in surface mechanics.
  • The research indicates that the parameters of the race surface that can be altered through maintenance have a greater impact on fetlock motion than other studied factors.
  • This finding suggests that careful management of race surface design, especially the depth of the upper layer, could potentially reduce the incidence of injuries.

Cite This Article

APA
Symons JE, Hawkins DA, Fyhrie DP, Upadhyaya SK, Stover SM. (2017). Modelling the effect of race surface and racehorse limb parameters on in silico fetlock motion and propensity for injury. Equine Vet J, 49(5), 681-687. https://doi.org/10.1111/evj.12672

Publication

ISSN: 2042-3306
NlmUniqueID: 0173320
Country: United States
Language: English
Volume: 49
Issue: 5
Pages: 681-687

Researcher Affiliations

Symons, J E
  • Biomedical Engineering Graduate Group, University of California - Davis, Davis, California, USA.
  • Department of Anatomy, Physiology and Cell Biology, University of California - Davis School of Veterinary Medicine, Davis, California, USA.
Hawkins, D A
  • Biomedical Engineering Graduate Group, University of California - Davis, Davis, California, USA.
  • Department of Neurobiology, Physiology and Behavior, University of California - Davis, Davis, California, USA.
Fyhrie, D P
  • Biomedical Engineering Graduate Group, University of California - Davis, Davis, California, USA.
  • Department of Orthopaedic Surgery, University of California - Davis Medical Center Sacramento, Davis, California, USA.
Upadhyaya, S K
  • Department of Biological and Agricultural Engineering, University of California - Davis, Davis, California, USA.
Stover, S M
  • Biomedical Engineering Graduate Group, University of California - Davis, Davis, California, USA.
  • Department of Anatomy, Physiology and Cell Biology, University of California - Davis School of Veterinary Medicine, Davis, California, USA.

MeSH Terms

  • Animals
  • Biomechanical Phenomena
  • Computer Simulation
  • Extremities
  • Gait / physiology
  • Hoof and Claw / physiology
  • Horses / physiology
  • Metacarpophalangeal Joint / injuries
  • Metacarpophalangeal Joint / physiology
  • Physical Conditioning, Animal / physiology
  • Range of Motion, Articular
  • Risk Factors
  • Running

Citations

This article has been cited 3 times.
  1. Demuth OE, Herbst E, Polet DT, Wiseman ALA, Hutchinson JR. Modern three-dimensional digital methods for studying locomotor biomechanics in tetrapods.. J Exp Biol 2023 Apr 25;226(Suppl_1).
    doi: 10.1242/jeb.245132pubmed: 36810943google scholar: lookup
  2. Pechette Markley A, Shoben AB, Kieves NR. Internet Survey of Risk Factors Associated With Training and Competition in Dogs Competing in Agility Competitions.. Front Vet Sci 2021;8:791617.
    doi: 10.3389/fvets.2021.791617pubmed: 35059455google scholar: lookup
  3. Crawford KL, Finnane A, Greer RM, Phillips CJC, Woldeyohannes SM, Perkins NR, Ahern BJ. Appraising the Welfare of Thoroughbred Racehorses in Training in Queensland, Australia: The Incidence and Type of Musculoskeletal Injuries Vary between Two-Year-Old and Older Thoroughbred Racehorses.. Animals (Basel) 2020 Nov 5;10(11).
    doi: 10.3390/ani10112046pubmed: 33167429google scholar: lookup