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Comprehensive surface-based morphometry reveals the association of fracture risk and bone geometry.

Abstract: Surface-based morphometry method is advantageous in its objectivity and increased capability in detecting focal morphological changes, but has not been applied in bone-related research. Orthopedics research in human has confirmed the association of the bone geometry in proximal femur and its fracture. In this study, surface-based morphometry is used to test the hypothesis that there is relationship between bone geometry and fracture risk of the proximal sesamoid bone (PSB) in forelimbs of Thoroughbred racehorses. The PSB surfaces were extracted from CT images of nonfractured forelegs (i.e., right foreleg in this study) of 6 racehorses with fractures in the contralateral (i.e., left) foreleg, and the right forelegs of 6 matched controls. Significant differences were detected at the abaxial margin of the medial PSB base which was found to be up to 3.5 mm more prominent in the fracture-group compared to the control-group. This study demonstrated a successful application of computational morphometry in bone. The detected anatomical differences may lead to a larger moment arm generated via the medial branch of the suspensory apparatus, increasing pressure on the sesamoid surface, and thus potentially predisposing to fracture. Findings from this pilot study not only increase the likelihood of accurate PSB fracture risk assessment, but also shed light on investigating the influence of sports and exercise on human athletes.
Publication Date: 2012-01-17 PubMed ID: 22253193DOI: 10.1002/jor.22062Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • Non-U.S. Gov't

Summary

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The research article uses the surface-based morphometry method to investigate the relationship between bone geometry and fracture risk in the proximal sesamoid bone of Thoroughbred racehorses. The study found a significant difference in the bone geometry between horses with fractures and without, indicating that this method could potentially aid in fracture risk assessment.

Introduction and Methodology

  • The researchers implemented a surface-based morphometry method, a technique that boasts enhanced capabilities in detecting nuanced morphological changes, to assess bone geometry and fracture risk relationships.
  • Although this method has previously been used in orthopedics research in humans, it’s application in bone-related animal research is less common.
  • The study’s test subjects were Thoroughbred racehorses. Specifically, the team used CT images of 12 horses with fracture-free right forelegs: six that had fractures in their left foreleg and six control animals without fractures.

Results

  • The study found significant differences in the proximal sesamoid bone (PSB) surface between the fracture group and the control group.
  • The researchers discovered an area up to 3.5mm more prominent in the fracture group, located at the abaxial margin of the medial PSB base.
  • The findings demonstrated the successful application of surface-based morphometry in bone research and highlighted the considerable anatomical disparity that could predispose a horse to a fracture.

Implications

  • The results suggest that bone geometry could impact the pressure and tension on a bone, potentially increasing fracture risk.
  • This observation may be due to the larger moment arm generated via the medial branch, which could raise the pressure on the sesamoid surface further predisposing a horse to fracture.
  • The findings could enhance the accuracy of PSB fracture risk assessment and could be beneficial to veterinary medicine for diagnosing and treating equine patients.
  • Additionally, this work’s conclusions may also be helpful in assessing the influence of sports and exercise on human athletes, further diversifying its potential applications.

Cite This Article

APA
Wang D, Shi L, Griffith JF, Qin L, Yew DT, Riggs CM. (2012). Comprehensive surface-based morphometry reveals the association of fracture risk and bone geometry. J Orthop Res, 30(8), 1277-1284. https://doi.org/10.1002/jor.22062

Publication

ISSN: 1554-527X
NlmUniqueID: 8404726
Country: United States
Language: English
Volume: 30
Issue: 8
Pages: 1277-1284

Researcher Affiliations

Wang, Defeng
  • Department of Diagnostic Radiology and Organ Imaging, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.
Shi, Lin
    Griffith, James F
      Qin, Ling
        Yew, David T W
          Riggs, Christopher M

            MeSH Terms

            • Animals
            • Clinical Laboratory Techniques
            • Forelimb / diagnostic imaging
            • Fractures, Bone / diagnostic imaging
            • Fractures, Bone / veterinary
            • Horse Diseases / diagnostic imaging
            • Horses
            • Male
            • Pilot Projects
            • Radiography
            • Risk
            • Sesamoid Bones / anatomy & histology
            • Sports

            Citations

            This article has been cited 4 times.
            1. Noordwijk KJ, Chen L, Ruspi BD, Schurer S, Papa B, Fasanello DC, McDonough SP, Palmer SE, Porter IR, Basran PS, Donnelly E, Reesink HL. Metacarpophalangeal Joint Pathology and Bone Mineral Density Increase with Exercise but Not with Incidence of Proximal Sesamoid Bone Fracture in Thoroughbred Racehorses. Animals (Basel) 2023 Feb 24;13(5).
              doi: 10.3390/ani13050827pubmed: 36899684google scholar: lookup
            2. Basran PS, McDonough S, Palmer S, Reesink HL. Radiomics Modeling of Catastrophic Proximal Sesamoid Bone Fractures in Thoroughbred Racehorses Using μCT. Animals (Basel) 2022 Nov 4;12(21).
              doi: 10.3390/ani12213033pubmed: 36359157google scholar: lookup
            3. Adams J, Bhalodia R, Elhabian S. Uncertain-DeepSSM: From Images to Probabilistic Shape Models. Shape Med Imaging (2020) 2020 Oct;12474:57-72.
              doi: 10.1007/978-3-030-61056-2_5pubmed: 33817703google scholar: lookup
            4. Agrawal P, Mozingo JD, Elhabian SY, Anderson AE, Whitaker RT. Combined Estimation of Shape and Pose for Statistical Analysis of Articulating Joints. Shape Med Imaging (2020) 2020 Oct;12474:111-121.
              doi: 10.1007/978-3-030-61056-2_9pubmed: 33738463google scholar: lookup