Relationship between CT-Derived Bone Mineral Density and UTE-MR-Derived Porosity Index in Equine Third Metacarpal and Metatarsal Bones.

BMD CT MRI PI equine fatigue injury lateral condylar fracture palmar osteochondral disease stress fracture ultra-short echo time

Journal

Animals : an open access journal from MDPI
ISSN: 2076-2615
Titre abrégé: Animals (Basel)
Pays: Switzerland
ID NLM: 101635614

Informations de publication

Date de publication:
31 Aug 2023
Historique:
received: 31 07 2023
revised: 28 08 2023
accepted: 29 08 2023
medline: 9 9 2023
pubmed: 9 9 2023
entrez: 9 9 2023
Statut: epublish

Résumé

Fatigue-related subchondral bone injuries of the third metacarpal/metatarsal (McIII/MtIII) bones are common causes of wastage, and they are welfare concerns in racehorses. A better understanding of bone health and strength would improve animal welfare and be of benefit for the racing industry. The porosity index (PI) is an indirect measure of osseous pore size and number in bones, and it is therefore an interesting indicator of bone strength. MRI of compact bone using traditional methods, even with short echo times, fail to generate enough signal to assess bone architecture as water protons are tightly bound. Ultra-short echo time (UTE) sequences aim to increase the amount of signal detected in equine McIII/MtIII condyles. Cadaver specimens were imaged using a novel dual-echo UTE MRI technique, and PI was calculated and validated against quantitative CT-derived bone mineral density (BMD) measures. BMD and PI are inversely correlated in equine distal Mc/MtIII bone, with a weak mean r value of -0.29. There is a statistically significant difference in r values between the forelimbs and hindlimbs. Further work is needed to assess how correlation patterns behave in different areas of bone and to evaluate PI in horses with and without clinically relevant stress injuries.

Identifiants

pubmed: 37685045
pii: ani13172780
doi: 10.3390/ani13172780
pmc: PMC10487176
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Horserace Betting Levy Board
ID : VET/CS/028
Organisme : Siemens Healthcare Ltd
ID : IPA 42

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Auteurs

Carola Riccarda Daniel (CR)

Royal (Dick) School of Veterinary Studies, The Roslin Institute, The University of Edinburgh, Edinburgh EH25 9RG, UK.

Sarah Elizabeth Taylor (SE)

Royal (Dick) School of Veterinary Studies, The Roslin Institute, The University of Edinburgh, Edinburgh EH25 9RG, UK.

Samuel McPhee (S)

Institute of Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, UK.

Uwe Wolfram (U)

Institute of Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, UK.

Tobias Schwarz (T)

Royal (Dick) School of Veterinary Studies, The Roslin Institute, The University of Edinburgh, Edinburgh EH25 9RG, UK.

Stefan Sommer (S)

Siemens Healthcare, 8047 Zurich, Switzerland.
Swiss Center for Musculoskeletal Imaging (SCMI), Balgrist Campus, 8008 Zurich, Switzerland.
Advanced Clinical Imaging Technology (ACIT), Siemens Healthcare AG, 1015 Lausanne, Switzerland.

Lucy E Kershaw (LE)

Centre for Cardiovascular Sciences and Edinburgh Imaging, The University of Edinburgh, Edinburgh EH16 4TJ, UK.

Classifications MeSH