ArticleVeterinary record open2023
Approaches to standardising the magnetic resonance image analysis of equine tendon lesions.
Article in Veterinary record open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Magnetic resonance imaging for diagnosing and managing deep digital flexor tendinopathy in equine athletes: Insights, advances and future directions.Equine veterinary journal · 2025Review
- Equine Musculoskeletal Pathologies: Clinical Approaches and Therapeutical Perspectives-A Review.Veterinary sciences · 2024Review
- Approaches to standardising the magnetic resonance image analysis of equine tendon lesions.Veterinary record open · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Low-field magnetic resonance imaging (MRI) has gained increasing importance to monitor equine tendon lesions. Comparing results between studies and cases is hampered, because image analysis approaches vary strongly. This study aimed to improve reliability, comparability and time efficiency of quantitative MRI image analysis. Methods: Induced tendon lesions were studied over a 24-week period with 10 follow-up MRI examinations. Signal intensities (SIs) of tendons, tendon lesions, cortical bone and background, as well as lesion cross-sectional areas (CSAs) were measured. Lesion SI standardisation with different formulas was evaluated, using histological findings as reference. Different types of region of interest (ROI) for lesion SI measurement were compared. Lesion CSA measurement at different levels was evaluated, using the calculated total lesion volume as reference. Subjective lesion identification and manual CSA and SI measurements were compared to an automated, algorithm-based approach. Results: Lesion SI standardised using a quotient of lesion and background or cortical bone SI, correlated best with histologically determined lesion severity. Lesion SI in circular ROIs correlated strongly with lesion SI in free-hand whole-lesion ROIs. The level of the maximum lesion CSA shifted over time; the CSA maximum correlated strongly with lesion volume. In sequences with short acquisition time, algorithm-based automated lesion detection showed almost perfect agreement with subjective lesion identification. Automated measurement of CSA and SI was also feasible, with stronger correlation and better agreement with the manually obtained data for the SI than for the CSA. Conclusion: Our study may provide guidance for MRI image analysis of tendon healing. Reliable image analysis can be performed time-efficiently, particularly regarding lesion SI quantification.
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Registered trials
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