Doll, Carla UlrikeCarla UlrikeDollBohner, MelanieMelanieBohnerBerner, DagmarDagmarBernerBuettner, KathrinKathrinBuettnerHorstmeier, CarolinCarolinHorstmeierWinter, KarstenKarstenWinterBurk, JaninaJaninaBurk2023-11-132023-11-132023https://jlupub.ub.uni-giessen.de/handle/jlupub/18606http://dx.doi.org/10.22029/jlupub-17970Background: Low-field magnetic resonance imaging (MRI) has gained increasingimportance to monitor equine tendon lesions. Comparing results between studies andcases is hampered, because image analysis approaches vary strongly. This study aimed toimprove 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 boneand background, as well as lesion cross-sectional areas (CSAs) were measured. LesionSI standardisation with different formulas was evaluated, using histological findings asreference. Different types of region of interest (ROI) for lesion SI measurement werecompared. Lesion CSA measurement at different levels was evaluated, using the calcu-lated 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 corticalbone 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.enNamensnennung 4.0 Internationalddc:630