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Abstract #2228

Value of Quantitative MRI in Muscle Classification and Force Prediction: Insights from the MOTION Study

Martijn Froeling1, Roosmarijn Brenninkmeijer2, Danny R van der Woude2, Bart Bartels2, and Linda Heskamp1
1Center for Image Sciences, Department of Imaging and Oncology, University Medical Center Utrecht, Utrecht, Netherlands, 2Child Development and Exercise Center, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, Netherlands

Synopsis

Keywords: Muscle, Muscle

Motivation: Quantitative MRI (qMRI) is valuable for assessing muscle properties but often lacks specificity and functional linkage.

Goal(s): The MOTION study aims to (i) identify key factors affecting qMRI measures and assess the value of qMRI measures for muscle (ii) classification and (iii) force prediction.

Approach: Whole-leg qMRI, muscle force, and lifestyle data were collected from 79 of 162 healthy volunteers. Covariate analysis was performed, and models were trained for muscle classification and force prediction using qMRI, volume, and biometric data.

Results: qMRI parameters are affected by muscle type, gender, and lean body mass. Furthermore, qMRI parameters improved muscle classification, but not force prediction.

Impact: This study identifies key covariates and demonstrates the added value of qMRI for muscle classification, while highlighting volume and biometric data as primary predictors of muscle force. Understanding which parameters define normal parameters aids in understanding muscle abnormalities.

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Keywords