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Abstract #1030

Assessing Semi-Automatic processing of Muscle Mass and Fat Fractions from mDIXON whole body MRI

Rosemary Nicholas1, Paul Greenhaff1, and Susan Francis1
1UNIVERSITY OF NOTTINGHAM, Nottingham, United Kingdom


Muscle volume and fat fraction can be quantified from mDIXON scans either manually or using automated processes. Here we compare manual volumes of thigh and calf muscle ROIs with an automated pipeline created using FSL’s FAST segmentation, to compare muscle volume and fat fraction across subject groups and with their DXA values. Automatic volume segmentations correlated highly with manually drawn measures (r=.975) as well as DXA (r=0.840). Group comparisons show COPD and post-COVID patients had significantly lower muscle mass and higher fat fraction. Automatic segmentation performs well compared to manually derived volumes and is more time efficient.

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