MRI ‐Derived Muscle Fat Fraction Reflects Disease Severity and Functional Impairment in Charcot–Marie–Tooth Disease Type 1A

Introduction/Aims Progressive intramuscular fat infiltration is a hallmark of neuromuscular degeneration in Charcot–Marie–Tooth disease type 1A (CMT1A). Quantitative assessment of muscle fat fraction (FF) by Dixon magnetic resonance imaging (MRI) provides an objective biomarker of disease severity, but manual segmentation is laborious and variable. This study explored whether automated MRI‐based FF quantification reflects disease severity and functional decline in CMT1A. Methods Sixty‐nine genetically confirmed patients with CMT1A who underwent 3D multi‐echo Dixon lower‐leg MRI were retrospectively analyzed. A deep learning–based segmentation model delineated four muscle compartments (anterior, lateral, deep posterior, superficial posterior) and mean FFs were computed volumetrically. Correlations were tested between MRI‐derived FFs and clinical outcomes, including the Charcot–Marie–Tooth Neuropathy Score (CMTNSv2), Functional Disability Scale (FDS), and time‐, strength‐, distance‐, and repetition‐based performance. Partial correlations were adjusted for age and body mass index. Results All compartmental and total FFs correlated positively with CMTNSv2 and FDS ( r = 0.39–0.49, p < 0.05). FFs were positively associated with time‐based and negatively with strength‐, distance‐, and repetition‐based measures. FF Anterior showed moderate correlations with stair climb time ( r = 0.68, p < 0.001) and 6‐min walk distance ( r = −0.66, p < 0.001), with similar magnitudes across compartments. Most associations remained significant after adjustment. The lateral compartment showed the highest FF (median 33.2%), consistent with the peroneal pattern of CMT1A. Discussion Automated MRI‐based FF quantification provides a reproducible biomarker of disease burden in CMT1A, reflecting clinical severity and functional decline, and may serve as an imaging outcome measure in future studies.