RESUMO
OBJECTIVES: Changes in skeletal muscle composition, such as fat content and mass, may exert unique metabolic and musculoskeletal risks; however, the reproducibility of their assessment is unknown. We determined the variability of the assessment of skeletal muscle fat content and area by MRI in a population-based sample. METHODS: A random sample from a prospective, community-based cohort study (KORA-FF4) was included. Skeletal muscle fat content was quantified as proton-density fat fraction (PDFF) and area as cross-sectional area (CSA) in multi-echo Dixon sequences (TR 8.90 ms, six echo times, flip angle 4°) by a standardized, anatomical landmark-based, manual skeletal muscle segmentation at level L3 vertebra by two independent observers. Reproducibility was assessed by intraclass correlation coefficients (ICC), scatter and Bland-Altman plots. RESULTS: From 50 subjects included (mean age 56.1 ± 8.8 years, 60.0% males, mean body mass index 28.3 ± 5.2) 2'400 measurements were obtained. Interobserver agreement was excellent for all muscle compartments (PDFF: ICC0.99, CSA: ICC0.98) with only minor absolute and relative differences (-0.2 ± 0.5%, 31 ± 44.7 mm2; -2.6 ± 6.4% and 2.7 ± 3.9%, respectively). Intra-observer reproducibility was similarly excellent (PDFF: ICC1.0, 0.0 ± 0.4%, 0.4%; CSA: ICC1.0, 5.5 ± 25.3 mm2, 0.5%, absolute and relative differences, respectively). All agreement was independent of age, gender, body mass index, body height and visceral adipose tissue (ICC0.96-1.0). Furthermore, PDFF reproducibility was independent of CSA (ICC0.93-0.99). Conclusions: Quantification of skeletal muscle fat content and area by MRI using an anatomical landmark-based, manual skeletal muscle segmentation is highly reproducible. Advances in knowledge: An anatomical landmark-based, manual skeletal muscle segmentation provides high reproducibility of skeletal muscle fat content and area and may therefore serve as a robust proxy for myosteatosis and sarcopenia in large cohort studies.