Lena Sophie Kiefer1, Jana Fabian1, Roberto Lorbeer2, Jürgen Machann3,4,5, Corinna Storz1, Mareen Sarah Kraus1, Elke Wintermeyer6, Christopher Schlett7, Frank Roemer8, Konstantin Nikolaou1, Annette Peters9,10,11, Fabian Bamberg1,9. 1. 1 Department of Diagnostic and Interventional Radiology, University of Tuebingen , Tuebingen , Germany. 2. 2 Department of Radiology, Ludwig-Maximilian-University Hospital , Munich , Germany. 3. 3 Department of Diagnostic and Interventional Radiology, Section of Experimental Radiology, University of Tuebingen , Tuebingen , Germany. 4. 4 Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich at the University of Tuebingen , Tuebingen , Germany. 5. 5 German Center for Diabetes Research (DZD) , Neuherberg , Germany. 6. 6 BG Trauma Center, University of Tuebingen , Tuebingen , Germany. 7. 7 Department of Radiology, Diagnostic and Interventional Radiology, University of Heidelberg , Heidelberg , Germany. 8. 8 Department of Radiology, University of Erlangen-Nuremberg , Erlangen , Germany. 9. 9 German Center for Cardiovascular Disease Research (DZHK e.V.) , Munich , Germany. 10. 10 Institute for Cardiovascular Prevention, Ludwig-Maximilian-University-Hospital , Munich , Germany. 11. 11 Institute of Epidemiology II, Helmholtz Zentrum Munich, German Research Center for Environmental Health , Neuherberg , Germany.
Abstract
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.
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.
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