Inter- and intra-observer variability of an anatomical landmark-based, manual segmentation method by MRI for the assessment of skeletal muscle fat content and area in subjects from the general population

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 popu...

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Hauptverfasser: Kiefer, Lena Sophie (VerfasserIn) , Fabian, Jana (VerfasserIn) , Lorbeer, Roberto (VerfasserIn) , Machann, Jürgen (VerfasserIn) , Storz, Corinna (VerfasserIn) , Kraus, Mareen Sarah (VerfasserIn) , Wintermeyer, Elke (VerfasserIn) , Schlett, Christopher L. (VerfasserIn) , Roemer, Frank (VerfasserIn) , Nikolaou, Konstantin (VerfasserIn) , Peters, Annette (VerfasserIn) , Bamberg, Fabian (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: May 03, 2018
In: British journal of radiology
Year: 2018, Jahrgang: 91, Heft: 1089
ISSN:1748-880X
DOI:10.1259/bjr.20180019
Online-Zugang:Verlag, Volltext: https://doi.org/10.1259/bjr.20180019
Verlag, Volltext: https://www.birpublications.org/doi/10.1259/bjr.20180019
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Verfasserangaben:Lena Sophie Kiefer, Jana Fabian, Roberto Lorbeer, Jürgen Machann, Corinna Storz, Mareen Sarah Kraus, Elke Wintermeyer, Christopher Schlett, Frank Roemer, Konstantin Nikolaou, Annette Peters, and Fabian Bamberg

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245 1 0 |a Inter- and intra-observer variability of an anatomical landmark-based, manual segmentation method by MRI for the assessment of skeletal muscle fat content and area in subjects from the general population  |c Lena Sophie Kiefer, Jana Fabian, Roberto Lorbeer, Jürgen Machann, Corinna Storz, Mareen Sarah Kraus, Elke Wintermeyer, Christopher Schlett, Frank Roemer, Konstantin Nikolaou, Annette Peters, and Fabian Bamberg 
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520 |a 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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700 1 |a Bamberg, Fabian  |e VerfasserIn  |4 aut 
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