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Haueise, T. ; Schick, F. ; Stefan, N. ; Schlett, C.L.* ; Weiss, J.B.* ; Nattenmüller, J.* ; Göbel-Guéniot, K.* ; Norajitra, T.* ; Nonnenmacher, T.* ; Kauczor, H.U.* ; Maier-Hein, K.H.* ; Niendorf, T.* ; Pischon, T.* ; Jöckel, K.H.* ; Umutlu, L.* ; Peters, A. ; Rospleszcz, S. ; Kröncke, T.* ; Hosten, N.* ; Völzke, H.* ; Krist, L.* ; Willich, S.N.* ; Bamberg, F.* ; Machann, J.

Analysis of volume and topography of adipose tissue in the trunk: Results of MRI of 11,141 participants in the German National Cohort.

Sci. Adv. 9:eadd0433 (2023)
DOI PMC
Creative Commons Lizenzvertrag
Open Access Gold möglich sobald Verlagsversion bei der ZB eingereicht worden ist.
This research addresses the assessment of adipose tissue (AT) and spatial distribution of visceral (VAT) and subcutaneous fat (SAT) in the trunk from standardized magnetic resonance imaging at 3 T, thereby demonstrating the feasibility of deep learning (DL)-based image segmentation in a large population-based cohort in Germany (five sites). Volume and distribution of AT play an essential role in the pathogenesis of insulin resistance, a risk factor of developing metabolic/cardiovascular diseases. Cross-validated training of the DL-segmentation model led to a mean Dice similarity coefficient of >0.94, corresponding to a mean absolute volume deviation of about 22 ml. SAT is significantly increased in women compared to men, whereas VAT is increased in males. Spatial distribution shows age- and body mass index-related displacements. DL-based image segmentation provides robust and fast quantification of AT (≈15 s per dataset versus 3 to 4 hours for manual processing) and assessment of its spatial distribution from magnetic resonance images in large cohort studies.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Multi-atlas Segmentation; Body-fat Distribution; Obesity; Population; Design; Burden; Images; Risk; Men
ISSN (print) / ISBN 2375-2548
e-ISSN 2375-2548
Zeitschrift Science Advances
Quellenangaben Band: 9, Heft: 19, Seiten: , Artikelnummer: eadd0433 Supplement: ,
Verlag American Association for the Advancement of Science (AAAS)
Verlagsort Washington, DC [u.a.]
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Diabetes Research and Metabolic Diseases (IDM)
Institute of Epidemiology II (EPI2)
Förderungen Leibniz Association
Helmholtz Association
federal states
Federal Ministry of Education and Research (BMBF)
German Federal Ministry of Education and Research (BMBF)
German Research Foundation