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Haueise, Tobias
[Author];
Schick, Fritz
[Author];
Stefan, Norbert
[Author];
Schlett, Christopher L.
[Author];
Weiss, Jakob B.
[Author];
Nattenmüller, Johanna
[Author];
Göbel-Guéniot, Katharina
[Author];
Norajitra, Tobias
[Author];
Nonnenmacher, Tobias
[Author];
Kauczor, Hans-Ulrich
[Author];
Maier-Hein, Klaus H.
[Author];
Niendorf, Thoralf
[Author];
Pischon, Tobias
[Author];
Jöckel, Karl-Heinz
[Author];
Umutlu, Lale
[Author];
Peters, Annette
[Author];
Rospleszcz, Susanne
[Author];
Kröncke, Thomas
[Author];
Hosten, Norbert
[Author];
Völzke, Henry
[Author];
Krist, Lilian
[Author];
Willich, Stefan N.
[Author];
Bamberg, Fabian
[Author];
Machann, Juergen
[Author]
Analysis of volume and topography of adipose tissue in the trunk
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- Media type: E-Article
- Title: Analysis of volume and topography of adipose tissue in the trunk : results of MRI of 11,141 participants in the German National Cohort
- Contributor: Haueise, Tobias [Author]; Schick, Fritz [Author]; Stefan, Norbert [Author]; Schlett, Christopher L. [Author]; Weiss, Jakob B. [Author]; Nattenmüller, Johanna [Author]; Göbel-Guéniot, Katharina [Author]; Norajitra, Tobias [Author]; Nonnenmacher, Tobias [Author]; Kauczor, Hans-Ulrich [Author]; Maier-Hein, Klaus H. [Author]; Niendorf, Thoralf [Author]; Pischon, Tobias [Author]; Jöckel, Karl-Heinz [Author]; Umutlu, Lale [Author]; Peters, Annette [Author]; Rospleszcz, Susanne [Author]; Kröncke, Thomas [Author]; Hosten, Norbert [Author]; Völzke, Henry [Author]; Krist, Lilian [Author]; Willich, Stefan N. [Author]; Bamberg, Fabian [Author]; Machann, Juergen [Author]
-
Published:
May 2023
- Published in: Science advances ; 9(2023), 19 vom: Mai, Artikel-ID eadd0433, Seite 1-10
- Language: English
- DOI: 10.1126/sciadv.add0433
- Identifier:
- Origination:
-
Footnote:
Veröffentlicht: 12. Mai 2023
- Description: 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.
- Access State: Open Access