Analysis of volume and topography of adipose tissue in the trunk: Results of MRI of 11,141 participants in the German National Cohort
Authors
- T. Haueise
- F. Schick
- N. Stefan
- C.L. Schlett
- J.B. Weiss
- J. Nattenmüller
- K. Göbel-Guéniot
- T. Norajitra
- T. Nonnenmacher
- H.U. Kauczor
- K.H. Maier-Hein
- T. Niendorf
- T. Pischon
- K.H. Jöckel
- L. Umutlu
- A. Peters
- S. Rospleszcz
- T. Kröncke
- N. Hosten
- H. Völzke
- L. Krist
- S.N. Willich
- F. Bamberg
- J. Machann
Journal
- Science Advances
Citation
- Sci Adv 9 (19): eadd0433
Abstract
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.