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Haueise, T. ; Schick, F. ; Stefan, N. ; Grune, E.* ; von Itter, M.N.* ; Kauczor, H.U.* ; Nattenmüller, J.* ; Norajitra, T.* ; Nonnenmacher, T.* ; Rospleszcz, S. ; Maier-Hein, K.H.* ; Schlett, C.L.* ; Weiss, J.B.* ; Fischer, B.* ; Jöckel, K.H.* ; Krist, L.* ; Niendorf, T.* ; Peters, A. ; Sedlmeier, A.M.* ; Willich, S.N.* ; Bamberg, F.* ; Machann, J.

Refining visceral adipose tissue quantification: Influence of sex, age, and BMI on single slice estimation in 3D MRI of the German National Cohort.

Z. Med. Phys., DOI: 10.1016/j.zemedi.2025.02.005 (2025)
Postprint DOI PMC
Open Access Green
Creative Commons Lizenzvertrag
OBJECTIVES: High prevalence of visceral obesity and its associated complications underscore the importance of accurately quantifying visceral adipose tissue (VAT) depots. While whole-body MRI offers comprehensive insights into adipose tissue distribution, it is resource-intensive. Alternatively, evaluation of defined single slices provides an efficient approach for estimation of total VAT volume. This study investigates the influence of sex-, age-, and BMI on VAT distribution along the craniocaudal axis and total VAT volume obtained from single slice versus volumetric assessment in 3D MRI and aims to identify age-independent locations for accurate estimation of VAT volume from single slice assessment. MATERIALS AND METHODS: This secondary analysis of the prospective population-based German National Cohort (NAKO) included 3D VIBE Dixon MRI from 11,191 participants (screened between May 2014 and December 2016). VAT and spine segmentations were automatically generated using fat-selective images. Standardized craniocaudal VAT profiles were generated. Axial percentage of total VAT was used for identification of reference locations for volume estimation of VAT from a single slice. RESULTS: Data from 11,036 participants (mean age, 52 ± 11 years, 5681 men) were analyzed. Craniocaudal VAT distribution differed qualitatively between men/women and with respect to age/BMI. Age-independent single slice VAT estimates demonstrated strong correlations with reference VAT volumes. Anatomical locations for accurate VAT estimation varied with sex/BMI. CONCLUSIONS: The selection of reference locations should be different depending on BMI groups, with a preference for caudal shifts in location with increasing BMI. For women with obesity (BMI >30 kg/m2), the L1 level emerges as the optimal reference location.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Deep Learning ; Magnetic Resonance Imaging ; Obesity ; Single Slice Quantification ; Visceral Adipose Tissue
Sprache englisch
Veröffentlichungsjahr 2025
HGF-Berichtsjahr 2025
ISSN (print) / ISBN 0939-3889
e-ISSN 1876-4436
Zeitschrift Zeitschrift für Medizinische Physik
Verlag Elsevier
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Diabetes Research and Metabolic Diseases (IDM)
Institute of Epidemiology (EPI)
POF Topic(s) 90000 - German Center for Diabetes Research
30202 - Environmental Health
Forschungsfeld(er) Helmholtz Diabetes Center
Genetics and Epidemiology
PSP-Element(e) G-502400-001
G-504000-010
G-504000-007
DOI 10.1016/j.zemedi.2025.02.005
Scopus ID 105000791168
PubMed ID 40122750
Erfassungsdatum 2025-05-09
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