% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Haueise:300113,
      author       = {T. Haueise and F. Schick and N. Stefan and E. Grune and
                      M.-N. von Itter and H.-U. Kauczor and J. Nattenmüller and
                      T. Norajitra$^*$ and T. Nonnenmacher and S. Rospleszcz and
                      K. H. Maier-Hein$^*$ and C. L. Schlett and J. B. Weiss and
                      B. Fischer and K.-H. Jöckel and L. Krist and T. Niendorf
                      and A. Peters and A. M. Sedlmeier and S. N. Willich and F.
                      Bamberg and J. Machann},
      title        = {{R}efining visceral adipose tissue quantification:
                      {I}nfluence of sex, age, and {BMI} on single slice
                      estimation in 3{D} {MRI} of the {G}erman {N}ational
                      {C}ohort.},
      journal      = {Zeitschrift für medizinische Physik},
      volume       = {36},
      number       = {1},
      issn         = {0939-3889},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {DKFZ-2025-00611},
      pages        = {114-124},
      year         = {2026},
      note         = {2026 Feb;36(1):114-124},
      abstract     = {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.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.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.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.},
      keywords     = {Deep learning (Other) / Magnetic resonance imaging (Other)
                      / Obesity (Other) / Single slice quantification (Other) /
                      Visceral adipose tissue (Other)},
      cin          = {E230},
      ddc          = {610},
      cid          = {I:(DE-He78)E230-20160331},
      pnm          = {315 - Bildgebung und Radioonkologie (POF4-315)},
      pid          = {G:(DE-HGF)POF4-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40122750},
      doi          = {10.1016/j.zemedi.2025.02.005},
      url          = {https://inrepo02.dkfz.de/record/300113},
}