Evidence map›Paper›PMID 40122750›Full record

ArticleZeitschrift fur medizinische Physik2026

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

Tobias Haueise, Fritz Schick, Norbert Stefan, Elena Grune, Marc-Nicolas von Itter, Hans-Ulrich Kauczor, Johanna Nattenmüller, Tobias Norajitra, Tobias Nonnenmacher, Susanne Rospleszcz and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Zeitschrift fur medizinische Physik, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Tobias HaueiseInstitute for Diabetes Research and Metabolic Diseases, Helmholtz Munich at the University of Tübingen, Tübingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany.
Fritz SchickInstitute for Diabetes Research and Metabolic Diseases, Helmholtz Munich at the University of Tübingen, Tübingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany; Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Tübingen, Germany.
Norbert StefanInstitute for Diabetes Research and Metabolic Diseases, Helmholtz Munich at the University of Tübingen, Tübingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany; Department of Internal Medicine, Division of Diabetology, Endocrinology and Nephrology, University of Tübingen, Tübingen, Germany.
Elena GruneDepartment of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany.
Marc-Nicolas von ItterDepartment of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Hans-Ulrich KauczorDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.
Johanna NattenmüllerInstitute of Radiology and Nuclear Medicine, Hirslanden Klinik St. Anna, Lucerne, Switzerland; Department of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Tobias NorajitraDivision of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany; Pattern Analysis and Learning Group, Department of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany.
Tobias NonnenmacherDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.
Susanne RospleszczDepartment of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Institute of Epidemiology, Helmholtz Munich, Environmental Health Center, Neuherberg, Germany.
Klaus H Maier-HeinDivision of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany; Pattern Analysis and Learning Group, Department of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany.
Christopher L SchlettDepartment of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Jakob B WeissDepartment of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Beate FischerDepartment of Epidemiology and Preventive Medicine, University of Regensburg, Germany.
Karl-Heinz JöckelInstitute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital Essen, Essen, Germany.
Lilian KristInstitute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Thoralf NiendorfBerlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany; Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.
Annette PetersDepartment of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany; Institute of Epidemiology, Helmholtz Munich, Environmental Health Center, Neuherberg, Germany; German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany; German Center for Diabetes Research (DZD), Partner Site Neuherberg, Neuherberg, Germany.
Anja M SedlmeierDepartment of Epidemiology and Preventive Medicine, University of Regensburg, Germany; Center for Translational Oncology, University Hospital Regensburg, Germany; Bavarian Cancer Research Center (BZKF), Regensburg, Germany.
Stefan N WillichInstitute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Fabian BambergDepartment of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Jürgen MachannInstitute for Diabetes Research and Metabolic Diseases, Helmholtz Munich at the University of Tübingen, Tübingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany; Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Tübingen, Germany. Electronic address: juergen.machann@med.uni-tuebingen.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesHigh 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

methodsThis 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.

resultsData 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.

conclusionsThe 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/m

Indexed as

Body Mass IndexImaging, Three-DimensionalIntra-Abdominal FatMagnetic Resonance ImagingAdultAgedAge FactorsCohort StudiesFemaleGermanyHumansMaleMiddle AgedProspective StudiesSex FactorsDeep learningMagnetic resonance imagingObesitySingle slice quantificationVisceral adipose tissue

Identifiers

PMID40122750
PMCPMC12901527

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.