Evidence map›Paper›PMID 40536702›Full record

ArticleEuropean radiology2025

Concordance between single-slice abdominal computed tomography-based and bioelectrical impedance-based analysis of body composition in a prospective study.

Uli Fehrenbach, Clarissa Hosse, William Wienbrandt, Thula Walter-Rittel, Johannes Kolck, Timo Alexander Auer, Elisabeth Blüthner, Frank Tacke, Nick Lasse Beetz, Dominik Geisel

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In one paragraph

Article in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

10 authors.

Uli Fehrenbach *Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, Germany. uli.fehrenbach@charite.de.ORCID http://orcid.org/0000-0003-3622-3268
Clarissa Hosse *Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, Germany.
William WienbrandtCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, Germany.
Thula Walter-RittelCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, Germany.
Johannes KolckCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, Germany.
Timo Alexander AuerCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, Germany.
Elisabeth BlüthnerCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Hepatology & Gastroenterology, Campus Virchow Klinikum and Campus Charité Mitte, Berlin, Germany.
Frank TackeCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Hepatology & Gastroenterology, Campus Virchow Klinikum and Campus Charité Mitte, Berlin, Germany.
Nick Lasse Beetz *Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, Germany.
Dominik Geisel *Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesBody composition analysis (BCA) is a recognized indicator of patient frailty. Apart from the established bioelectrical impedance analysis (BIA), computed tomography (CT)-derived BCA is being increasingly explored. The aim of this prospective study was to directly compare BCA obtained from BIA and CT. MATERIALS AND

methodsA total of 210 consecutive patients scheduled for CT, including a high proportion of cancer patients, were prospectively enrolled. Immediately prior to the CT scan, all patients underwent BIA. CT-based BCA was performed using a single-slice AI tool for automated detection and segmentation at the level of the third lumbar vertebra (L3). BIA-based parameters, body fat mass (BFM

resultsParameters representing fat, BFM

conclusionCT-based BCA strongly correlates with BIA results and yields quantitative results for BFP and SMI comparable to the existing gold standard. KEY POINTS: Question CT-based body composition analysis (BCA) is moving more and more into clinical focus, but validation against established methods is lacking. Findings Fully automated CT-based BCA correlates very strongly with guideline-accepted bioelectrical impedance analysis (BIA). Clinical relevance BCA is currently moving further into clinical focus to improve assessment of patient frailty and individualize therapies accordingly. Comparability with established BIA strengthens the value of CT-based BCA and supports its translation into clinical routine.

Indexed as

Body CompositionElectric ImpedanceTomography, X-Ray ComputedAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedProspective StudiesReproducibility of ResultsArtificial intelligenceBioelectrical impedanceBody compositionComputed tomographyFrailty

Identifiers

PMID40536702
PMCPMC12634744

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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.