Evidence map›Paper›PMID 31776743›Full record

ArticleEuropean radiology2020

Single-slice CT measurements allow for accurate assessment of sarcopenia and body composition.

David Zopfs, Sebastian Theurich, Nils Große Hokamp, Jana Knuever, Lukas Gerecht, Jan Borggrefe, Max Schlaak, Daniel Pinto Dos Santos

Registry-linked trialAbstract read
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In one paragraph

Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06404489 (Evaluation of a Multimodal Program of Prehabilitation in Oncological Patients Undergoing Major Gastrointestinal Surgery Within an ERAS Pathway.), which is not on this map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 1 pooled it
–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.

NCT06404489 naactive not recruitingnot on this mapstarted 2024, after this paper: background citation

Evaluation of a Multimodal Program of Prehabilitation in Oncological Patients Undergoing Major Gastrointestinal Surgery Within an ERAS Pathway.

TypeinterventionalSponsorUniversità Vita-Salute San RaffaeleRan2024 to 2026Enrolled400ConditionsOncological Patients, Major SurgeryArmsMultimodal prehabilitation Program
3 · Its place in the literature

Who cites it

62 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. [The value of the nutritional assessment index or score in prognostic evaluation for patients with liver cancer].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2026
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  18. Open-Source Image Analysis Software Yields Reproducible CT Measures of Longissimus Muscle Area and Density in Sheep.Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association · 2025
    Article
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2 more citing papers are in PubMed but not listed here.

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

8 authors.

David ZopfsFaculty of Medicine and University Hospital Cologne, Department for Diagnostic and Interventional Radiology, University of Cologne, Kerpener Strasse 62, 50937, Cologne, Germany. david.zopfs@uk-koeln.de.ORCID http://orcid.org/0000-0001-9978-7453
Sebastian TheurichCancer- and Immunometabolism Research Group, Gene Center LMU, Ludwig-Maximilians-University, Munich, Germany.
Nils Große HokampFaculty of Medicine and University Hospital Cologne, Department for Diagnostic and Interventional Radiology, University of Cologne, Kerpener Strasse 62, 50937, Cologne, Germany.
Jana KnueverFaculty of Medicine and University Hospital Cologne, Department of Dermatology and Venereology, University of Cologne, Cologne, Germany.
Lukas GerechtFaculty of Medicine and University Hospital Cologne, Department of Dermatology and Venereology, University of Cologne, Cologne, Germany.
Jan BorggrefeFaculty of Medicine and University Hospital Cologne, Department for Diagnostic and Interventional Radiology, University of Cologne, Kerpener Strasse 62, 50937, Cologne, Germany.
Max SchlaakDepartment of Dermatology and Allergy, University Hospital, LMU Munich, Munich, Germany.
Daniel Pinto Dos SantosFaculty of Medicine and University Hospital Cologne, Department for Diagnostic and Interventional Radiology, University of Cologne, Kerpener Strasse 62, 50937, Cologne, Germany.

Funding

Else Kröner-Fresenius-Stiftung 2016-Kolleg-19Koeln Fortune Program / Faculty of Medicine, University of Cologne (Koeln Fortune 339/2018) 339/2018
6 · The paper itself

Abstract

objectivesTo evaluate the correlation between simple planimetric measurements in axial computed tomography (CT) slices and measurements of patient body composition and anthropometric data performed with bioelectrical impedance analysis (BIA) and metric clinical assessments.

methodsIn this prospective cross-sectional study, we analyzed data of a cohort of 62 consecutive, untreated adult patients with advanced malignant melanoma who underwent concurrent BIA assessments at their radiologic baseline staging by CT between July 2016 and October 2017. To assess muscle and adipose tissue mass, we analyzed the areas of the paraspinal muscles as well as the cross-sectional total patient area in a single CT slice at the height of the third lumbar vertebra. These measurements were subsequently correlated with anthropometric (body weight) and body composition parameters derived from BIA (muscle mass, fat mass, fat-free mass, and visceral fat mass). Linear regression models were built to allow for estimation of each parameter based on CT measurements.

resultsLinear regression models allowed for accurate prediction of patient body weight (adjusted R

conclusionsOur data suggest that patient body composition can accurately and quantitatively be determined by using simple measurements in a single axial CT slice. This could be useful in various medical and scientific settings, where the knowledge of the patient's anthropometric parameters is not immediately or easily available. KEY POINTS: • Easy to perform measurements on a single CT slice highly correlate with clinically valuable parameters of body composition. • Body composition data were acquired using bioelectrical impedance analysis to correlate CT measurements with a non-imaging-based method, which is frequently lacking in previous studies. • The obtained equations facilitate a quick, opportunistic assessment of relevant parameters of body composition.

Indexed as

Body CompositionAdultAgedAged, 80 and overAnthropometryCross-Sectional StudiesElectric ImpedanceFemaleHumansMaleMiddle AgedProspective StudiesSarcopeniaTomography, X-Ray ComputedBody compositionElectrical impedanceIntra-abdominal fatSarcopeniaTomographyX-ray computed

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Registered trials

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.