Evidence map›Paper›PMID 41996421›Full record

ArticlePloS one2026

Repeatability of automated body composition measurement on low dose chest CT in male subjects.

Stijn Bunk, Edwin Bennink, Grigory Sidorenkov, Hester Gietema, Harry Groen, Geertruida de Bock, Pim A de Jong, Rozemarijn Vliegenthart, Firdaus Mohamed Hoesein, NELSON-POP consortium

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Stijn BunkUniversity Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0009-0009-3020-995X
Edwin BenninkUniversity Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Grigory SidorenkovUniversity Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0002-1926-8862
Hester GietemaMaastricht University Medical Center, Maastricht University, Maastricht, The Netherlands.
Harry GroenUniversity Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Geertruida de BockUniversity Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0003-3104-4471
Pim A de JongUniversity Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Rozemarijn VliegenthartUniversity Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Firdaus Mohamed HoeseinUniversity Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
NELSON-POP consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe objective was to determine the most repeatable of three automated body composition methods applied to baseline and short-term follow-up chest CT scans.

methodsAreas of skeletal muscle and subcutaneous adipose tissue (SAT) were analyzed in a 1 mm slice close to the aortic arch in a subset of males from the NELSON lung cancer screening trial with baseline and 3-4 month repeat CT scan. We compared three pre-existing machine learning methods we call: truncated field of view (FOV), compensated FOV, and extended FOV, of which the last two can deal with non-overlapping FOV in scans. Repeatability was assessed using Bland-Altman plots and paired T-tests.

resultsOf 562 males the median (interquartile range) age was 60.8 (56.3-64.8) years. Mean skeletal muscle areas were similar for truncated (212 cm²) and extended FOV (211 cm²), and slightly lower for compensated FOV (208 cm²) (p < 0.001). SAT areas were higher with extended FOV (156 cm²) compared to truncated (132 cm²) and compensated FOV (125 cm²) (p < 0.001). A small systematic longitudinal difference in skeletal muscle was observed for extended FOV (mean±SD 1.7 ± 17.3 cm2, p = 0.017). Limits of agreement for skeletal muscle area were -18.9% to 20.4% for truncated FOV, -11.1% to 11.6% for compensated FOV, and -16.7% to 18.2% for extended FOV. Corresponding values for SAT area were -37.3% to 38.3%,-30.2% to 29.3%, and -29.1% to 29.9%.

conclusionExtended FOV had the second-most repeatable measurements and was unaffected by FOV cutoff. Compensated FOV was most repeatable, but underestimated SAT.

Indexed as

Body CompositionRadiography, ThoracicTomography, X-Ray ComputedAutomationHumansMaleMiddle AgedMuscle, SkeletalRadiation DosageReproducibility of ResultsSubcutaneous Fat

Identifiers

PMID41996421
PMCPMC13089885

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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.