Evidence mapPaperPMID 40924130Full record

ArticleAbdominal radiology (New York)2026

Automated volumetric MRI quantification of body fat and skeletal muscle in the UK Biobank: technical validation against expert manual segmentations and comparison with single-slice techniques.

Magdalena Nowak, Luis Núñez, Charles E Hill, Tim Pagliaro, John McGonigle, Marili Niglas, Camillo Bell-Bradford, Matthew D Robson, Helena Thomaides Brears, E Louise Thomas and 1 more

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In one paragraph

Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Magdalena NowakPerspectum, Oxford, UK. magdalena.nowak@perspectum.com.ORCID 0000-0001-6346-197X
Luis NúñezPerspectum, Oxford, UK.ORCID 0000-0001-8403-9380
Charles E HillPerspectum, Oxford, UK.ORCID 0000-0001-5825-030X
Tim PagliaroPerspectum, Oxford, UK.
John McGoniglePerspectum, Oxford, UK.ORCID 0000-0001-6670-8181
Marili NiglasResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
Camillo Bell-BradfordResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
Matthew D RobsonPerspectum, Oxford, UK.ORCID 0000-0002-5902-1012
Helena Thomaides BrearsPerspectum, Oxford, UK.ORCID 0000-0003-0774-6983
E Louise ThomasResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.ORCID 0000-0003-4235-4694
Jimmy D BellResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.ORCID 0000-0003-3804-1281

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe escalating global incidence of obesity, cardiometabolic disease and sarcopenia necessitates reliable body composition measurement tools. MRI-based assessment is the gold standard, with utility in both clinical and drug trial settings. This study aims to validate a new automated volumetric MRI method by comparing with manual ground truth, prior volumetric measurements, and against a new method for semi-automated single-slice area measurements.

methods4905 individuals from the UK Biobank with repeat whole-body Dixon MRI scans were selected. MRI data were processed automatically to derive new (1) volumetric and (2) single-slice area measurements at L3 vertebral level for visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and abdominal skeletal muscle (SM). For comparison, prior volumetric measurements of VAT and SAT were included. A separate set of scans from 100 subjects was randomly selected and body composition volumes and areas were manually segmented as ground truth.

resultsThe new automated volumetric measurements were found to have excellent agreement with manual ground truth with no substantial bias (ICC ≥ 0.96, CoV ≤ 3.8%). In the cohort of 4905 individuals (49% male, mean age 62 years ± 8, BMI 26 kg/m

conclusionWe found robust correlations between manually segmented, automated volumetric, and semi-automated single-slice body composition methods. The interchangeability of these methods suggests that for each application the method should be selected according to practical considerations, operational differences and measurement granularity, rather than technical performance.

Indexed as

Adipose TissueMagnetic Resonance ImagingMuscle, SkeletalAdultAgedBiological Specimen BanksBody CompositionFemaleHumansMaleMiddle AgedReproducibility of ResultsUK BiobankUnited KingdomBody compositionMRISingle-sliceSkeletal muscleVisceral adipose tissueVolumetric

Identifiers

PMID40924130
PMCPMC13013200

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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 Socratic graph.