Evidence map›Paper›PMID 42164140›Full record

ArticleJournal of orthopaedic translation2026

Quantification of skeletal muscle density, mass and fat fraction using single-energy computed tomography.

Jonathan Bammessel, Stefan Bartenschlager, Oliver Chaudry, Nicolai Krekiehn, Fjola Johannesdottir, Ling Wang, Michael Uder, Georg Schett, Klaus Engelke

Abstract read
In one paragraph

Article in Journal of orthopaedic translation, 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

9 authors.

Jonathan BammesselDepartment of Medicine 3, Friedrich-Alexander-Universität Erlangen-Nürnberg and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany.
Stefan BartenschlagerDepartment of Medicine 3, Friedrich-Alexander-Universität Erlangen-Nürnberg and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany.
Oliver ChaudryInstitute of Radiology, Friedrich-Alexander-Universität Erlangen-Nürnberg and Universitätsklinikum Erlangen, Maximiliansplatz 3, 91054, Erlangen, Germany.
Nicolai KrekiehnSection Biomedical Imaging, Department of Radiology and Neuroradiology, Kiel University, Kiel, Germany.
Fjola JohannesdottirCenter for Advanced Orthopedic Studies, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Ling WangDepartment of Radiology, Beijing Jishuitan Hospital, Capital Medical University, National Center for Orthopaedics, Beijing, 100035, PR China.
Michael UderInstitute of Radiology, Friedrich-Alexander-Universität Erlangen-Nürnberg and Universitätsklinikum Erlangen, Maximiliansplatz 3, 91054, Erlangen, Germany.
Georg SchettDepartment of Medicine 3, Friedrich-Alexander-Universität Erlangen-Nürnberg and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany.
Klaus EngelkeDepartment of Medicine 3, Friedrich-Alexander-Universität Erlangen-Nürnberg and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Currently, CT muscle density is measured in Hounsfield units and is not converted to g/cm Methods: We propose a phantomless calibration method to calculate muscle tissue and muscle density in g/cm Results: The mean SMT CT value of the phantom measurements was 47.7 ± 1.9 HU. In line with previous publications, the SMT fat fraction was set to 3%, and the subcutaneous adipose tissue (SAT) FF to 85%. Using an SMT CT value of 48 HU, the mean muscle tissue density, muscle density, and muscle fat fraction (FF) of the 41 subjects were 0.94 ± 0.08 g/cm Conclusions: The proposed methodology for muscle calibration in single-energy CT images showed a high degree of agreement with MR Dixon FF measurements. The simulated accuracy errors were comparable to those caused by missing water offset corrections of the measured CT values. This is a proof-of-concept study, further validation in subjects with higher muscle FF and in other muscle groups is required. The translational potential of this article: Quantitative assessments of muscle properties such as density and fat infiltration are important biomarkers for myopathies, sarcopenia, obesity and potentially for osteoporosis. While MRI techniques are state-of-the-art, the opportunistic use of existing CT scans can support screening strategies and may help to identify more subjects at early risk for muscle and perhaps even bone loss. New CT technology, such as photon counting CT, which reduces radiation exposure by around 50% compared to standard CT, may also make CT attractive for dedicated muscle imaging.

Indexed as

CalibrationComputed tomographyMuscle densityMuscle fat fractionMuscle tissue densityParaspinal muscle

Identifiers

PMID42164140
PMCPMC13185934

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Registered trials

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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.