Evidence map›Paper›PMID 36251648›Full record

ArticlePloS one2022

Internal calibration for opportunistic computed tomography muscle density analysis.

Ainsley C J Smith, Justin J Tse, Tadiwa H Waungana, Kirsten N Bott, Michael T Kuczynski, Andrew S Michalski, Steven K Boyd, Sarah L Manske

Abstract read
In one paragraph

Article in PloS one, 2022. 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
  2. Review
  3. Review
  4. Article
  5. Myosteatosis: diagnostic significance and assessment by imaging approaches.Quantitative imaging in medicine and surgery · 2024
    Review
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.

Ainsley C J SmithBiomedical Engineering Graduate Program, University of Calgary, Alberta, Canada.ORCID 0000-0002-9604-6382
Justin J TseDepartment of Radiology, Cumming School of Medicine, University of Calgary, Alberta, Canada.
Tadiwa H WaunganaBiomedical Engineering Graduate Program, University of Calgary, Alberta, Canada.ORCID 0000-0002-0430-4242
Kirsten N BottDepartment of Radiology, Cumming School of Medicine, University of Calgary, Alberta, Canada.
Michael T KuczynskiBiomedical Engineering Graduate Program, University of Calgary, Alberta, Canada.ORCID 0000-0001-5671-1205
Andrew S MichalskiBiomedical Engineering Graduate Program, University of Calgary, Alberta, Canada.
Steven K BoydBiomedical Engineering Graduate Program, University of Calgary, Alberta, Canada.
Sarah L ManskeBiomedical Engineering Graduate Program, University of Calgary, Alberta, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMuscle weakness can lead to reduced physical function and quality of life. Computed tomography (CT) can be used to assess muscle health through measures of muscle cross-sectional area and density loss associated with fat infiltration. However, there are limited opportunities to measure muscle density in clinically acquired CT scans because a density calibration phantom, allowing for the conversion of CT Hounsfield units into density, is typically not included within the field-of-view. For bone density analysis, internal density calibration methods use regions of interest within the scan field-of-view to derive the relationship between Hounsfield units and bone density, but these methods have yet to be adapted for muscle density analysis. The objective of this study was to design and validate a CT internal calibration method for muscle density analysis. METHODOLOGY: We CT scanned 10 bovine muscle samples using two scan protocols and five scan positions within the scanner bore. The scans were calibrated using internal calibration and a reference phantom. We tested combinations of internal calibration regions of interest (e.g., air, blood, bone, muscle, adipose).

resultsWe found that the internal calibration method using two regions of interest, air and adipose or blood, yielded accurate muscle density values (< 1% error) when compared with the reference phantom. The muscle density values derived from the internal and reference phantom calibration methods were highly correlated (R2 > 0.99). The coefficient of variation for muscle density across two scan protocols and five scan positions was significantly lower for internal calibration (mean = 0.33%) than for Hounsfield units (mean = 6.52%). There was no difference between coefficient of variation for the internal calibration and reference phantom methods.

conclusionsWe have developed an internal calibration method to produce accurate and reliable muscle density measures from opportunistic computed tomography images without the need for calibration phantoms.

Indexed as

Quality of LifeTomography, X-Ray ComputedAnimalsBone DensityCalibrationCattleMusclesPhantoms, Imaging

Identifiers

PMID36251648
PMCPMC9576101

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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.