Evidence map›Paper›PMID 38688396›Full record

ArticleCurrent problems in cardiology2024

Intra- and inter-reader reproducibility in quantitative coronary plaque analysis on coronary computed tomography angiography.

Raymundo A Quintana, Philipp von Knebel Doeberitz, Nishant Vatsa, Chang Liu, Yi-An Ko, Carlo N De Cecco, Marly van Assen, Arshed A Quyyumi

Abstract read
In one paragraph

Article in Current problems in cardiology, 2024. 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.

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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.

Raymundo A QuintanaCardiovascular Imaging Section, Division of Cardiology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Philipp von Knebel DoeberitzInstitute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Nishant VatsaDepartment of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA.
Chang LiuDepartment of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Yi-An KoDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Carlo N De CeccoDepartment of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA; Translational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Emory University School of Medicine, Atlanta, GA, USA.
Marly van AssenDepartment of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA; Translational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Emory University School of Medicine, Atlanta, GA, USA.
Arshed A QuyyumiDepartment of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA. Electronic address: aquyyum@emory.edu.

Funding

Neuro HPA Project 1U54AG062334 · NIA · EMORY UNIVERSITY · PI Ighovwerha Ofotokun · 2018 to 2026
$12.2M
Multidisciplinary Research Training to Reduce Inequities in Cardiovascular HealthT32HL130025 · NHLBI · EMORY UNIVERSITY · PI Tené T Lewis, Viola Vaccarino · 2016 to 2026
$6.4M
NHLBI NIH HHS T32 HL130025NIA NIH HHS U54 AG062334
6 · The paper itself

Abstract

purposeCoronary artery plaque burden, low attenuation non-calcified plaque (LAP), and pericoronary adipose tissue (PCAT) on coronary CT angiography (CCTA), have been linked to future cardiac events. The purpose of this study was to evaluate intra- and inter reader reproducibility in the quantification of coronary plaque burden and its characteristics using an artificial intelligence-enhanced semi-automated software. MATERIALS AND

methodsA total of 10 women and 6 men, aged 52 (IQR 49-58) underwent CCTA using a Siemens Somatom Force, Somatom Definition AS and Somatom Definition Flash scanners. Two expert readers utilized dedicated semi-automatic software (vascuCAP, Elucid Bioimaging, Wenham, MA) to assess calcified plaque, low attenuation plaque and PCAT. Readers were blinded to all clinical information and repeated their analysis at 6 weeks in random order to minimize recall bias. Data analysis was performed on the right and left coronary arteries. Intra- and inter-reader reproducibility was compared using Pearson correlation coefficient, while absolute values between analyses and readers were compared with paired non-parametric tests. This is a sub-study of the Specialized Center of Research Excellence (SCORE) clinical trial (5U54AG062334).

resultsA total of 64 vessels from 16 patients were analyzed. Intra-reader Pearson correlation coefficients for calcified plaque volume, LAP volume and PCAT volumes were 0.96, 0.99 and 0.92 for reader 1 and 0.94, 0.94 and 0.95 for reader 2, respectively, (all p < 0.0001). Inter-reader Pearson correlation coefficients for calcified plaque volume, LAP and PCAT volumes were 0.92, 0.96 and 0.78, and 0.99, 0.99 and 0.93 on the second analyses, all had a p value <0.0001. There was no significant bias on the corresponding Bland-Altman analyses.

conclusionVolume measurement of coronary plaque burden and PCAT volume can be performed with high intra- and inter-reader agreement.

Indexed as

Computed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseCoronary VesselsPlaque, AtheroscleroticFemaleHumansMaleMiddle AgedObserver VariationReproducibility of ResultsBland–Altman plotComputerized tomographyCoronary artery diseaseInter-readerIntra-reader reproducibilityPlaque burden

Identifiers

PMID38688396
PMCPMC11146670

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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.