Evidence map›Paper›PMID 23324971›Full record

ArticleThe international journal of cardiovascular imaging2013

Non-calcified coronary atherosclerotic plaque visualization on CT: effects of contrast-enhancement and lipid-content fractions.

Wisnumurti Kristanto, Peter M A van Ooijen, Marcel J W Greuter, Jaap M Groen, Rozemarijn Vliegenthart, Matthijs Oudkerk

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Article in The international journal of cardiovascular imaging, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

Who cites it

6 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

6 authors.

Wisnumurti KristantoDepartment of Radiology, Center for Medical Imaging-North East Netherlands, University Medical Center Groningen, University of Groningen, PO Box 30001, 9700RB Groningen, The Netherlands.
Peter M A van Ooijen
Marcel J W Greuter
Jaap M Groen
Rozemarijn Vliegenthart
Matthijs Oudkerk

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computed tomography (CT) may characterize lipid-rich and presumably rupture-prone non-calcified coronary atherosclerotic plaque based on its Hounsfield-Unit (HU), but still inconclusively. This study aimed to evaluate factors influencing the HU-value of non-calcified plaque using software simulation. Several realistic virtual plaqueburdened coronary phantoms were constructed at 5 μm resolution. CT scanning was simulated with settings resembling a 64-row multi-detector CT (64-MDCT) and reconstructed at 64-MDCT (0.4 mm) and MicroCT (48 μm) resolutions. Influences of lumen contrast-enhancement, stenosis-grades, and plaque compositions on plaque visualization were analyzed. Lumen contrast-enhancement and mean plaque HU-value were positively correlated (R(2) > 0.92), with approximately the same slopes for all plaque compositions. Percentage lipid-content and mean plaque HU-value were negatively correlated (R(2) > 0.98). Stenosis-grade and noise had minimal influence on the correlations. Influence of lumen contrast-enhancement on plaque HU-value was following a specific exponentially declining pattern (y = Ae(-λx) + c) from the lumen border until 2-pixel radius. Outside 2-pixel radius, plaque HU-values deviated maximally 5 HU from non-contrast-enhanced reference. Thus, to avoid lumen contrast-enhancement influence, plaques should be measured outside 2-pixel radius from the lumen border. Based on the patterns found, a lumen influence correction algorithm may be developed. HU-based plaque percentage lipid-content determination might serve as an alternative plaque characterization method. However, its applicability is still hindered by many inherent limitations.

Indexed as

Multidetector Computed TomographyPlaque, AtheroscleroticAlgorithmsComputer SimulationCoronary AngiographyCoronary Artery DiseaseCoronary StenosisCoronary VesselsHumansLinear ModelsLipidsModels, CardiovascularPhantoms, ImagingPredictive Value of TestsSeverity of Illness IndexSoftwareLipids

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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.