Evidence map›Paper›PMID 38904849›Full record

ArticleThe international journal of cardiovascular imaging2024

Coronary artery calcium quantification technique using dual energy material decomposition: a simulation study.

Dale Black, Tejus Singh, Sabee Molloi

Abstract readComparative Study
In one paragraph

Article in The international journal of cardiovascular imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Dale BlackDepartment of Radiological Sciences, University of California, Medical Sciences I, B-140, Irvine, CA, 92697, USA.
Tejus SinghDepartment of Radiological Sciences, University of California, Medical Sciences I, B-140, Irvine, CA, 92697, USA.
Sabee MolloiDepartment of Radiological Sciences, University of California, Medical Sciences I, B-140, Irvine, CA, 92697, USA. symolloi@uci.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronary artery calcification is a significant predictor of cardiovascular disease, with current detection methods like Agatston scoring having limitations in sensitivity. This study aimed to evaluate the effectiveness of a novel CAC quantification method using dual-energy material decomposition, particularly its ability to detect low-density calcium and microcalcifications. A simulation study was conducted comparing the dual-energy material decomposition technique against the established Agatston scoring method and the newer volume fraction calcium mass technique. Detection accuracy and calcium mass measurement were the primary evaluation metrics. The dual-energy material decomposition technique demonstrated fewer false negatives than both Agatston scoring and volume fraction calcium mass, indicating higher sensitivity. In low-density phantom measurements, material decomposition resulted in only 7.41% false-negative (CAC = 0) measurements compared to 83.95% for Agatston scoring. For high-density phantoms, false negatives were removed (0.0%) compared to 20.99% in Agatston scoring. The dual-energy material decomposition technique presents a more sensitive and reliable method for CAC quantification.

Indexed as

Computed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseCoronary VesselsPhantoms, ImagingPredictive Value of TestsRadiographic Image Interpretation, Computer-AssistedVascular CalcificationComputer SimulationFalse Negative ReactionsHumansModels, CardiovascularMultidetector Computed TomographyReproducibility of ResultsSeverity of Illness IndexAgatston scoringCalcium scoringComputed tomographyMaterial decompositionVolume fraction calcium mass

Identifiers

PMID38904849
PMCPMC11258084

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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.