Evidence map›Paper›PMID 29720611›Full record

ArticleScientific reports2018

Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study.

Ping Li, Lei Xu, Lin Yang, Rui Wang, Jiang Hsieh, Zhonghua Sun, Zhanming Fan, Jonathon A Leipsic

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
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

32 citing papers in PubMed, 56 citations in OpenAlex.

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  6. Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factors.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2025
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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 at 4 institutions in 3 countries.

Ping LiDepartment of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China.
Lei XuDepartment of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China. leixu2001@hotmail.com.
Lin YangDepartment of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China.
Rui WangDepartment of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China.
Jiang HsiehMICT Engineering, GE Healthcare, Waukesha, WI, 53188, USA.
Zhonghua SunDepartment of Medical Radiation Sciences, Curtin University, Perth, 6845, Australia.
Zhanming FanDepartment of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China.
Jonathon A LeipsicDepartment of Radiology, St Paul's Hospital and University of British Columbia, Vancouver, BC, V6Z 1Y6, Canada.
Capital Medical University · CNBeijing Anzhen Hospital · CNCurtin University · AUSt. Paul's Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to investigate the use of de-blooming algorithm in coronary CT angiography (CCTA) for optimal evaluation of calcified plaques. Calcified plaques were simulated on a coronary vessel phantom and a cardiac motion phantom. Two convolution kernels, standard (STND) and high-definition standard (HD STND), were used for imaging reconstruction. A dedicated de-blooming algorithm was used for imaging processing. We found a smaller bias towards measurement of stenosis using the de-blooming algorithm (STND: bias 24.6% vs 15.0%, range 10.2% to 39.0% vs 4.0% to 25.9%; HD STND: bias 17.9% vs 11.0%, range 8.9% to 30.6% vs 0.5% to 21.5%). With use of de-blooming algorithm, specificity for diagnosing significant stenosis increased from 45.8% to 75.0% (STND), from 62.5% to 83.3% (HD STND); while positive predictive value (PPV) increased from 69.8% to 83.3% (STND), from 76.9% to 88.2% (HD STND). In the patient group, reduction in calcification volume was 48.1 ± 10.3%, reduction in coronary diameter stenosis over calcified plaque was 52.4 ± 24.2%. Our results suggest that the novel de-blooming algorithm could effectively decrease the blooming artifacts caused by coronary calcified plaques, and consequently improve diagnostic accuracy of CCTA in assessing coronary stenosis.

Indexed as

AlgorithmsComputed Tomography AngiographyAgedArtifactsCoronary Artery DiseaseCoronary StenosisFemaleHumansMaleMiddle AgedPlaque, AtheroscleroticSensitivity and SpecificityVascular Calcification

Identifiers

PMID29720611
PMCPMC5931966
OpenAlexW2805554393

What OpenQuestion holds

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LicenceCC BY
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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.