Evidence map›Paper›PMID 35851642›Full record

ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2023

Automated cardiovascular risk categorization through AI-driven coronary calcium quantification in cardiac PET acquired attenuation correction CT.

S G M van Velzen, M M Dobrolinska, P Knaapen, R L M van Herten, R Jukema, I Danad, R H J A Slart, M J W Greuter, I Išgum

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Article in Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Subclinical Hypertension-Mediated Organ Damage (HMOD) in Hypertension: Atherosclerotic Cardiovascular Disease (ASCVD) and Calcium Score.High blood pressure & cardiovascular prevention : the official journal of the Italian Society of Hypertension · 2023
    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

9 authors.

S G M van VelzenDepartment of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, Meibergdreef 123, 1105 AZ, Amsterdam, the Netherlands. s.g.m.vanvelzen@amsterdamumc.nl.
M M DobrolinskaMedical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, the Netherlands.
P KnaapenDepartment of Cardiology, VU University Medical Center, Amsterdam, the Netherlands.
R L M van HertenDepartment of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, Meibergdreef 123, 1105 AZ, Amsterdam, the Netherlands.
R JukemaDepartment of Cardiology, VU University Medical Center, Amsterdam, the Netherlands.
I DanadDepartment of Cardiology, VU University Medical Center, Amsterdam, the Netherlands.
R H J A SlartMedical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, the Netherlands.
M J W GreuterMedical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, the Netherlands.
I IšgumDepartment of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, Meibergdreef 123, 1105 AZ, Amsterdam, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe present an automatic method for coronary artery calcium (CAC) quantification and cardiovascular risk categorization in CT attenuation correction (CTAC) scans acquired at rest and stress during cardiac PET/CT. The method segments CAC according to visual assessment rather than the commonly used CT-number threshold.

methodsThe method decomposes an image containing CAC into a synthetic image without CAC and an image showing only CAC. Extensive evaluation was performed in a set of 98 patients, each having rest and stress CTAC scans and a dedicated calcium scoring CT (CSCT). Standard manual calcium scoring in CSCT provided the reference standard.

resultsThe interscan reproducibility of CAC quantification computed as average absolute relative differences between CTAC and CSCT scan pairs was 75% and 85% at rest and stress using the automatic method compared to 121% and 114% using clinical calcium scoring. Agreement between automatic risk assessment in CTAC and clinical risk categorization in CSCT resulted in linearly weighted kappa of 0.65 compared to 0.40 between CTAC and CSCT using clinically used calcium scoring.

conclusionThe increased interscan reproducibility achieved by our method may allow routine cardiovascular risk assessment in CTAC, potentially relieving the need for dedicated CSCT.

Indexed as

Cardiovascular DiseasesCoronary Artery DiseaseArtificial IntelligenceCalciumCoronary VesselsHeart Disease Risk FactorsHumansPositron Emission Tomography Computed TomographyReproducibility of ResultsRisk FactorsTomography, X-Ray ComputedCalciumartificial intelligenceatherosclerosisCADCTimage analysisrisk categorization

Identifiers

PMID35851642
PMCPMC10261233

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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.