The accuracy of coronary CT angiography in patients with coronary calcium score above 1000 Agatston Units: Comparison with quantitative coronary angiography.


Journal

Journal of cardiovascular computed tomography
ISSN: 1876-861X
Titre abrégé: J Cardiovasc Comput Tomogr
Pays: United States
ID NLM: 101308347

Informations de publication

Date de publication:
Historique:
received: 14 12 2020
revised: 13 02 2021
accepted: 14 03 2021
pubmed: 30 3 2021
medline: 15 12 2021
entrez: 29 3 2021
Statut: ppublish

Résumé

High amounts of coronary artery calcium (CAC) pose challenges in interpretation of coronary CT angiography (CCTA). The accuracy of stenosis assessment by CCTA in patients with very extensive CAC is uncertain. Retrospective study was performed including patients who underwent clinically directed CCTA with CAC score >1000 and invasive coronary angiography within 90 days. Segmental stenosis on CCTA was graded by visual inspection with two-observer consensus using categories of 0%, 1-24%, 25-49%, 50-69%, 70-99%, 100% stenosis, or uninterpretable. Blinded quantitative coronary angiography (QCA) was performed on all segments with stenosis ≥25% by CCTA. The primary outcome was vessel-based agreement between CCTA and QCA, using significant stenosis defined by diameter stenosis ≥70%. Secondary analyses on a per-patient basis and inclusive of uninterpretable segments were performed. 726 segments with stenosis ≥25% in 346 vessels within 119 patients were analyzed. Median coronary calcium score was 1616 (1221-2118). CCTA identification of QCA-based stenosis resulted in a per-vessel sensitivity of 79%, specificity of 75%, positive predictive value (PPV) of 45%, negative predictive value (NPV) of 93%, and accuracy 76% (68 false positive and 15 false negative). Per-patient analysis had sensitivity 94%, specificity 55%, PPV 63%, NPV 92%, and accuracy 72% (30 false-positive and 3 false-negative). Inclusion of uninterpretable segments had variable effect on sensitivity and specificity, depending on whether they are considered as significant or non-significant stenosis. In patients with very extensive CAC (>1000 Agatston units), CCTA retained a negative predictive value ​> ​90% to identify lack of significant stenosis on a per-vessel and per-patient level, but frequently overestimated stenosis.

Sections du résumé

BACKGROUND BACKGROUND
High amounts of coronary artery calcium (CAC) pose challenges in interpretation of coronary CT angiography (CCTA). The accuracy of stenosis assessment by CCTA in patients with very extensive CAC is uncertain.
METHODS METHODS
Retrospective study was performed including patients who underwent clinically directed CCTA with CAC score >1000 and invasive coronary angiography within 90 days. Segmental stenosis on CCTA was graded by visual inspection with two-observer consensus using categories of 0%, 1-24%, 25-49%, 50-69%, 70-99%, 100% stenosis, or uninterpretable. Blinded quantitative coronary angiography (QCA) was performed on all segments with stenosis ≥25% by CCTA. The primary outcome was vessel-based agreement between CCTA and QCA, using significant stenosis defined by diameter stenosis ≥70%. Secondary analyses on a per-patient basis and inclusive of uninterpretable segments were performed.
RESULTS RESULTS
726 segments with stenosis ≥25% in 346 vessels within 119 patients were analyzed. Median coronary calcium score was 1616 (1221-2118). CCTA identification of QCA-based stenosis resulted in a per-vessel sensitivity of 79%, specificity of 75%, positive predictive value (PPV) of 45%, negative predictive value (NPV) of 93%, and accuracy 76% (68 false positive and 15 false negative). Per-patient analysis had sensitivity 94%, specificity 55%, PPV 63%, NPV 92%, and accuracy 72% (30 false-positive and 3 false-negative). Inclusion of uninterpretable segments had variable effect on sensitivity and specificity, depending on whether they are considered as significant or non-significant stenosis.
CONCLUSIONS CONCLUSIONS
In patients with very extensive CAC (>1000 Agatston units), CCTA retained a negative predictive value ​> ​90% to identify lack of significant stenosis on a per-vessel and per-patient level, but frequently overestimated stenosis.

Identifiants

pubmed: 33775584
pii: S1934-5925(21)00037-X
doi: 10.1016/j.jcct.2021.03.007
pmc: PMC8403134
mid: NIHMS1687935
pii:
doi:

Substances chimiques

Calcium SY7Q814VUP

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

412-418

Subventions

Organisme : Doris Duke Charitable Foundation
ID : 2020059
Pays : United States
Organisme : NHLBI NIH HHS
ID : T32 HL116273
Pays : United States

Informations de copyright

Copyright © 2021 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors report no conflicts of interest.

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Auteurs

Alan C Kwan (AC)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA.

Heidi Gransar (H)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA.

Evangelos Tzolos (E)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA; BHF Centre for Cardiovascular Science, University of Edinburgh,Edinburgh,United Kingdom, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK.

Billy Chen (B)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA.

Yuka Otaki (Y)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA.

Eyal Klein (E)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA.

Adele J Pope (AJ)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA.

Donghee Han (D)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA.

Andrew Howarth (A)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA; Department of Cardiac Sciences, University of Calgary,Calgary AB,Canada, 2500, University Dr. NW, Calgary, Alberta, T2N 1N4, Canada.

Nishita Jain (N)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA.

Damini Dey (D)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA.

Robert Jh Miller (RJ)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA; Department of Cardiac Sciences, University of Calgary,Calgary AB,Canada, 2500, University Dr. NW, Calgary, Alberta, T2N 1N4, Canada.

Victor Cheng (V)

Department of Cardiology and Cardiovascular Imaging, Minneapolis Heart Institute, Minneapolis, MN, 800 E 28th St, Minneapolis, MN, 55407, USA.

Babak Azarbal (B)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA.

Daniel S Berman (DS)

Department of Imaging, Medicine, Smidt Heart Institute, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA. Electronic address: Daniel.berman@cshs.org.

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