Logo do repositório
 
Publicação

Prognostic value of aI-based quantitative coronary CTA vs human reader-based visual assessment: results from the CONFIRM2 registry

2026-01-01Artigo de investigação Acesso aberto
Ver registo simples
dc.contributor.authorRosendael, Alexander van
dc.contributor.authorNakanishi, Rine
dc.contributor.authorBax, Jeroen J.
dc.contributor.authorPontone, Gianluca
dc.contributor.authorMushtaq, Saima
dc.contributor.authorBuechel, Ronny R.
dc.contributor.authorGräni, Christoph
dc.contributor.authorFeuchtner, Gudrun
dc.contributor.authorLacaita, Pietro G.
dc.contributor.authorPatel, Amit R.
dc.contributor.authorSingulane, Cristiane C.
dc.contributor.authorChoi, Andrew D.
dc.contributor.authorAl-Mallah, Mouaz
dc.contributor.authorAndreini, Daniele
dc.contributor.authorKarlsberg, Ronald P.
dc.contributor.authorCho, Geoffrey W.
dc.contributor.authorRochitte, Carlos E.
dc.contributor.authorAlasnag, Mirvat
dc.contributor.authorHamdan, Ashraf
dc.contributor.authorCademartiri, Filippo
dc.contributor.authorMaffei, Erica
dc.contributor.authorMarques, Hugo
dc.contributor.authorGonçalves, Pedro de Araújo
dc.contributor.authorGupta, Himanshu
dc.contributor.authorHadamitzky, Martin
dc.contributor.authorKhalique, Omar
dc.contributor.authorKalra, Dinesh
dc.contributor.authorMills, James D.
dc.contributor.authorNurmohamed, Nick S.
dc.contributor.authorKnaapen, Paul
dc.contributor.authorBudoff, Matthew
dc.contributor.authorShaikh, Kashif
dc.contributor.authorMartin, Enrico
dc.contributor.authorGerman, David M.
dc.contributor.authorFerencik, Maros
dc.contributor.authorOehler, Andrew C.
dc.contributor.authorDeaño, Roderick
dc.contributor.authorNagpal, Prashant
dc.contributor.authorAssen, Marly van
dc.contributor.authorCecco, Carlo N. de
dc.contributor.authorKamperidis, Vasileios
dc.contributor.authorFoldyna, Borek
dc.contributor.authorBrendel, Jan M.
dc.contributor.authorCheng, Victor Y.
dc.contributor.authorBranch, Kelley R.
dc.contributor.authorBittencourt, Marcio
dc.contributor.authorBhatti, Sabha
dc.contributor.authorPolsani, Venkateshwar
dc.contributor.authorWesbey, George
dc.contributor.authorCardoso, Rhanderson
dc.contributor.authorBlankstein, Ron
dc.contributor.authorDelago, Augustin
dc.contributor.authorPursnani, Amit
dc.contributor.authorAlsaid, Amro
dc.contributor.authorSingh, Vasvi
dc.contributor.authorAquino, Melissa
dc.contributor.authorPark, Jisuk
dc.contributor.authorDanad, Ibrahim
dc.date.accessioned2026-01-15T09:24:05Z
dc.date.available2026-01-15T09:24:05Z
dc.date.issued2026-01-01
dc.description.abstractBackground: The severity and extent of whole heart coronary plaque volume and stenosis can be reliably measured by artificial intelligence–guided quantitative coronary computed tomography angiography (AI-QCT). Limited data are available on the potential incremental prognostic value compared with currently recommended qualitative coronary computed tomography angiography (CTA) reads and the coronary artery calcium score (CACS). Objectives: The aim of this study was to evaluate the prognostic value of AI-QCT compared with human coronary CTA reads, including the CAD-RADS (Coronary Artery Disease–Reporting and Data System), CACS, and the modified Duke Index. Methods: CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) is a multicenter, international, observational cohort study of patients undergoing clinically indicated coronary CTA with follow-up for major adverse cardiac events (MACE). Asymptomatic patients and those with cardiac history were excluded. Coronary artery disease presence, extent, and composition were quantified by AI-QCT across the coronary tree, yielding 24 patient-, vessel-, and plaque-level variables. On the basis of prior analyses, noncalcified plaque burden and diameter stenosis were identified as the strongest predictors and combined for statistical modeling as “AI-QCT.” Comparator computed tomography scores included CAD-RADS, CACS, and the modified Duke Index, whereas clinical predictors were summarized in the risk factor–weighted clinical likelihood score. Area under the curve (AUC) and continuous net reclassification index (NRI) were calculated to assess the incremental value. The primary endpoint was MACE (death, myocardial infarction [MI], stroke, heart failure, late revascularization, or hospital stay for unstable angina), and the secondary endpoint was death or MI. Results: In 1,916 patients with all risk scores available, 87 (4.5%) MACE and 27 (1.4%) death/MI events occurred during 3 years of follow-up. There was a stepwise risk increase with higher coronary artery disease classifications with CAD-RADS and CACS. The addition of AI-QCT significantly improved risk stratification for MACE compared with CAD-RADS (AUC: 0.81 vs 0.79; P < 0.001 and NRI: 0.47; P < 0.001), CACS (AUC: 0.79 vs 0.70; P < 0.001 and NRI 0.61; P < 0.001), the modified Duke Index (AUC: 0.81 vs 0.76; P < 0.001 and NRI: 0.52; P < 0.001), and CAD-RADS + CACS model (AUC: 0.81 vs 0.79; P = 0.004 and NRI: 0.54; P < 0.001). AI-QCT also improved discrimination when results were adjusted for the risk factor–weighted clinical likelihood and for the prediction of death/MI. Excluding 195 patients with severe stenosis (?70%), in a multivariable model of CAD-RADS and AI-QCT, only AI-QCT was significantly associated with MACE and death/MI, and AI-QCT significantly improved risk stratification compared with CAD-RADS for MACE (AUC: 0.77 vs 0.72; P < 0.001 and NRI: 0.54; P < 0.001) and death/MI (AUC: 0.81 vs 0.73; P = 0.011 and NRI: 0.69; P = 0.001). Conclusions: AI-QCT provided incremental prognostic information compared with CAD-RADS 2.0, CACS, and the modified Duke Index for the prediction of MACE as well as the secondary endpoint of death or nonfatal MI.eng
dc.identifier.citationRosendael, A. V., Nakanishi, R., Bax, J. J., & Pontone, G. et al. (in press). Prognostic value of aI-based quantitative coronary CTA vs human reader-based visual assessment: results from the CONFIRM2 registry. JACC: Cardiovascular Imaging. https://doi.org/10.1016/j.jcmg.2025.09.021
dc.identifier.doi10.1016/j.jcmg.2025.09.021
dc.identifier.eid105026296281
dc.identifier.issn1936-878X
dc.identifier.othera2e608c1-556c-45ec-b0c4-d31ff8cbbfcc
dc.identifier.pmid41324522
dc.identifier.urihttp://hdl.handle.net/10400.14/56522
dc.language.isoeng
dc.peerreviewedyes
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectArtificial intelligence
dc.subjectCAD-RADS score
dc.subjectCalcium scoring
dc.subjectCoronary CTA
dc.subjectPrognosis
dc.titlePrognostic value of aI-based quantitative coronary CTA vs human reader-based visual assessment: results from the CONFIRM2 registryeng
dc.typeresearch article
dspace.entity.typePublication
oaire.citation.titleJACC: Cardiovascular Imaging
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

Ficheiros

Principais
A mostrar 1 - 1 de 1
Miniatura
Nome:
138192124.pdf
Tamanho:
4.04 MB
Formato:
Adobe Portable Document Format
Ver/Abrir

Coleções

CIIS - Contribuições em Revistas Científicas / Contribution to Journals
FM - Contribuições em Revistas Científicas / Contribution to Journals