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  3. Rationale and design of the CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) study.
 

Rationale and design of the CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) study.

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BORIS DOI
10.48350/188812
Publisher DOI
10.1016/j.jcct.2023.10.004
PubMed ID
37951725
Description
BACKGROUND

In the last 15 years, large registries and several randomized clinical trials have demonstrated the diagnostic and prognostic value of coronary computed tomography angiography (CCTA). Advances in CT scanner technology and developments of analytic tools now enable accurate quantification of coronary artery disease (CAD), including total coronary plaque volume (TPV) and low attenuation plaque volume (LAP). The primary aim of CONFIRM2, (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) is to perform comprehensive quantification of CCTA findings, including coronary, non-coronary cardiac, non-cardiac vascular, non-cardiac findings, and relate them to clinical variables and cardiovascular clinical outcomes.

DESIGN

CONFIRM2 is a multicenter, international observational cohort study designed to evaluate multidimensional associations between quantitative phenotype of cardiovascular disease and future adverse clinical outcomes in subjects undergoing clinically indicated CCTA. The targeted population is heterogenous and includes patients undergoing CCTA for atherosclerotic evaluation, valvular heart disease, congenital heart disease or pre-procedural evaluation. Automated software will be utilized for quantification of coronary plaque, stenosis, vascular morphology and cardiac structures for rapid and reproducible tissue characterization. Up to 30,000 patients will be included from up to 50 international multi-continental clinical CCTA sites and followed for 3-4 years.

SUMMARY

CONFIRM2 is one of the largest CCTA studies to establish the clinical value of a multiparametric approach to quantify the phenotype of cardiovascular disease by CCTA using automated imaging solutions.
Date of Publication
2024
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
Keyword(s)
Artificial intelligence Atherosclerosis Computed tomography angiography Coronary artery disease Machine-learning Prognosis
Language(s)
en
Contributor(s)
van Rosendael, Alexander R
Crabtree, Tami
Bax, Jeroen J
Nakanishi, Rine
Mushtaq, Saima
Pontone, Gianluca
Andreini, Daniele
Buechel, Ronny R
Gräni, Christoph
Universitätsklinik für Kardiologie
Feuchtner, Gudrun
Patel, Toral R
Choi, Andrew D
Al-Mallah, Mouaz
Nabi, Faisal
Karlsberg, Ronald P
Rochitte, Carlos E
Alasnag, Mirvat
Hamdan, Ashraf
Cademartiri, Filippo
Marques, Hugo
Kalra, Dinesh
German, David M
Gupta, Himanshu
Hadamitzky, Martin
Deaño, Roderick C
Khalique, Omar
Knaapen, Paul
Hoffmann, Udo
Earls, James
Min, James K
Danad, Ibrahim
Additional Credits
Universitätsklinik für Kardiologie
Series
Journal of cardiovascular computed tomography
Publisher
Elsevier
ISSN
1876-861X
Access(Rights)
open.access
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