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Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data

Authors :
Sang Eun Lee
Jeroen J. Bax
Mohit Pandey
Filippo Cademartiri
Daniele Andreini
Byoung Kwon Lee
Edoardo Conte
Ji Min Sung
Sanghoon Shin
Leslee J. Shaw
Matthew J. Budoff
Yong Jin Kim
Mouaz H. Al-Mallah
Benjamin Goebel
Jonathon Leipsic
Benjamin C. Lee
Lohendran Baskaran
Gianluca Pontone
Kavitha Chinnaiyan
Eun Ju Chun
Erica Maffei
Martin Hadamitzky
Hugo Marques
Fay Y. Lin
Ilan Gottlieb
Jagat Narula
Yeonyee E. Yoon
Pedro de Araújo Gonçalves
Jung Hyun Choi
Hyuk Jae Chang
Source :
Scientific Reports, Scientific Reports, 11(1). NATURE PORTFOLIO, Scientific reports, vol 11, iss 1, Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Publication Year :
2021
Publisher :
Nature Publishing Group UK, 2021.

Abstract

Patient-specific phenotyping of coronary atherosclerosis would facilitate personalized risk assessment and preventive treatment. We explored whether unsupervised cluster analysis can categorize patients with coronary atherosclerosis according to their plaque composition, and determined how these differing plaque composition profiles impact plaque progression. Patients with coronary atherosclerotic plaque (n = 947; median age, 62 years; 59% male) were enrolled from a prospective multi-national registry of consecutive patients who underwent serial coronary computed tomography angiography (median inter-scan duration, 3.3 years). K-means clustering applied to the percent volume of each plaque component and identified 4 clusters of patients with distinct plaque composition. Cluster 1 (n = 52), which comprised mainly fibro-fatty plaque with a significant necrotic core (median, 55.7% and 16.0% of the total plaque volume, respectively), showed the least total plaque volume (PV) progression (+ 23.3 mm3), with necrotic core and fibro-fatty PV regression (− 5.7 mm3 and − 5.6 mm3, respectively). Cluster 2 (n = 219), which contained largely fibro-fatty (39.2%) and fibrous plaque (46.8%), showed fibro-fatty PV regression (− 2.4 mm3). Cluster 3 (n = 376), which comprised mostly fibrous (62.7%) and calcified plaque (23.6%), showed increasingly prominent calcified PV progression (+ 21.4 mm3). Cluster 4 (n = 300), which comprised mostly calcified plaque (58.7%), demonstrated the greatest total PV increase (+ 50.7mm3), predominantly increasing in calcified PV (+ 35.9 mm3). Multivariable analysis showed higher risk for plaque progression in Clusters 3 and 4, and higher risk for adverse cardiac events in Clusters 2, 3, and 4 compared to that in Cluster 1. Unsupervised clustering algorithms may uniquely characterize patient phenotypes with varied atherosclerotic plaque profiles, yielding distinct patterns of progressive disease and outcome.

Details

Language :
English
ISSN :
20452322
Volume :
11
Database :
OpenAIRE
Journal :
Scientific Reports
Accession number :
edsair.doi.dedup.....daa05dd14c0284e63b20503f12a5080b