TY - JOUR
T1 - Differential progression of coronary atherosclerosis according to plaque composition
T2 - a cluster analysis of PARADIGM registry data
AU - Yoon, Yeonyee E.
AU - Baskaran, Lohendran
AU - Lee, Benjamin C.
AU - Pandey, Mohit Kumar
AU - Goebel, Benjamin
AU - Lee, Sang Eun
AU - Sung, Ji Min
AU - Andreini, Daniele
AU - Al-Mallah, Mouaz H.
AU - Budoff, Matthew J.
AU - Cademartiri, Filippo
AU - Chinnaiyan, Kavitha
AU - Choi, Jung Hyun
AU - Chun, Eun Ju
AU - Conte, Edoardo
AU - Gottlieb, Ilan
AU - Hadamitzky, Martin
AU - Kim, Yong Jin
AU - Lee, Byoung Kwon
AU - Leipsic, Jonathon A.
AU - Maffei, Erica
AU - Marques, Hugo
AU - de Araújo Gonçalves, Pedro
AU - Pontone, Gianluca
AU - Shin, Sanghoon
AU - Narula, Jagat
AU - Bax, Jeroen J.
AU - Lin, Fay Yu Huei
AU - Shaw, Leslee
AU - Chang, Hyuk Jae
N1 - © 2021. The Author(s).
PY - 2021/8/24
Y1 - 2021/8/24
N2 - 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.
AB - 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.
KW - Aged
KW - Cluster Analysis
KW - Coronary Angiography
KW - Coronary Artery Disease/diagnostic imaging
KW - Female
KW - Humans
KW - Male
KW - Middle Aged
KW - Plaque, Atherosclerotic/classification
KW - Vascular Calcification/diagnostic imaging
UR - http://www.scopus.com/inward/record.url?scp=85113344323&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113344323&partnerID=8YFLogxK
U2 - 10.1038/s41598-021-96616-w
DO - 10.1038/s41598-021-96616-w
M3 - Article
C2 - 34429500
AN - SCOPUS:85113344323
SN - 2045-2322
VL - 11
SP - 17121
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 17121
ER -