Literature DB >> 31734214

Differences in Progression to Obstructive Lesions per High-Risk Plaque Features and Plaque Volumes With CCTA.

Sang-Eun Lee1, Ji Min Sung2, Daniele Andreini3, Mouaz H Al-Mallah4, Matthew J Budoff5, Filippo Cademartiri6, Kavitha Chinnaiyan7, Jung Hyun Choi8, Eun Ju Chun9, Edoardo Conte3, Ilan Gottlieb10, Martin Hadamitzky11, Yong Jin Kim12, Byoung Kwon Lee13, Jonathon A Leipsic14, Erica Maffei15, Hugo Marques16, Pedro de Araújo Gonçalves16, Gianluca Pontone3, Gilbert L Raff7, Sanghoon Shin17, Peter H Stone18, Habib Samady19, Renu Virmani20, Jagat Narula21, Daniel S Berman22, Leslee J Shaw23, Jeroen J Bax24, Fay Y Lin23, James K Min23, Hyuk-Jae Chang25.   

Abstract

OBJECTIVES: This study explored whether the pattern of nonobstructive lesion progression into obstructive lesions would differ according to the presence of high-risk plaque (HRP).
BACKGROUND: It is still debatable whether HRP simply represents a certain phase during the natural history of coronary atherosclerotic plaques or if disease progression would differ according to the presence of HRP.
METHODS: Patients with nonobstructive coronary artery disease, defined as percent diameter stenosis (%DS) <50%, were enrolled from a prospective, multinational registry of consecutive patients who underwent serial coronary computed tomography angiography at an interscan interval of ≥2 years. HRP was defined as lesions with ≥2 features of positive remodeling, spotty calcification, or low-attenuation plaque. Quantitative total and compositional percent atheroma volume (PAV) at baseline and annualized PAV change were compared between non-HRP and HRP lesions.
RESULTS: A total of 3,049 nonobstructive lesions were identified from 1,297 patients (mean age 60.3 ± 9.3 years; 56.8% men). There were 2,624 non-HRP and 425 HRP lesions. HRP lesions had a greater total PAV and all noncalcified components of PAV and %DS at baseline compared with non-HRP lesions. However, the annualized total PAV changes were greater in non-HRP lesions than in HRP lesions. On multivariate analysis adjusted for clinical risk factors, drug use, change in lipid level, total PAV, %DS, and HRP, only the baseline total PAV and %DS independently predicted the development of obstructive lesions (hazard ratio [HR]: 1.04; 95% confidence interval [CI]: 1.02 to 1.07, and HR: 1.07; 95% CI: 1.04 to 1.10, respectively, all p < 0.05), whereas the presence of HRP did not (p > 0.05).
CONCLUSIONS: The pattern of individual coronary atherosclerotic plaque progression differed according to the presence of HRP. Baseline PAV, not the presence of HRP features, was the most important predictor of lesions developing into obstructive lesions. (Progression of Atherosclerotic Plaque Determined By Computed Tomographic Angiography Imaging [PARADIGM]; NCT02803411).
Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  coronary artery atherosclerosis; coronary artery disease; coronary computed tomography angiography; high-risk plaque

Year:  2019        PMID: 31734214     DOI: 10.1016/j.jcmg.2019.09.011

Source DB:  PubMed          Journal:  JACC Cardiovasc Imaging        ISSN: 1876-7591


  13 in total

Review 1.  Coronary Arterial Function and Disease in Women With No Obstructive Coronary Arteries.

Authors:  Harmony R Reynolds; C Noel Bairey Merz; Colin Berry; Rohit Samuel; Jacqueline Saw; Nathaniel R Smilowitz; Ana Carolina do A H de Souza; Robert Sykes; Viviany R Taqueti; Janet Wei
Journal:  Circ Res       Date:  2022-02-17       Impact factor: 17.367

2.  Quantitative coronary computed tomography angiography assessment of chronic total occlusion percutaneous coronary intervention.

Authors:  Haoran Xing; Lijun Zhang; Dongfeng Zhang; Rui Wang; Jinfan Tian; Yinghui Le; Zhiguo Ju; Hui Chen; Yi He; Xiantao Song
Journal:  Quant Imaging Med Surg       Date:  2022-07

Review 3.  Evolving concepts of the vulnerable atherosclerotic plaque and the vulnerable patient: implications for patient care and future research.

Authors:  Prakriti Gaba; Bernard J Gersh; James Muller; Jagat Narula; Gregg W Stone
Journal:  Nat Rev Cardiol       Date:  2022-09-23       Impact factor: 49.421

4.  Clinical applications of cardiac computed tomography: a consensus paper of the European Association of Cardiovascular Imaging-part II.

Authors:  Gianluca Pontone; Alexia Rossi; Marco Guglielmo; Marc R Dweck; Oliver Gaemperli; Koen Nieman; Francesca Pugliese; Pal Maurovich-Horvat; Alessia Gimelli; Bernard Cosyns; Stephan Achenbach
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2022-03-22       Impact factor: 9.130

Review 5.  Multimodality imaging for the prevention of cardiovascular events: Coronary artery calcium and beyond.

Authors:  Duygu Kocyigit; Alexandra Scanameo; Bo Xu
Journal:  Cardiovasc Diagn Ther       Date:  2021-06

6.  Spotlight from the American Society for Preventive Cardiology on Key Features of the 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guidelines on the Management of Blood Cholesterol.

Authors:  Nathan D Wong; Ezra A Amsterdam; Christie Ballantyne; Amit Khera; Khurram Nasir; Peter P Toth
Journal:  Am J Cardiovasc Drugs       Date:  2020-02       Impact factor: 3.571

Review 7.  SCCT 2021 Expert Consensus Document on Coronary Computed Tomographic Angiography: A Report of the Society of Cardiovascular Computed Tomography.

Authors:  Jagat Narula; Y Chandrashekhar; Amir Ahmadi; Suhny Abbara; Daniel S Berman; Ron Blankstein; Jonathon Leipsic; David Newby; Edward D Nicol; Koen Nieman; Leslee Shaw; Todd C Villines; Michelle Williams; Harvey S Hecht
Journal:  J Cardiovasc Comput Tomogr       Date:  2020-11-20

8.  Association between Admission Hyperglycemia and Culprit Lesion Characteristics in Nondiabetic Patients with Acute Myocardial Infarction: An Intravascular Optical Coherence Tomography Study.

Authors:  Jinying Zhou; Zhaoxue Sheng; Chen Liu; Peng Zhou; Jiannan Li; Runzhen Chen; Li Song; Hanjun Zhao; Hongbing Yan
Journal:  J Diabetes Res       Date:  2020-06-20       Impact factor: 4.011

Review 9.  The Molecular Basis of Predicting Atherosclerotic Cardiovascular Disease Risk.

Authors:  Matthew Nayor; Kemar J Brown; Ramachandran S Vasan
Journal:  Circ Res       Date:  2021-01-21       Impact factor: 17.367

10.  SIRM-SIC appropriateness criteria for the use of Cardiac Computed Tomography. Part 1: Congenital heart diseases, primary prevention, risk assessment before surgery, suspected CAD in symptomatic patients, plaque and epicardial adipose tissue characterization, and functional assessment of stenosis.

Authors:  Antonio Esposito; Marco Francone; Daniele Andreini; Vitaliano Buffa; Filippo Cademartiri; Iacopo Carbone; Alberto Clemente; Andrea Igoren Guaricci; Marco Guglielmo; Ciro Indolfi; Ludovico La Grutta; Guido Ligabue; Carlo Liguori; Giuseppe Mercuro; Saima Mushtaq; Danilo Neglia; Anna Palmisano; Roberto Sciagrà; Sara Seitun; Davide Vignale; Gianluca Pontone; Nazario Carrabba
Journal:  Radiol Med       Date:  2021-06-23       Impact factor: 3.469

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.