Tsao CW, Aday AW, Almarzooq ZI et al (2023) Heart disease and stroke statistics-2023 update: a report from the American Heart Association. Circulation 147:e93–e621. https://doi.org/10.1161/CIR.0000000000001123
Conte E, Annoni A, Pontone G et al (2017) Evaluation of coronary plaque characteristics with coronary computed tomography angiography in patients with non-obstructive coronary artery disease: a long-term follow-up study. Eur Heart J Cardiovasc Imaging 18:1170–1178. https://doi.org/10.1093/ehjci/jew200
Wang ZJ, Zhang LL, Elmariah S et al (2017) Prevalence and prognosis of nonobstructive coronary artery disease in patients undergoing coronary angiography or coronary computed tomography angiography: a meta-analysis. Mayo Clin Proc 92:329–346. https://doi.org/10.1016/j.mayocp.2016.11.016
Tomaniak M, Katagiri Y, Modolo R et al (2020) Vulnerable plaques and patients: state-of-the-art. Eur Heart J 41:2997–3004. https://doi.org/10.1093/eurheartj/ehaa227
Article PubMed PubMed Central Google Scholar
Erlinge D, Maehara A, Ben-Yehuda O et al (2021) Identification of vulnerable plaques and patients by intracoronary near-infrared spectroscopy and ultrasound (PROSPECT II): a prospective natural history study. Lancet 397:985–995. https://doi.org/10.1016/S0140-6736(21)00249-X
Article CAS PubMed Google Scholar
Antonopoulos AS, Angelopoulos A, Tsioufis K et al (2022) Cardiovascular risk stratification by coronary computed tomography angiography imaging: current state-of-the-art. Eur J Prev Cardiol 29:608–624. https://doi.org/10.1093/eurjpc/zwab067
Won K-B, Lee S-E, Lee BK et al (2019) Longitudinal assessment of coronary plaque volume change related to glycemic status using serial coronary computed tomography angiography: a PARADIGM (Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging) substudy. J Cardiovasc Comput 13:142–147. https://doi.org/10.1016/j.jcct.2018.12.002
Hell MM, Motwani M, Otaki Y et al (2017) Quantitative global plaque characteristics from coronary computed tomography angiography for the prediction of future cardiac mortality during long-term follow-up. Eur Heart J Cardiovasc Imaging 18:1331–1339. https://doi.org/10.1093/ehjci/jex183
Article PubMed PubMed Central Google Scholar
Gu SZ, Bennett MR (2022) Plaque structural stress: detection, determinants and role in atherosclerotic plaque rupture and progression. Front Cardiovasc Med 9:875413. https://doi.org/10.3389/fcvm.2022.875413
Article PubMed PubMed Central Google Scholar
Yang S, Hoshino M, Koo B-K et al (2022) Relationship of plaque features at coronary CT to coronary hemodynamics and cardiovascular events. Radiology 305:578–587. https://doi.org/10.1148/radiol.213271
Wang J, Zhou L, Chen H et al (2022) Predicting major adverse cardiac events based on multi-parameter coronary computed tomography angiography. Med Phys 49:3612–3623. https://doi.org/10.1002/mp.15616
Zhuang B, Wang S, Zhao S, Lu M (2020) Computed tomography angiography-derived fractional flow reserve (CT-FFR) for the detection of myocardial ischemia with invasive fractional flow reserve as reference: systematic review and meta-analysis. Eur Radiol 30:712–725. https://doi.org/10.1007/s00330-019-06470-8
Fischer AM, van Assen M, Schoepf UJ et al (2021) Non-invasive fractional flow reserve (FFRCT) in the evaluation of acute chest pain - Concepts and first experiences. Eur J Radiol 138:109633. https://doi.org/10.1016/j.ejrad.2021.109633
Kalykakis G-E, Antonopoulos AS, Pitsargiotis T et al (2021) Relationship of endothelial shear stress with plaque features with coronary CT angiography and vasodilating capability with PET. Radiology 300:549–556. https://doi.org/10.1148/radiol.2021204381
Toba T, Otake H, Choi G et al (2021) Wall shear stress and plaque vulnerability: computational fluid dynamics analysis derived from cCTA and OCT. JACC Cardiovasc Imaging 14:315–317. https://doi.org/10.1016/j.jcmg.2020.07.034
Yang S, Choi G, Zhang J et al (2021) Association among local hemodynamic parameters derived from CT angiography and their comparable implications in development of acute coronary syndrome. Front Cardiovasc Med 8:713835. https://doi.org/10.3389/fcvm.2021.713835
Article PubMed PubMed Central Google Scholar
Lee JM, Choi G, Koo B-K et al (2019) Identification of high-risk plaques destined to cause acute coronary syndrome using coronary computed tomographic angiography and computational fluid dynamics. JACC Cardiovasc Imaging 12:1032–1043. https://doi.org/10.1016/j.jcmg.2018.01.023
Li M, Ling R, Yu L et al (2023) Deep learning segmentation and reconstruction for CT of chronic total coronary occlusion. Radiology 306:e221393. https://doi.org/10.1148/radiol.221393
Yang W, Chen C, Yang Y et al (2023) Diagnostic performance of deep learning-based vessel extraction and stenosis detection on coronary computed tomography angiography for coronary artery disease: a multi-reader multi-case study. Radiol Med 128:307–315. https://doi.org/10.1007/s11547-023-01606-9
Williams MC, Moss AJ, Dweck M et al (2019) Coronary artery plaque characteristics associated with adverse outcomes in the SCOT-HEART study. J Am Coll Cardiol 73:291–301. https://doi.org/10.1016/j.jacc.2018.10.066
Article PubMed PubMed Central Google Scholar
Motoyama S, Ito H, Sarai M et al (2015) Plaque characterization by coronary computed tomography angiography and the likelihood of acute coronary events in mid-term follow-up. J Am Coll Cardiol 66:337–346. https://doi.org/10.1016/j.jacc.2015.05.069
Lee SH, Hong D, Dai N et al (2022) Anatomic and hemodynamic plaque characteristics for subsequent coronary events. Front Cardiovasc Med 9:871450. https://doi.org/10.3389/fcvm.2022.871450
Article CAS PubMed PubMed Central Google Scholar
Zeng Y, Wang X, Tang Z et al (2024) Diagnostic accuracy of CT-FFR with a new coarse-to-fine subpixel algorithm in detecting lesion-specific ischemia: a prospective multicenter study. Rev Esp Cardiol (Engl Ed) 77:129–137. https://doi.org/10.1016/j.rec.2023.05.008
Dai N, Chen Z, Zhou F et al (2022) Association of lipoprotein (a) with coronary-computed tomography angiography-assessed high-risk coronary disease attributes and cardiovascular outcomes. Circ Cardiovasc Imaging 15:e014611. https://doi.org/10.1161/CIRCIMAGING.122.014611
Lee JM, Choi KH, Koo B-K et al (2019) Prognostic implications of plaque characteristics and stenosis severity in patients with coronary artery disease. J Am Coll Cardiol 73:2413–2424. https://doi.org/10.1016/j.jacc.2019.02.060
Thomsen C, Abdulla J (2016) Characteristics of high-risk coronary plaques identified by computed tomographic angiography and associated prognosis: a systematic review and meta-analysis. Eur Heart J Cardiovasc Imaging 17:120–129. https://doi.org/10.1093/ehjci/jev325
Williams MC, Kwiecinski J, Doris M et al (2020) Low-attenuation noncalcified plaque on coronary computed tomography angiography predicts myocardial infarction: results from the multicenter SCOT-HEART trial (Scottish Computed Tomography of the HEART). Circulation 141:1452. https://doi.org/10.1161/CIRCULATIONAHA.119.044720
Article CAS PubMed PubMed Central Google Scholar
Choi G, Lee JM, Kim H-J et al (2015) Coronary artery axial plaque stress and its relationship with lesion geometry: application of computational fluid dynamics to coronary CT angiography. JACC Cardiovasc Imaging 8:1156–1166. https://doi.org/10.1016/j.jcmg.2015.04.024
Cameron JN, Mehta OH, Michail M et al (2020) Exploring the relationship between biomechanical stresses and coronary atherosclerosis. Atherosclerosis 302:43–51. https://doi.org/10.1016/j.atherosclerosis.2020.04.011
留言 (0)