Optical coherence tomography (OCT) is the current state-of-the-art intracoronary imaging modality that allows visualization of detailed morphological characteristics of both atherosclerotic plaque and stent. So far, three expert review documents have been released for standardization of OCT image analysis. In the real world, a variety of definitions are being used by different groups and by different core laboratories to analyze OCT findings because of different clinical/procedural contexts in which OCT research has been carried out. This comprehensive overview is aimed to summarize different applicable definitions used by different research groups in plaque and stent analysis using OCT. In addition, it presents readers with a panoramic view to select the best definition of OCT measurement for one's own study purpose. We divided this review article into two parts: Part I - Plaque analysis, and Part II - Stent analysis. The plaque analysis section summarizes the definitions of plaque composition, rupture, erosion, protruding calcific nodules, macrophages, microvessels, and cholesterol crystal. The stent analysis section includes the classification of stent struts, features of neointimal hyperplasia, and other stent-related findings such as tissue protrusion, thrombus, intrastent, and stent edge dissections. In each case of controversy, an explanation for the specific context is provided.
Abstract Purpose: Unrecognized myocardial infarction (UMI) detected by delayed-enhancement cardiac magnetic resonance imaging (DE-CMR) and coronary computed tomography angiographic (CCTA)-derived high-risk features provide prognostic information in patients with chronic coronary syndrome (CCS). However, the relationship between UMI and CCTA-derived characteristics remains elusive. The aim of this study is to assess the prognostic value of UMI on DE-CMR and predictors of UMI using CCTA in patients with CCS. Methods: 181 CCS patients without prior history of myocardial infarction and coronary intervention who underwent both DE-CMR and CCTA before elective PCI were enrolled. The CCTA-derived predictors of UMI and the association of baseline clinical characteristics, CCTA findings, and CMR-derived factors with major adverse cardiovascular events (MACE), defined as death, nonfatal myocardial infarction, unplanned late revascularization, hospitalization for congestive heart failure, and stroke were investigated. Results: UMI was detected in 57 patients (31.5%). ROC analysis revealed the optimal cut-off values of Agastson score and mean pericoronary adipose tissue index (FAI) for predicting the presence of UMI were 397 and − 69.8, respectively. Left ventricular mass, Agatston score > 397, mean FAI >-69.8, positive remodeling of the target lesion, and CCTA-derived stenosis severity were independent predictors of UMI. Patients with UMI were associated with worse prognosis. The risk of MACE significantly increased according to the number of 4 preprocedural CCTA relevant features of UMI. Conclusion 57 patients (31.5%) showed UMI. Preprocedural comprehensive CCTA analysis may help predict the presence of UMI and provide prognostic information in patients with CCS undergoing PCI.
Coronary physiologic assessment is performed to measure coronary pressure, flow, and resistance or their surrogates to enable the selection of appropriate management strategy and its optimization for patients with coronary artery disease. The value of physiologic assessment is supported by a large body of evidence that has led to major recommendations in clinical practice guidelines. This expert consensus document aims to convey practical and balanced recommendations and future perspectives for coronary physiologic assessment for physicians and patients in the Asia-Pacific region based on updated information in the field that including both wire- and image-based physiologic assessment. This is Part 1 of the whole consensus document, which describes the general concept of coronary physiology, as well as practical information on the clinical application of physiologic indices and novel image-based physiologic assessment.
