Morphological, pathophysiological, and hemodynamic predictors of coronary atherosclerotic plaque instability (literature review)
TL;DR
It is concluded that accurate stratification of acute coronary event risk requires an integrative, multifactorial approach that combines imaging findings with hemodynamic and pathophysiological data, and emerging approaches include the application of machine learning and computational modeling.
Abstract
This review summarizes current knowledge of the key determinants of coronary atherosclerotic plaque (CAP) vulnerability. Particular emphasis is placed on morphological markers of plaque instability identified by intravascular imaging techniques, such as optical coherence tomography (OCT) and intravascular ultrasound (IVUS). Hemodynamic predictors of plaque destabilization are considered in detail, including peak cap stress, whole-blood viscosity, and wall shear stress, all of which play crucial roles in the biomechanics of plaque rupture. Pathophysiological processes contributing to instability are also discussed: pro-inflammatory cytokines (TNF-α, IL-1β, IL-6), matrix metalloproteinases (MMP-1, -2, -3, -9, -12), intraplaque hemorrhage, endothelial dysfunction, and plaque erosion. It is highlighted that morphological assessment alone is insufficient for reliable risk prediction, as many plaques with features of vulnerability remain clinically stable. The authors conclude 4 that accurate stratification of acute coronary event risk requires an integrative, multifactorial approach that combines imaging findings with hemodynamic and pathophysiological data. Emerging approaches include the application of machine learning and computational modeling to develop personalized diagnostic and prognostic tools for cardiovascular risk assessment.