Intravascular imaging in coronary artery disease

Intravascular imaging methods, such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT), and near-infrared spectroscopy (NIRS), have revolutionized our understanding of coronary pathophysiology and plaque characteristics. This themed collection aims to explore the role of intravascular imaging techniques, artificial intelligence (AI), and treatment strategies in understanding and managing coronary artery disease, with a particular focus on acute coronary syndrome (ACS) and vulnerable plaque. AI algorithms and machine learning techniques have shown tremendous potential in optimizing the analysis of intravascular imaging data. They have the potential to automate plaque characterization, plaque burden, and identify high-risk features, aiding the detection and risk stratification of vulnerable plaques.

This collection seeks to bring together original research, review articles, and case reports that delve into the diagnostic and prognostic value of intravascular imaging, AI applications, and new treatment strategies in ACS, with a special emphasis on the mechanisms (rupture, erosion, calcified nodule, SCAD, spasm, and others) assessment, imaging-guided personalized treatment, the identification and management of vulnerable plaques. The collection will highlight advancements in imaging modalities ( integration of emerging imaging modalities, such as photoacoustic imaging and intravascular magnetic resonance imaging, NIRS, and NIRF) and AI algorithms, shedding light on emerging approaches that may further enhance our ability to detect and treat high-risk plaques, providing a comprehensive overview of the current state of intravascular imaging, AI, and treatment of vulnerable plaque, this collection aims to foster knowledge exchange and drive future research in this exciting and promising field.