Intravascular imaging of coronary artery: Bridging the gap between clinical needs and technical advances

Atherosclerosis plaque tissue classification using self-attention-based conditional variational auto-encoder generative adversarial network using OCT plaque image

Adults with coronary artery disease often have atherosclerosis, this is defined as the accumulation of plaque in the tissues of the arterial wall. Cardiologists utilize optical coherence tomography (OCT), a light-based imaging method, to examine the layers of intracoronary tissue along pathological formations, such as plaque accumulation. Intracoronary cross-sectional images produced by state-of-the-art catheter-based imaging scheme have 10-15 µm high resolution. Nevertheless, interpretation of the obtained images depends on the operator, which takes a lot of time and is exceedingly error-prone from one observer to another. OCT image post-processing that automatically and accurately tags coronary plaques can help the technique become more widely used and lower the diagnostic error rate. To overcome these problems, Atherosclerosis plaque tissue classification using Self-Attention-Based Conditional Variational Auto-Encoder Generative Adversarial Network (APC-OCTPI-SACVAGAN) is proposed which classifies the Atherosclerosis plaque images as Fibro calcific plaque, Fibro atheroma, Thrombus, Fibrous plaque and Micro-vessel. The proposed APC-OCTPI-SACVAGAN technique is executed in MATLAB. The efficiency of proposed APC-OCTPI-SACVAGAN method attains 16.19 %, 17.93 %, 19.81 % and 1.57 % higher accuracy; 16.92 %, 11.54 %, 5.29 % and 1.946 % higher Area under curve; and 28.06 %, 25.32 %, 32.19 % and 39.185 % lower computational time comparing to the existing methods respectively.

Circular RNAs in atherosclerosis

Atherosclerosis (AS) is a chronic inflammatory lesion of the arterial vessel wall caused by a variety of complex factors. Furthermore, it is a major cause of cardiovascular disease and a leading cause of death. Circular RNAs (circRNAs) are a new family of endogenous non-coding RNAs with unique covalently closed loops that have sparked interest due to their unique characteristics and potential diagnostic and therapeutic applications in various diseases. A growing number of studies have shown that circRNAs can be used as biomarkers for the diagnosis and treatment of AS. In this article, we review the biogenesis, classification as well as functions of circRNA and summarize the research on circRNA as a diagnostic biomarker for AS. Finally, we describe the regulatory capacity of circRNA in AS pathogenesis through its pathogenesis and demonstrate the potential therapeutic role of circRNA for AS.