At present, artificial intelligence (AI) has already been applied in cardiovascular imaging (e.g., image segmentation, automated measurements, and eventually, automated diagnosis) and it has been propelled to the forefront of cardiovascular medical imaging research. In this review, we presented the current status of artificial intelligence applied to image analysis of coronary atherosclerotic plaques, covering multiple areas from plaque component analysis (e.g., identification of plaque properties, identification of vulnerable plaque, detection of myocardial function, and risk prediction) to risk prediction. Additionally, we discuss the current evidence, strengths, limitations, and future directions for AI in cardiac imaging of atherosclerotic plaques, as well as lessons that can be learned from other areas. The continuous development of computer science and technology may further promote the development of this field.

Background. It has been reported that ischemia and ischemic preconditioning (IPC) have different effects on the expression of tuberous sclerosis complex 1 (TSC1), which may contribute to the tolerance to ischemia/hypoxia with the increase of autophagy. The mechanisms of TSC1 differential expression are still unclear under ischemia/IPC conditions in hippocampal Cornu Ammon 1 (CA1) and Cornu Ammon 3 (CA3) area neuronal cells. While we have shown that 5-Aza-CdR, a DNA methyltransferase inhibitor, can upregulate TSC1 and increase hypoxic tolerance by autophagy in vivo and in vitro, in this study, we examined whether DNA methylation was involved in the differential expression of TSC1 in the CA1 and CA3 regions induced by hypoxic preconditioning (HPC). Methods. Level of rapamycin (mTOR) autophagy, a downstream molecular pathway of TSC1/TSC2 complex, was detected in HPC mouse hippocampal CA1 and CA3 areas as well as in the HPC model of mouse hippocampal HT22 cells. DNA methylation level of TSC1 promoter (-720 bp~ -360 bp) was determined in CA1 and CA3 areas by bisulfite-modified DNA sequencing (BMDS). At the same time, autophagy was detected in HT22 cells transfected with GFP-LC3 plasmid. The role of TSC1 in neuroprotection was measured by cell viability and apoptosis, and the role of TSC1 in metabolism was checked by ATP assay and ROS assay in HT22 cells that overexpressed/knocked down TSC1. Results. HPC upregulated the expression of TSC1, downregulated the level of P-mTOR (Ser2448) and P-p70S6K (Thr389), and enhanced the activity of autophagy in both in vivo and in vitro. The increased expression of TSC1 in HPC may depend on its DNA hypomethylation in the promoter region in vivo. HPC also could reduce energy consumption in HT22 cells. Overexpression and knockdown of TSC1 can affect cell viability, cell apoptosis, and metabolism in HT22 cells exposed to hypoxia. Conclusion. TSC1 expression induced by HPC may relate to the downregulation of its DNA methylation level with the increase of autophagy and the decrease of energy demand.

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