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In this review, we describe the technical aspects of artificial intelligence (AI) in cardiac imaging, starting with radiomics, basic algorithms of deep learning and application tasks of algorithms, until recently the availability of the public database. Subsequently, we conducted a systematic literature search for recently published clinically relevant studies on AI in cardiac imaging. As a result, 24 and 14 studies using CT and MRI, respectively, were included and summarized. From these studies, it can be concluded that AI is widely applied in cardiac applications in the clinic, including coronary calcium scoring, coronary CT angiography, fractional flow reserve CT, plaque analysis, left ventricular myocardium analysis, diagnosis of myocardial infarction, prognosis of coronary artery disease, assessment of cardiac function, and diagnosis and prognosis of cardiomyopathy. These advancements show that AI has a promising prospect in cardiac imaging.

Triple negative breast cancer (TNBC) is the deadliest form of breast cancer because it is more aggressive, diagnosed at later stage and more likely to develop local and systemic recurrence. Many patients do not experience adequate tumor control after current clinical treatments involving surgical removal, chemotherapy and/or radiotherapy, leading to disease progression and significantly decreased quality of life. Here we report a new combinatory therapy strategy involving cannabinoid-based medicine and photodynamic therapy (PDT) for the treatment of TNBC. This combinatory therapy targets two proteins upregulated in TNBC: the cannabinoid CB2 receptor (CBR, a G-protein coupled receptor) and translocator protein (TSPO, a mitochondria membrane receptor). We found that the combined CBR agonist and TSPO-PDT treatment resulted in synergistic inhibition in TNBC cell and tumor growth. This combinatory therapy approach provides new opportunities to treat TNBC with high efficacy. In addition, this study provides new evidence on the therapeutic potential of CBR agonists for cancer.

AIM:To investigate the correlation of enhancement features of hepatocellular carcinoma (HCC) revealed by single-level dynamic spiral CT scanning (DSCT) with tumor microvessel density (MVD), and to determine the validity of DSCT in assessing in vivo tumor angiogenic activity of HCC. METHODS:Twenty six HCC patients were diagnosed histopathologically. DSCT was performed for all patients according to standard scanning protocol. Time-density curves were generated, relevant curve parameters were measured, and gross enhancement morphology was analyzed. Operation was performed to remove HCC lesions 1 to 2 weeks following CT scan. Histopathological slides were carefully prepared for the standard F 8 RA immunohistochemical staining and tumor microvessel counting. Enhancement imaging features of HCC lesions were correlatively studied with tumor MVD and its intra-tumor distribution characteristics. RESULTS:On DSCT images of HCC lesions, three patterns of time-density curve and three types of gross enhancement morphology were recognized. Histomorphologically, the distribution of positively stained tumor endothelial cells within tumor was categorized into 3 types. Curve parameters such as peak enhancement value and contrast enhancement ratio were significantly correlated with tumor tissue MVD (r=0.508 and r=0.423, P<0.01 and P<0.05 respectively). Both the pattern of time-density curve and the gross enhancement morphology of HCC lesions were also correlated with tumor MVD, and reflected the distributive features of tumor microvessels within HCC lesions. Correlation between the likelihood of intrahepatic metastasis of HCC lesions with densely enhanced pseudocapsules and rich pseudocapsular tumor MVD was found.CONCLUSION: Enhancement imaging features of HCC lesions on DSCT scanning are correlated with tumor MVD, and reflect the intra-tumor distribution characteristics of tumor microvessels. DSCT is valuable in assessing the angiogenic activity and tumor neovascularity of HCC patients in vivo.Chen WX, Min PQ, Song B, Xiao BL, Liu Y, Ge YH. Single-level dynamic spiral CT of hepatocellular carcinoma: Correlation between imaging features and density of tumor microvessels.