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Cardiovascular disease remains an integral field on which new research in both the biomedical and technological fields is based, as it remains the leading cause of mortality and morbidity worldwide. However, despite the progress of cardiac imaging techniques, the heart remains a challenging organ to study. Artificial intelligence (AI) has emerged as one of the major innovations in the field of diagnostic imaging, with a dramatic impact on cardiovascular magnetic resonance imaging (CMR). AI will be increasingly present in the medical world, with strong potential for greater diagnostic efficiency and accuracy. Regarding the use of AI in image acquisition and reconstruction, the main role was to reduce the time of image acquisition and analysis, one of the biggest challenges concerning magnetic resonance; moreover, it has been seen to play a role in the automatic correction of artifacts. The use of these techniques in image segmentation has allowed automatic and accurate quantification of the volumes and masses of the left and right ventricles, with occasional need for manual correction. Furthermore, AI can be a useful tool to directly help the clinician in the diagnosis and derivation of prognostic information of cardiovascular diseases. This review addresses the applications and future prospects of AI in CMR imaging, from image acquisition and reconstruction to image segmentation, tissue characterization, diagnostic evaluation, and prognostication.

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(1) Background: Glucagone-Like Peptide-1 Receptor Agonists (GLP-1 RAs) (GLP-1 RAs) are incretine-based medications recommended in the treatment of type 2 Diabetes Mellitus (DM2) with atherosclerotic cardiovascular disease (ASCVD) or high or very high cardiovascular (CV) risk. However, knowledge of the direct mechanism of GLP-1 RAs on cardiac function is modest and not yet fully elucidated. Left ventricular (LV) Global Longitudinal Strain (GLS) with Speckle Tracking Echocardiography (STE) represents an innovative technique for the evaluation of myocardial contractility. (2) Methods: an observational, perspective, monocentric study was conducted in a cohort of 22 consecutive patients with DM2 and ASCVD or high/very high CV risk, enrolled between December 2019 and March 2020 and treated with GLP-1 RAs dulaglutide or semaglutide. The echocardiographic parameters of diastolic and systolic function were recorded at baseline and after six months of treatment. (3) Results: the mean age of the sample was 65 ± 10 years with a prevalence of the male sex (64%). A significant improvement in the LV GLS (mean difference: −1.4 ± 1.1%; p value < 0.001) was observed after six months of treatment with GLP-1 RAs dulaglutide or semaglutide. No relevant changes were seen in the other echocardiographic parameters. (4) Conclusions: six months of treatment with GLP-1 RAs dulaglutide or semaglutide leads to an improvement in the LV GLS in subjects with DM2 with and high/very high risk for ASCVD or with ASCVD. Further studies on larger populations and with a longer follow-up are warranted to confirm these preliminary results.

The diagnosis of acute myocarditis often involves several noninvasive techniques that can provide information regarding volumes, ejection fraction, and tissue characterization. In particular, echocardiography is extremely helpful for the evaluation of biventricular volumes, strain and ejection fraction. Cardiac magnetic resonance, beyond biventricular volumes, strain, and ejection fraction allows to characterize myocardial tissue providing information regarding edema, hyperemia, and fibrosis. Contemporary cardiac computed tomography angiography (CCTA) can not only be extremely important for the assessment of coronary arteries, pulmonary arteries and aorta but also tissue characterization using CCTA can be an additional tool that can explain chest pain with a diagnosis of myocarditis.