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Purpose: Artificial intelligence could play a key role in cardiac imaging analysis. To evaluate the diagnostic accuracy of a deep learning (DL) algorithm predicting hemodynamically significant coronary artery disease (CAD) by using a rest dataset of myocardial computed tomography perfusion (CTP) as compared to invasive evaluation. Methods: One hundred and twelve consecutive symptomatic patients scheduled for clinically indicated invasive coronary angiography (ICA) underwent CCTA plus static stress CTP and ICA with invasive fractional flow reserve (FFR) for stenoses ranging between 30% and 80%. Subsequently, a DL algorithm for the prediction of significant CAD by using the rest dataset (CTP-DLrest) and stress dataset (CTP-DLstress) was developed. The diagnostic accuracy for identification of significant CAD using CCTA, CCTA+CTPStress, CCTA+CTP-DLrest, and CCTA+CTP-DLstress were measured and compared. The time of analysis for CTPStress, CTP-DLrest and CTP-DLStress were recorded. Results: Patient-specific sensitivity, specificity, NPV, PPV, accuracy and area under the curve (AUC) of CCTA alone and CCTA+CTPStress were 100%, 33%, 100%, 54%, 63%, 67% and 86%, 89%, 89%, 86%, 88%, 87%, respectively. Patient-specific sensitivity, specificity, NPV, PPV, accuracy and AUC of CCTA+DLrest and CCTA+DLstress were 100%, 72%, 100%, 74%, 84%, 96% and 93%, 83%, 94%, 81%,88%,98%, respectively. All CCTA+CTPStress, CCTA+CTP-DLRest and CCTA+CTP-DLStress significantly improved detection of hemodynamically significant CAD (pConclusion: Evaluation of myocardial ischemia using a DL approach on rest CTP datasets is feasible and accurate. This approach may be a useful gatekeeper prior to CTPStress.

Background: Despite the low spatial resolution of 2D-multisegment late gadolinium enhancement (2D-MSLGE) sequences, it may be useful in uncooperative patients instead of standard 2D single segmented inversion recovery gradient echo late gadolinium enhancement sequences (2D-SSLGE). The aim of the study is to assess the feasibility and comparison of 2D-MSLGE reconstructed with artificial intelligence reconstruction deep learning noise reduction (NR) algorithm compared to standard 2D-SSLGE in consecutive patients with ischemic cardiomyopathy (ICM). Methods: Fifty-seven patients with known ICM referred for a clinically indicated CMR were enrolled in this study. 2D-MSLGE were reconstructed using a growing level of NR (0%,25%,50%,75%and 100%). Subjective image quality, signal to noise ratio (SNR) and contrast to noise ratio (CNR) were evaluated in each dataset and compared to standard 2D-SSLGE. Moreover, diagnostic accuracy, LGE mass and scan time were compared between 2D-MSLGE with NR and 2D-SSLGE. Results: The application of NR reconstruction ≥50% to 2D-MSLGE provided better subjective image quality, CNR and SNR compared to 2D-SSLGE (p < 0.01). The best compromise in terms of subjective and objective image quality was observed for values of 2D-MSLGE 75%, while no differences were found in terms of LGE quantification between 2D-MSLGE versus 2D-SSLGE, regardless the NR applied. The sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 2D-MSLGE NR 75% were 87.77%,96.27%,96.13%,88.16% and 94.22%, respectively. Time of acquisition of 2D-MSLGE was significantly shorter compared to 2D-SSLGE (p < 0.01). Conclusion: When compared to standard 2D-SSLGE, the application of NR reconstruction to 2D-MSLGE provides superior image quality with similar diagnostic accuracy.

Cardiac computed tomography angiography (CCTA) is widely used as a diagnostic tool for evaluation of coronary artery disease (CAD). Despite the excellent capability to rule-out CAD, CCTA may overestimate the degree of stenosis; furthermore, CCTA analysis can be time consuming, often requiring advanced postprocessing techniques. In consideration of the most recent ESC guidelines on CAD management, which will likely increase CCTA volume over the next years, new tools are necessary to shorten reporting time and improve the accuracy for the detection of ischemia-inducing coronary lesions. The application of artificial intelligence (AI) may provide a helpful tool in CCTA, improving the evaluation and quantification of coronary stenosis, plaque characterization, and assessment of myocardial ischemia. Furthermore, in comparison with existing risk scores, machine-learning algorithms can better predict the outcome utilizing both imaging findings and clinical parameters. Medical AI is moving from the research field to daily clinical practice, and with the increasing number of CCTA examinations, AI will be extensively utilized in cardiac imaging. This review is aimed at illustrating the state of the art in AI-based CCTA applications and future clinical scenarios.

Objectives: Computed tomography (CT) provides excellent anatomy assessment of the aortic annulus (AoA) and is utilized for pre-procedural planning of transcatheter aortic valve implantation (TAVI). We sought to investigate if geometrical characteristics of the AoA determined by CT may represent predictors of structural valve degeneration (SVD) in patients undergoing TAVI with balloon-expandable valves. Methods: This is a retrospective study on 124 consecutive patients (mean age: 79 ± 7 years; female: 61%) undergoing balloon-expandable TAVI prospectively enrolled in a registry. AoA maximum diameter (Dmax), minimum diameter (Dmin), and area were assessed using pre-procedural CT. SVD was identified during follow-up with transthoracic echocardiography documenting structural prosthetic valve abnormalities with or without hemodynamic changes. Results: The mean follow-up was 5.9 ± 1.7 years. SVD was found in 48 out of 124 patients (38%). AoA Dmax, Dmin, and area were significantly smaller in patients with SVD compared to patients without SVD (25.6 ± 2.2 mm vs. 27.1 ± 2.8 mm, p = 0.012; 20.5 ± 2.1 mm vs. 21.8 ± 2.1 mm, p = 0.001 and 419 ± 77 mm2 vs. 467 ± 88 mm2, p = 0.002, respectively). At univariable analysis, female sex, BSA, 23-mm prosthetic valve size, Dmax < 27.1 mm, and a Dmin < 19.9 mm were associated with SVD, whereas at multivariable analysis, only Dmin < 19.9 mm (OR = 2.873, 95% CI: 1.191–6.929, p = 0.019) and female sex (OR = 2.659, 95% CI: 1.095–6.458, p = 0.031) were independent predictors of SVD. Conclusions: Female sex and AoA Dmin < 19.9 mm are associated with SVD in patients undergoing TAVI with balloon-expandable valves. When implanting large prostheses in order to avoid paraprosthetic regurgitation, caution should be observed due to the risk of excessive stretching of the AoA Dmin, which may play a role in SVD. Key Points: • Long-term durability is a concern for transcatheter aortic valve bioprosthesis. • CT provides an excellent assessment of the aortic annulus’s geometrical characteristics for prosthesis sizing before transcatheter aortic valve implantation (TAVI). • Female sex and a small minimum aortic annulus diameter measured with CT are independent predictors of structural valve degeneration in patients undergoing TAVI with balloon-expandable valves.

Ischemic cardiomyopathy (ICM) is one of the most common causes of congestive heart failure. In patients with ICM, tissue characterization with cardiac magnetic resonance imaging (CMR) allows for evaluation of myocardial abnormalities in acute and chronic settings. Myocardial edema, microvascular obstruction (MVO), intracardiac thrombus, intramyocardial hemorrhage, and late gadolinium enhancement of the myocardium are easily depicted using standard CMR sequences. In the acute setting, tissue characterization is mainly focused on assessment of ventricular thrombus and MVO, which are associated with poor prognosis. Conversely, in chronic ICM, it is important to depict late gadolinium enhancement and myocardial ischemia using stress perfusion sequences. Overall, with CMR's ability to accurately characterize myocardial tissue in acute and chronic ICM, it represents a valuable diagnostic and prognostic imaging method for treatment planning. In particular, tissue characterization abnormalities in the acute setting can provide information regarding the patients that may develop major adverse cardiac event and show the presence of ventricular thrombus; in the chronic setting, evaluation of viable myocardium can be fundamental for planning myocardial revascularization. In this review, the main findings on tissue characterization are illustrated in acute and chronic settings using qualitative and quantitative tissue characterization.

Background: We aim to evaluate the value of Cardiac magnetic resonance (CMR) feature tracking (CMR-FT) in addition to Task Force Criteria(TFC) in patients with (arrhythmogenic cardiomyopathy) AC biopsy-proved. Methods: Thirty-five patients with AC histologically proven who performed CMR with late gadolinium enhancement (LGE) acquisition were enrolled. The study population was divided in Group1 (negative CMR TFC and LV ejection fraction≥55%) and Group2 (positive CMR TFC and/or LVEF

The recently published 2019 guidelines on chronic coronary syndromes (CCS) focus on the need for noninvasive imaging modalities to accurately establish the diagnosis of coronary artery disease (CAD) and assess the risk of clinical scenario occurrence. Appropriate patient management should rely on controlling symptoms, improving prognosis, and guiding each therapeutic strategy as well as monitoring disease progress. Among the noninvasive imaging modalities, cardiovascular magnetic resonance (CMR) has gained broad acceptance in past years due to its unique features in providing a complete assessment of CAD through data on cardiac anatomy and function and myocardial viability, with high spatial and temporal resolution and without ionizing radiation. In detail, evaluation of the presence and extent of myocardial ischemia through stress CMR (S-CMR) has shown a high rule-in power in detecting functionally significant coronary artery stenosis in patients suspected of CCS. Moreover, S-CMR technique may add significant prognostic value, as demonstrated by different studies which have progressively evidenced the valuable power of this multiparametric imaging modality in predicting adverse cardiac events. The latest scientific progress supports a greater expansion of S-CMR with improvement of quantitative myocardial perfusion analysis, myocardial strain, and native mapping within the same examination. Although further study is warranted, these techniques, which are currently mostly restricted to the research field, are likely to become increasingly prevalent in the clinical setting with the scope of increasing accuracy in the selection of patients to be sent to invasive revascularization. This review investigates the diagnostic and prognostic role of S-CMR in the context of CAD, by analysing a strong, long-standing, scientific evidence together with an appraisal of new advanced techniques which may potentially enrich CAD management in the next future.

Funding Acknowledgements Type of funding sources: None. Background Stress cardiovascular magnetic resonance (S-CMR) has been recognized as a reliable technique for the diagnosis and prognostic stratification of patients with known or suspected coronary artery disease (CAD). Recently, the novel technique of feature-tracking (FT) strain has been applied to S-CMR in order to improve the risk stratification of patients. However, no data are available on the prognostication role of FT strain in patients undergoing a S-CMR with dypiridamole. Aim of this study is to assess the additional role of FT strain in the long-term risk stratification of a large population of patients with known or suspected CAD undergoing a S-CMR with dypiridamole. Methods 731 consecutive patients (age: 63 ± 10 y, male 84%) with stable typical or atypical symptoms suggesting possible cardiac ischemia underwent dipyridamole S-CMR. The patients were followed up for 5.8 ± 1.2 years. CMR-FT analysis of steady state free precession (SSFP) short and long axis cine images obtained in rest and stress conditions was performed in each patient to obtain 2D global peak systolic rest and stress longitudinal (GLS), circumferential (GCS) and radial strains (GRS). Major adverse cardiac events (MACE) were defined as myocardial infarction and cardiac death. Results MACE occurred in 64 (8.7%) patients. Patients experiencing MACE showed higher indexed left ventricular (LV) end-diastolic (EDVi), end-systolic (ESVi) volumes and lower LV ejection fraction (LVEF), higher late-gadolinium enhancement (LGE) presence and reduced both rest and stress GLS, GCS and GRS. At multivariable analysis, LVEDVi (HR 1,01 [95% CI 1.001-1.022]) and LGE (HR 2.399 [95% CI 1.322-4.355] were independently associated with MACE (p = 0.027 and p = 0.04 respectively). By Kaplan-Meier analysis, patients with stress GLS ≥ -15.35% had significantly reduced event-free survival compared with those with stress GLS < -15.35 (log-rank p = 0.001). A model based on stress GCS > - 15.3% plus LVEDVi showed a similar prognostication value of a model made of LVEDVi plus LGE. Conclusions In patients with known or suspected CAD undergoing S-CMR with dypiridamole, a model based on LVEDVi plus stress GCS owns a prognostication value similar to LVEDVi plus LGE.

Coronavirus disease 2019 (COVID-19) has become a rapid worldwide pandemic. While COVID-19 primarily manifests as an interstitial pneumonia and severe acute respiratory distress syndrome, severe involvement of other organs has been documented. In this article, we will review the role of non-contrast chest computed tomography in the diagnosis, follow-up and prognosis of patients affected by COVID-19 pneumonia with a detailed description of the imaging findings that may be encountered. Given that patients with COVID-19 may also suffer from coagulopathy, we will discuss the role of CT pulmonary angiography in the detection of acute pulmonary embolism. Finally, we will describe more advanced applications of CT in the differential diagnosis of myocardial injury with an emphasis on ruling out acute coronary syndrome and myocarditis., Graphical abstract Central Illustration. CT guided diagnostic-work up of COVID-19 patients with elevated troponin. Cardiac CT is reserved to patients with low and intermediate probability of CAD. Timing the acquisition for the simultaneous evaluation of pulmonary and coronary arteries allows the ruling in/out of both pulmonary embolism and CAD. In case of obstructive CAD the patient will be referred to invasive coronary angiography. Conversely, if obstructive CAD is excluded, an additional delayed acquisition might be obtained for the detection of potential myocardial damage. Alternatively to late iodine enhancement imaging, pre and post-contrast CT phase can be analysed to calculate the ECV. Abbreviations: ACS: acute coronary syndrome; CAD: coronary artery disease; CT: computed tomography; ECG: electrocardiogram; ECV: extracellular volume; ICA: invasive coronary angiography; PE: pulmonary embolism; STEMI: ST elevation myocardial infarction.Image 1

In the context of chronic coronary syndromes (CCS), coronary computed tomography angiography (CCTA) has gained broad acceptance as a noninvasive anatomical imaging tool with ability of excluding coronary stenosis with strong negative predictive value. Atherosclerotic plaque lesions are independent predictors of cardiovascular outcomes in high risk patients with known coronary artery disease (CAD). Calcium detection is commonly expressed through the coronary artery calcium score (CACS), but further research is warranted to confirm the powerness of a CACS-only strategy in both diagnosis and prognosis assessment. Recent studies evidence how defined plaque composition characteristics effectively relate to the risk of plaque instabilization and the overall ischemic burden. Fractional flow reserve from CCTA (FFR-CT) has been demonstrated as a reliable method for noninvasive functional evaluation of coronary lesions severity, while the assessment of perfusion imaging under stress conditions is growing as a useful tool for assessment of myocardial ischemia. Moreover, specific applications in procedural planning of transcatheter valve substitution and follow-up of heart transplantation have gained recent importance. This review illustrates the incremental role of CCTA, which can potentially revolutionize the diagnosis and management pathway within the wide clinical spectrum of CCS.