From CT to artificial intelligence for complex assessment of plaque-associated risk.

The recent technological developments in the field of cardiac imaging have established coronary computed tomography angiography (CCTA) as a first-line diagnostic tool in patients with suspected coronary artery disease (CAD). CCTA offers robust information on the overall coronary circulation and luminal stenosis, also providing the ability to assess the composition, morphology, and vulnerability of atherosclerotic plaques. In addition, the perivascular adipose tissue (PVAT) has recently emerged as a marker of increased cardiovascular risk. The addition of PVAT quantification to standard CCTA imaging may provide the ability to extract information on local inflammation, for an individualized approach in coronary risk stratification. The development of image post-processing tools over the past several years allowed CCTA to provide a significant amount of data that can be incorporated into machine learning (ML) applications. ML algorithms that use radiomic features extracted from CCTA are still at an early stage. However, the recent development of artificial intelligence will probably bring major changes in the way we integrate clinical, biological, and imaging information, for a complex risk stratification and individualized therapeutic decision making in patients with CAD. This review aims to present the current evidence on the complex role of CCTA in the detection and quantification of vulnerable plaques and the associated coronary inflammation, also describing the most recent developments in the radiomics-based machine learning approach for complex assessment of plaque-associated risk.

Cardiovascular Imaging for Guiding Interventional Therapy in Structural Heart Diseases.

Development of interventional methods has revolutionized the treatment of structural cardiac diseases. Given the complexity of structural interventions and the anatomical variability of various structural defects, novel imaging techniques have been implemented in the current clinical practice for guiding the interventional procedure and for selection of the device to be used. Three- dimensional echocardiography is the most used imaging method that has improved the threedimensional assessment of cardiac structures, and it has considerably reduced the cost of complications derived from malalignment of interventional devices. Assessment of cardiac structures with the use of angiography holds the advantage of providing images in real time, but it does not allow an anatomical description. Transesophageal Echocardiography (TEE) and intracardiac ultrasonography play major roles in guiding Atrial Septal Defect (ASD) or Patent Foramen Ovale (PFO) closure and device follow-up, while TEE is the procedure of choice to assess the flow in the Left Atrial Appendage (LAA) and the embolic risk associated with a decreased flow. On the other hand, contrast CT and MRI have high specificity for providing a detailed description of structure, but cannot assess the flow through the shunt or the valvular mobility. This review aims to present the role of modern imaging techniques in pre-procedural assessment and intraprocedural guiding of structural percutaneous interventions performed to close an ASD, a PFO, an LAA or a patent ductus arteriosus.

Predictors of Mortality in Patients with ST-Segment Elevation Acute Myocardial Infarction and Resuscitated Out-of-Hospital Cardiac Arrest.

INTRODUCTION: In patients with out-of-hospital cardiac arrest (OHCA) complicating an ST-segment elevation myocardial infarction (STEMI), the survival depends largely on the restoration of coronary flow in the infarct related artery. The aim of this study was to determine clinical and angiographic predictors of in-hospital mortality in patients with OHCA and STEMI, successfully resuscitated and undergoing primary percutaneous intervention (PCI). METHODS: From January 2013 to July 2015, 78 patients with STEMI presenting OHCA, successfully resuscitated, transferred immediately to the catheterization unit and treated with primary PCI, were analyzed. Clinical, laboratory and angiographic data were compared in 28 non-survivors and 50 survivors. RESULTS: The clinical baseline characteristics of the study population showed no significant differences between the survivors and non-survivors in respect to age (p=0.06), gender (p=0.8), the presence of hypertension (p=0.4), dyslipidemia (p=0.09) obesity (p=1), smoking status (p=0.2), presence of diabetes (p=0.2), a clinical history of acute myocardial infarction (p=0.7) or stroke (p=0.17). Compared to survivors, the non-survivor group exhibited a significantly higher incidence of cardiogenic shock (50% vs 24%, p=0.02), renal failure (64.3% vs 30.0%, p=0.004) and anaemia (35.7% vs 12.0%, p=0.02). Three-vessel disease was significantly higher in the non-survivor group (42.8% vs. 20.0%, p=0.03), while there was a significantly higher percentage of TIMI 3 flow postPCI in the infarct-related artery in the survivor group (80.% vs. 57.1%, p=0.03). The time from the onset of symptoms to revascularization was significantly higher in patients who died compared to those who survived (387.5 +/- 211.3 minutes vs 300.8 +/- 166.1 minutes, p=0.04), as was the time from the onset of cardiac arrest to revascularization (103.0 +/- 56.34 minutes vs 67.0 +/- 44.4 minutes, p=0.002). Multivariate analysis identified the presence of cardiogenic shock (odds ratio [OR]: 3.17, p=0.02), multivessel disease (OR: 3.0, p=0.03), renal failure (OR: 4.2, p=0.004), anaemia (OR: 4.07, p=0.02), need for mechanical ventilation >48 hours (OR: 8.07, p=0.0002) and a duration of stay in the ICU longer than 5 days (OR: 9.96, p=0.0002) as the most significant independent predictors for mortality in patients with OHCA and STEMI. CONCLUSION: In patients surviving an OHCA in the early phase of a myocardial infarction, the presence of cardiogenic shock, renal failure, anaemia or multivessel disease, as well as a longer time from the onset of symptoms or of cardiac arrest to revascularization, are independent predictors of mortality. However, the most powerful predictor of death is the duration of stay in the ICU and the requirement of mechanical ventilation for more than forty-eight hours.