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Background: Coronary computed tomographic angiography (CCTA) is a non-invasive imaging technique that possesses the ability to provide detailed anatomical information about coronary arteries, avoiding unnecessary invasive procedures. Our aim was to assess the ability of CCTA to identify coronary artery disease compared to invasive coronary angiography (ICA) in a real-life setting. Methods: We examined 137 consecutive patients who underwent ICA after CCTA. The latter was conducted in various non-selected centers, and data regarding stenosis were taken from individual reports without further analysis. Results: A total of 60.5% of patients who underwent CCTA were found to have at least one critical stenosis, while the remaining 39.5% underwent ICA due to concurrent clinical or instrumental indications. Among these, 29.5% had angiographically critical pathology, 20.3% underwent a percutaneous coronary intervention (PCI), and 1.8% had coronary artery bypass grafting. Among the 83 patients with positive CCTA results, 34.9% had negative ICA findings. CCTA demonstrated low sensitivity (57.8%) and a positive predictive value of 42.6%. However, it retained high specificity (83.6%) and a negative predictive value of 90.4% for identifying critical stenosis. Among the 18.2% of patients who underwent CCTA without a specific indication, 60% had critical coronary lesions on their ICA and 86.6% of these subsequently underwent a PCI. Conclusions: CCTA performed in non-selective centers has a low concordance with ICA.

The capability of prompt response in the case of critical circumstances occurring within a maritime scenario depends on the awareness level of the competent authorities. From this perspective, a quick and integrated surveillance service represents a tool of utmost importance. This is even more true when the main purpose is to tackle illegal activities such as smuggling, waste flooding, or malicious vessel trafficking. This work presents an improved version of the OSIRIS system, a previously developed Information and Communication Technology framework devoted to understanding the maritime vessel traffic through the exploitation of optical and radar data captured by satellite imaging sensors. A number of dedicated processing units are cascaded with the objective of (i) detecting the presence of vessel targets in the input imagery, (ii) estimating the vessel types on the basis of their geometric and scatterometric features, (iii) estimating the vessel kinematics, (iv) classifying the navigation behavior of the vessel and predicting its route, and, eventually, (v) integrating the several outcomes within a webGIS interface to easily assess the traffic status inside the considered area. The entire processing pipeline has been tested on satellite imagery captured within the Mediterranean Sea or extracted from public annotated datasets.