Human, All Too Human? An All-Around Appraisal of the "Artificial Intelligence Revolution" in Medical Imaging.

Artificial intelligence (AI) has seen dramatic growth over the past decade, evolving from a niche super specialty computer application into a powerful tool which has revolutionized many areas of our professional and daily lives, and the potential of which seems to be still largely untapped. The field of medicine and medical imaging, as one of its various specialties, has gained considerable benefit from AI, including improved diagnostic accuracy and the possibility of predicting individual patient outcomes and options of more personalized treatment. It should be noted that this process can actively support the ongoing development of advanced, highly specific treatment strategies (e.g., target therapies for cancer patients) while enabling faster workflow and more efficient use of healthcare resources. The potential advantages of AI over conventional methods have made it attractive for physicians and other healthcare stakeholders, raising much interest in both the research and the industry communities. However, the fast development of AI has unveiled its potential for disrupting the work of healthcare professionals, spawning concerns among radiologists that, in the future, AI may outperform them, thus damaging their reputations or putting their jobs at risk. Furthermore, this development has raised relevant psychological, ethical, and medico-legal issues which need to be addressed for AI to be considered fully capable of patient management. The aim of this review is to provide a brief, hopefully exhaustive, overview of the state of the art of AI systems regarding medical imaging, with a special focus on how AI and the entire healthcare environment should be prepared to accomplish the goal of a more advanced human-centered world.

Expected and non-expected immune-related adverse events detectable by CT.

PURPOSE: Cancer treatments with immune checkpoint inhibitors (ICI) are associated with a unique set of drug toxicities called immune-related adverse events (irAES). The aim of the present study was to describe the radiological manifestation of irAES detectable by CT. METHOD: Retrospective analysis of 284 patients treated with ICI for various types of advanced cancer; of them, 129 patients were selected, all having been treated with single-agent ICI, and all with a baseline CT scan and follow-up scans available at our Institute. CT examinations were reviewed by two radiologists involved in the study with a consensus reading. Imaging findings consistent with irAES were reported and correlated with clinical-laboratory data. RESULTS: Immune-related adverse events were found in 25/129 (19.4 %) patients. No statistically significant differences were found in either the prevalence of irAES or in the time of onset of tumour type. Thoracic complications were detected in 14/25 (56.0 %) patients consisting in: 3 radiation recall pneumonia, 3 Transient Asymptomatic Pulmonary Opacities (TAPOs), 3 hypersensitivity pneumonia, 2 diffuse alveolar damage, 2 organizing pneumonia, 1 sarcoid-like reaction. In the remaining 11/25 (44.0 %), there were extra-pulmonary complications: 3 colitis, 4 cholecystitis, 2 pancreatitis and 2 cases of visceral ischemia. CONCLUSIONS: Radiologists should be aware of the wide spectrum of irAES as they could affect the outcome. Pneumonia is the most frequent irAES; however, the international classification for interstitial lung disease does not seem to be capable of describing all possible drug-related pulmonary toxicities. Additional findings included TAPOs, radiation recall pneumonia and sarcoid-like reaction.