RESUMEN
SARS-CoV-2 epidemics has resulted in an unprecedented global health crisis causing a high number of deaths with pneumonia being the most common manifestation. Chest CT is the best imaging modality to identify pulmonary involvement, but unfortunately there are no pathognomonic features for COVID-19 pneumonia, since many other infectious and non-infectious diseases may cause similar alterations. The adoption of artificial intelligence in biomedical imaging has the potential to revolutionize the identification, management, and the patient’s outcome. If adequately validated, it could be used as a support with predictive and prognostic purposes in symptomatic patients but also as a screening test in asymptomatic patients in COVID-19 epidemics. Some studies have already shown the potential adoption of artificial intelligence for detection of COVID-19 infection, or even to differentiate from community-acquired pneumonia, but at present artificial intelligence cannot routinely applied for COVID-19 due to several limitations. This book chapter will first revise the basics of radiomics with a short practical and easy guide for radiologists;then, the main radiological findings of COVID-19 pneumonia will be presented with the most relevant information that are assessed to evaluate extent of the disease;finally, the main current literature on potential clinical application of radiomics and artificial intelligence for COVID-19 will be presented together with limitations and perspectives. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
RESUMEN
Coronavirus disease 2019 (COVID-19) is a newly emerging human infectious disease that has quickly become a worldwide threat to health, mainly causing severe acute respiratory syndrome. In addition to the widely described respiratory syndrome, COVID-19 may cause life-treating complications directly or indirectly related to this infection. Among these, thrombotic complications have emerged as an important issue in patients with COVID-19 infection, particularly in patients in intensive care units. Thrombotic complications due to COVID-19 are likely to occur due to a pro-coagulant pattern encountered in some of these patients or to a progressive endothelial thrombo-inflammatory syndrome causing microvascular disease. In the present authors' experience, from five different hospitals in Italy and the UK, imaging has proved its utility in identifying these COVID-19-related thrombotic complications, with translational clinical relevance. The aim of this review is to illustrate thromboembolic complications directly or indirectly related to COVID-19 disease. Specifically, this review will show complications related to thromboembolism due to a pro-coagulant pattern from those likely related to an endothelial thrombo-inflammatory syndrome.