Abstract
COVID-19 disease, caused by the SARS-CoV-2 virus, was identified in December 2019 in China and declared a global pandemic in all over the world. Since then, many investigators have trying to determine its' epidemiology, etiology,pathophysiology, radiological manifestations, therapeutic strategies and outcome prediction, etc. In addition, a few academic societies as well as academic institution had proposed some category classifications for assessing COVID-19 pneumonia,and many clinicians reported their utility in routine clinical practice. Moreover, artificial Intelligence (AI) is a potentially powerful tool in the fight against the COVID-19 pandemic, when considering the above-mentioned situation in Chest Radiology. For present purposes, AI can currently be tried to demonstrate its' clinical utility for diagnosis, disease severity evaluation and treatment response assessment for radiological examination in patients with COVID-19 infection. Then,many papers have been reported radiological features as well as clinical features of COVID-19 infection, development, and clinical application of AI system for chest radiograph (or chest X-ray : CXR) or computed tomography (CT) in not only China, but also other Western countries including Japan and Korea. Encouraging for developments and clinical studies for AI may contribute to not only clinicians, but also radiologists for improving clinical practice in patients with COVID-19 infection. Moreover, AI is required a careful balance between data privacy and public health concerns, and more rigorous human-AI interaction. So, the progress of AI is very important for future control of COVID-19 infection in routine clinical practice.
In this article, we discuss 1) radiological manifestation of COVID-19 pneumonia on CXR or CT, 2) current clinical indication for CT examination in suspected COVID-19 patients, 3) previously published categorization for probability of COVID-19 pneumonia on CT (or CXR) by a few academic societies or institutions and 4) current status and future direction of AI for radiological assessment in patients with COVID-19.
