Use of CT and artificial intelligence in suspected or COVID-19 positive patients: statement of the Italian Society of Medical and Interventional Radiology

Abstract

The COVID-19 pandemic started in Italy in February 2020 with an exponential growth that has exceeded the number of cases reported in China. Italian radiology departments found themselves at the forefront in the management of suspected and positive COVID cases, both in diagnosis, in estimating the severity of the disease and in follow-up. In this context SIRM recommends chest X-ray as first-line imaging tool, CT as additional tool that shows typical features of COVID pneumonia, and ultrasound of the lungs as monitoring tool. SIRM recommends, as high priority, to ensure appropriate sanitation procedures on the scan equipment after detecting any suspected or positive COVID-19 patients. In this emergency situation, several expectations have been raised by the scientific community about the role that artificial intelligence can have in improving the diagnosis and treatment of coronavirus infection, and SIRM wishes to deliver clear statements to the radiological community, on the usefulness of artificial intelligence as a radiological decision support system in COVID-19 positive patients.(1) SIRM supports the research on the use of artificial intelligence as a predictive and prognostic decision support system, especially in hospitalized patients and those admitted to intensive care, and welcomes single center of multicenter studies for a clinical validation of the test. (2) SIRM does not support the use of CT with artificial intelligence for screening or as first-line test to diagnose COVID-19. (3) Chest CT with artificial intelligence cannot replace molecular diagnosis tests with nose-pharyngeal swab (rRT-PCR) in suspected for COVID-19 patients.

Chest CT in the emergency department for suspected COVID-19 pneumonia

“…One false negative was observed in a patient with CT performed within 2 days of symptoms onset, probably related to the known lower prevalence of parenchymal involvement in the earliest stages of disease [ 12 , 13 ]. In our setting, CT specificity and PPV were slightly higher than in most previous reports [ 5 , 10 ], probably in relation to the better clinical selection of patients and high pretest probability of disease in epidemic territories [ 8 , 11 ].…”

“…We retrospectively analyzed 142 chest CT scans performed from March 8 to 30, 2020, at two tertiary-care University Hospitals in patients referring to the EDs for suspected COVID-19 pneumonia, with inconclusive or possible false-negative X-ray results [ 8 ]. Chest CT was performed on a dedicated scanner with a separated access applying standardized protocols for infection control.…”

“…Importantly, one case of H1N1 pneumonia was reported, for the known possibility of overlapping CT findings, highlighting the necessity to provide a microbiological confirmation also in patients with highly suggestive CT findings [ 8 ].…”

Artificial Intelligence for COVID-19: Rapid Review

“…As there is significant overlap in how the lungs respond to different pathological insults [ 33 ], and as radiological presentation often depends on an interplay of multiple factors [ 21 ], the full potential of CT-based AI algorithms may be better realized by including non–image-based clinical data. For now, based on recommendations by the Italian Society of Medical and Interventional Radiology, CT should be used as a screening tool only for symptomatic patients with specific indications, and the use of CT with AI for screening or as a first-line test is not supported [ 43 ].…”

Management reorganization of a Radiology ward during the Covid-19 pandemic in a University Hospital structured inpavilions.

“…What's more, deep learning models applied to CT imaging could be useful to increase speci city and sensitivity to help the Radiologist with the differential diagnosis with community aquired pneumonia and other lung diseases [13].…”