2019 Novel Coronavirus (COVID-19) Pneumonia: Serial Computed Tomography Findings

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new virus recently isolated from humans. SARS-CoV-2 was discovered to be the pathogen responsible for a cluster of pneumonia associated with severe respiratory disease occurred in December 2019 in China. This novel pulmonary infection, formally called coronavirus disease 2019 (COVID-19), has spread rapidly in China and beyond. On 8 March 2020, the number of Italians with SARS-CoV-2 infection was 7375 with a 48% hospitalization rate. At present, chest computed tomography imaging is considered the most effective method for detection of lung abnormalities in early-stage disease and for quantitative assessment of severity and progression of COVID-19 infection. Although chest x-ray (CXR) is considered not sensitive for the detection of pulmonary involvement in the early stage of disease, we believe that, in the current emergency setting, CXR can be a useful diagnostic tool for monitoring the rapid progression of lung abnormalities in infected patients, particularly in intensive care units. In this article we present our experimental CXR scoring system that we are applying in hospitalized patients with COVID-19 pneumonia to quantify and monitor the severity and progression of this new infectious disease. We also present the results of our preliminary validation study on a sample of 100 hospitalized patients with SARS-CoV-2 infection for whom the final outcome (recovery or death) was available.

COVID-19 outbreak in Italy: experimental chest X-ray scoring system for quantifying and monitoring disease progression

“…Computed tomography (CT) imaging is considered the most effective method for the detection of lung abnormalities, particularly in the early stage of the disease [4,[6][7][8][9][10][11][12]. Moreover, serial chest CT imaging with different time intervals (from three to seven days) is also effective in assessing the disease progression (from the time of initial diagnosis of COVID-19 until patient discharge) [6,7,13].…”

Prediction of the Development of Pulmonary Fibrosis Using Serial Thin-Section CT and Clinical Features in Patients Discharged after Treatment for COVID-19 Pneumonia

“…Thin-section chest CT scans have been contributing greatly to the disease assessment and patient condition surveillance in relation to . Researchers in radiology have reported that typical imaging features of COVID-19 patients include ground-glass opacity (GGO) (6,7), crazy-paving pattern, and consolidation (8). Once discharged, a sizable amount of patients had almost no CT abnormalities (9); yet many still demonstrated apparent residual parenchymal abnormalities on follow-up chest CT scans (10).…”

Clinical features, Diagnosis, and Treatment of COVID-19: A systematic review of case reports and case series

“…It is important to highlight that 134 the CT scan can be normal during initial days, and a normal CT scan in a suspected case would 135 never definitely rule out the diagnosis of COVID-19 [18]. Moreover, the CT scan is dynamic in 136 patients with COVID-19 and changes rapidly [19][20][21]. The earliest abnormal finding in the CT 137 scan is the appearance of ground-glass opacities in peripheral and sub-pleural areas [22].…”

“…Lastly, 180 there are different therapeutic strategies for COVID-19 patients, but we don't have enough data 181 for their efficacy. Additional investigations including randomized controlled trials will be 182 necessary to further our understanding in the treatment of COVID- 19…”