ABSTRACT
Objective@#To identify the initial chest computed tomography (CT) findings and clinical characteristics associated with the course of coronavirus disease 2019 (COVID-19) pneumonia. @*Materials and Methods@#Baseline CT scans and clinical and laboratory data of 72 patients admitted with COVID-19 pneumonia (39 men, 46.2 ± 15.9 years) were retrospectively analyzed. Baseline CT findings including lobar distribution, presence of ground glass opacities, consolidation, linear opacities, and lung severity score were evaluated. The outcome event was recovery with hospital discharge. The time from symptom onset to discharge or the end of follow-up (for those remained hospitalized) was recorded. Data were censored in events such as death or discharge without recovery. Multivariable Cox proportional hazard regression was used to explore the association between initial CT, clinical or laboratory findings, and discharge with recovery, whereby hazard ratio (HR) values 4 vs. ≤ 4 [reference]: adjusted HR = 0.41 [95% confidence interval, CI = 0.18–0.92], p = 0.031) and initial lymphocyte count (reduced vs. normal or elevated [reference]: adjusted HR = 0.14 [95% CI = 0.03–0.60], p = 0.008) were two significant independent factors that influenced recovery and discharge. @*Conclusion@#Lung severity score > 4 and reduced lymphocyte count at initial evaluation were independently associated with a significantly lower rate of recovery and discharge and extended hospitalization in patients admitted for COVID-19 pneumonia.
ABSTRACT
To examine the feasibility of using a computer tool for stratifying the severity of Coronavirus Disease 2019 (COVID-19) based on computed tomography (CT) images. We retrospectively examined 44 confirmed COVID-19 cases. All cases were evaluated separately by radiologists (visually) and through an in-house computer software. The degree of lesions was visually scored by the radiologist, as follows, for each of the 5 lung lobes:0, no lesion present;1,<1/3 involvement;2,>1/3 and<2/3 involvement;and 3,>2/3 involvement. Lesion density was assessed based on the proportion of ground-glass opacity (GGO), consolidation and fibrosis of the lesions. The parameters obtained using the computer tool included lung volume (mL), lesion volume (mL), lesion percentage (％), and mean lesion density (HU) of the whole lung, right lung, left lung, and each lobe. The scores obtained by the radiologists and quantitative results generated by the computer software were tested for correlation. A Chi-square test was used to test the consistency of radiologist- and computer-derived lesion percentage in the right/left lung, upper/lower lobe, and each of the 5 lobes. The results showed a strong to moderate correlation between lesion percentage scores obtained by radiologists and the computer software (r ranged from 0.7679 to 0.8373, P < 0.05), and a moderate correlation between the proportion of GGO and mean lesion density (r=-0.5894, P<0.05), and proportion of consolidation and mean lesion density (r=0.6282, P<0.05). Computer-aided quantification showed a statistical significant higher lesion percentage for lower lobes than that assessed by the radiologists (x2 = 8.160, P = 0.004). Our experiments demonstrated that the computer tool could reliably and accurately assess the severity and distribution of pneumonia on CT scans.