CT Features of Coronavirus Disease 2019 (COVID-19) Pneumonia in 62 Patients in Wuhan, China.

OBJECTIVE. The purpose of this study was to investigate 62 subjects in Wuhan, China, with laboratory-confirmed coronavirus disease (COVID-19) pneumonia and describe the CT features of this epidemic disease. MATERIALS AND METHODS. A retrospective study of 62 consecutive patients with laboratory-confirmed COVID-19 pneumonia was performed. CT images and clinical data were reviewed. Two thoracic radiologists evaluated the distribution and CT signs of the lesions and also scored the extent of involvement of the CT signs. The Mann-Whitney U test was used to compare lesion distribution and CT scores. The chi-square test was used to compare the CT signs of early-phase versus advanced-phase COVID-19 pneumonia. RESULTS. A total of 62 patients (39 men and 23 women; mean [± SD] age, 52.8 ± 12.2 years; range, 30-77 years) with COVID-19 pneumonia were evaluated. Twenty-four of 30 patients who underwent routine blood tests (80.0%) had a decreased lymphocyte count. Of 27 patients who had their erythrocyte sedimentation rate and high-sensitivity C-reactive protein level assessed, 18 (66.7%) had an increased erythrocyte sedimentation rate, and all 27 (100.0%) had an elevated high-sensitivity C-reactive protein level. Multiple lesions were seen on the initial CT scan of 52 of 62 patients (83.9%). Forty-eight of 62 patients (77.4%) had predominantly peripheral distribution of lesions. The mean CT score for the upper zone (3.0 ± 3.4) was significantly lower than that for the middle (4.5 ± 3.8) and lower (4.5 ± 3.7) zones (p = 0.022 and p = 0.020, respectively), and there was no significant difference in the mean CT score of the middle and lower zones (p = 1.00). The mean CT score for the anterior area (4.4 ± 4.1) was significantly lower than that for the posterior area (7.7 ± 6.3) (p = 0.003). CT findings for the patients were as follows: 25 patients (40.3%) had ground-glass opacities (GGO), 21 (33.9%), consolidation; 39 (62.9%), GGO plus a reticular pattern; 34 (54.8%), vacuolar sign; 28 (45.2%), microvascular dilation sign; 35 (56.5%), fibrotic streaks; 21 (33.9%), a subpleural line; and 33 (53.2%), a subpleural transparent line. With regard to bronchial changes seen on CT, 45 patients (72.6%) had air bronchogram, and 11 (17.7%) had bronchus distortion. In terms of pleural changes, CT showed that 30 patients (48.4%) had pleural thickening, 35 (56.5%) had pleural retraction sign, and six (9.7%) had pleural effusion. Compared with early-phase disease (≤ 7 days after the onset of symptoms), advanced-phase disease (8-14 days after the onset of symptoms) was characterized by significantly increased frequencies of GGO plus a reticular pattern, vacuolar sign, fibrotic streaks, a subpleural line, a subpleural transparent line, air bronchogram, bronchus distortion, and pleural effusion; however, GGO significantly decreased in advanced-phase disease. CONCLUSION. CT examination of patients with COVID-19 pneumonia showed a mixed and diverse pattern with both lung parenchyma and the interstitium involved. Identification of GGO and a single lesion on the initial CT scan suggested early-phase disease. CT signs of aggravation and repair coexisted in advanced-phase disease. Lesions presented with a characteristic multifocal distribution in the middle and lower lung regions and in the posterior lung area. A decreased lymphocyte count and an increased high-sensitivity C-reactive protein level were the most common laboratory findings.

A comparison of radiographic features between non-survivors and survivors from ICU.

The clinical and imaging data of 121 ICU patients with SARS-CoV-2 infection (63 survivors and 58 non-survivors) were retrospectively reviewed. The clinical results and radiographic features were compared between survivors and non-survivors. Compared with survivors, non-survivors were more likely to develop ARDS (53 [91 %] vs. 22 [35 %], P < 0.0001), shock (6 [10 %] vs. 0, P = 0.009), cardiac injury(18 [31 %] vs. 6 [10 %], P = 0.003), acute kidney injury(21 [36 %] vs. 10 [16 %], P = 0.01), and pneumothorax(5 [9%] vs. 0, P = 0.017). There were typical radiographic features for ICU patients with SARS-CoV-2 pneumonia. Extensive air-space opacities could be seen in all patients. Middle and lower lung involvement was significantly more serious than upper lung (score 6.8 ±â€¯1.9, 7.2 ±â€¯2.1, and 5.7 ±â€¯1.7, respectively, P < 0.0001). Based on X-ray involvement score, non-survivors were in a more critical condition than survivors (20.3 ±â€¯4.6 vs. 19.1 ±â€¯3.1, P = 0.038).

Chest CT imaging features and severity scores as biomarkers for prognostic prediction in patients with COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a pandemic. Few studies have explored the role of chest computed tomography (CT) features and severity scores for prognostic prediction. In this study, we aimed to investigate the role of chest CT severity score and imaging features in the prediction of the prognosis of COVID-19 patients. METHODS: A total of 134 patients (62 recovered and 72 deceased patients) with confirmed COVID-19 were enrolled. The clinical, laboratory, and chest CT (316 scans) data were retrospectively reviewed. Demographics, symptoms, comorbidities, and temporal changes of laboratory results, CT features, and severity scores were compared between recovered and deceased groups using the Mann-Whitney U test and logistic regression to identify the risk factors for poor prognosis. RESULTS: Median age was 48 and 58 years for recovered and deceased patients, respectively. More patients had at least one comorbidity in the deceased group than the recovered group (60% vs. 29%). Leukocytes, neutrophil, high-sensitivity C-reactive protein (hsCRP), prothrombin, D-dimer, serum ferritin, interleukin (IL)-2, and IL-6 were significantly elevated in the deceased group than the recovered group at different stages. The total CT score at the peak stage was significantly greater in the deceased group than the recovered group (20 vs. 11 points). The optimal cutoff value of the total CT scores was 16.5 points, achieving 69.4% sensitivity and 82.2% specificity for the prognostic prediction. The crazy-paving pattern and consolidation were more common in the deceased patients than those in the recovered patients. Linear opacities significantly increased with the disease course in the recovered patients. Sex, age, neutrophil, IL-2, IL-6, and total CT scores were independent risk factors for the prognosis with odds ratios of 3.8 to 8.7. CONCLUSIONS: Sex (male), older age (>60 years), elevated neutrophil, IL-2, IL-6 level, and total CT scores (≥16) were independent risk factors for poor prognosis in patients with COVID-19. Temporal changes of chest CT features and severity scores could be valuable for early identification of severe cases and eventually reducing the mortality rate of COVID-19.

A prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in thousands of deaths in the world. Information about prediction model of prognosis of SARS-CoV-2 infection is scarce. We used machine learning for processing laboratory findings of 110 patients with SARS-CoV-2 pneumonia (including 51 non-survivors and 59 discharged patients). The maximum relevance minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator logistic regression model were used for selection of laboratory features. Seven laboratory features selected in the model were: prothrombin activity, urea, white blood cell, interleukin-2 receptor, indirect bilirubin, myoglobin, and fibrinogen degradation products. The signature constructed using the seven features had 98% [93%, 100%] sensitivity and 91% [84%, 99%] specificity in predicting outcome of SARS-CoV-2 pneumonia. Thus it is feasible to establish an accurate prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings.

Imaging features and evolution on CT in 100 COVID-19 pneumonia patients in Wuhan, China.

OBJECTIVES: To investigate CT images of 100 confirmed COVID-19 pneumonia patients to describe the lesion distribution, CT signs, and evolution during different courses. METHODS: A retrospective study of 100 COVID-19 pneumonia patients without ARDS was performed, and CT scans were reviewed. A COVID-19 pneumonia course diagram was drawn. Mann-Whitney U test was used to compare the lesion distribution and CT scores, χ2 test was used to compare the CT findings between different stages. RESULTS: A total of 272 CT scans from 100 patients (mean age, 52.3 years ± 13.1) were investigated. Four patients with lung abnormalities on CT first showed negative RT-PCR result and turned positive afterwards. One hundred sixty-nine (62.1%) showed predominantly peripheral distribution. The CT scores of the upper zone (3.4 ± 3.6) were significantly lower than those of the middle (5.0 ± 3.9) and lower (4.8 ± 3.6) zones (p < 0.001). The CT scores of the anterior zones (4.9 ± 4.7) were significantly lower than those of the posterior zones (8.4 ± 6.2) (p < 0.001). In the early rapid progressive stage (1~7 days), ground glass opacity (GGO) plus reticular pattern (58.1%), GGO plus consolidation (43.0%), and GGO (41.9%) were all common. In the advanced stage (8~14 days), GGO plus consolidation (79.8%) and repairing CT signs (subpleural line, bronchus distortion, and fibrotic strips) showed a significant increase (p < 0.05). In the absorption stage, GGO plus consolidation (9.1%) sharply decreased (p < 0.05). CONCLUSION: CT imaging of COVID-19 pneumonia showed a predominantly peripheral, middle and lower, and posterior distribution. The early rapid progressive stage is 1~7 days from symptom onset, the advanced stage with peak levels of abnormalities on CT is 8~14 days, and the abnormalities started to improve after 14 days. KEY POINTS: • The course of COVID-19 pneumonia consists of three stages: 1~7 days is the early rapid progressive stage, 8~14 days is the advanced stage, and after 14 days, the abnormalities started to decrease. • In the early rapid progressive stage, GGO plus a reticular pattern, GGO plus consolidation, and GGO were all common signs; in the advanced stage, signs of progression and absorption coexisted; lung abnormalities showed an asynchronous process with parts with absorption and parts progressing. • Lung abnormalities mainly showed predominantly peripheral, middle, and lower distribution.

A Comparative Study of Chest Computed Tomography Features in Young and Older Adults With Corona Virus Disease (COVID-19).

OBJECTIVE: To analyze the most common computed tomography (CT) findings of pneumonia caused by new coronavirus in younger patients (60 and younger) and older adults (older than 60). MATERIALS AND METHODS: The chest CT images of 72 symptomatic patients with corona virus disease (COVID-19) were analyzed retrospectively, including 44 younger patients (47.5±8.7 y old) and 28 older patients (68.4±6.0 y old). CT findings including density (pure ground-glass opacities, ground-glass opacities with consolidation, consolidation), the number of lobes involved, lesion distribution, and the main accompanying signs were analyzed and compared. RESULTS: Characteristic CT findings included the lobes of bilateral lung extensively involved, ground-glass opacity and ground-glass opacity with consolidation in the peripheral area, sometimes accompanied by interlobular septal thickening, and subpleural line and pleural thickening. Compared with the younger group, the proportion of extensive involvement of lung lobes was higher in the elderly group (71.4% vs. 36.4%, P=0.009), and subpleural line and pleural thickening were more likely to occur (50.0% vs. 25.0%, and 71.4% vs. 40.9%, P=0.030 and 0.011, respectively). CONCLUSION: Elderly and younger patients with corona virus disease have some common CT features, but older patients are more likely to have extensive lung lobe involvement, and subpleural line and pleural thickening. These differentiated characteristics may be related to the progress and prognosis of the disease.

Initial CT findings and temporal changes in patients with the novel coronavirus pneumonia (2019-nCoV): a study of 63 patients in Wuhan, China.

OBJECTIVES: The purpose of this study was to observe the imaging characteristics of the novel coronavirus pneumonia. METHODS: Sixty-three confirmed patients were enrolled from December 30, 2019 to January 31, 2020. High-resolution CT (HRCT) of the chest was performed. The number of affected lobes, ground glass nodules (GGO), patchy/punctate ground glass opacities, patchy consolidation, fibrous stripes and irregular solid nodules in each patient's chest CT image were recorded. Additionally, we performed imaging follow-up of these patients. RESULTS: CT images of 63 confirmed patients were collected. M/F ratio: 33/30. The mean age was 44.9 ± 15.2 years. The mean number of affected lobes was 3.3 ± 1.8. Nineteen (30.2%) patients had one affected lobe, five (7.9%) patients had two affected lobes, four (6.3%) patients had three affected lobes, seven (11.1%) patients had four affected lobes while 28 (44.4%) patients had 5 affected lobes. Fifty-four (85.7%) patients had patchy/punctate ground glass opacities, 14 (22.2%) patients had GGO, 12 (19.0%) patients had patchy consolidation, 11 (17.5%) patients had fibrous stripes and 8 (12.7%) patients had irregular solid nodules. Fifty-four (85.7%) patients progressed, including single GGO increased, enlarged and consolidated; fibrous stripe enlarged, while solid nodules increased and enlarged. CONCLUSIONS: Imaging changes in novel viral pneumonia are rapid. The manifestations of the novel coronavirus pneumonia are diverse. Imaging changes of typical viral pneumonia and some specific imaging features were observed. Therefore, we need to strengthen the recognition of image changes to help clinicians to diagnose quickly and accurately. KEY POINTS: • High-resolution CT (HRCT) of the chest is critical for early detection, evaluation of disease severity and follow-up of patients with the novel coronavirus pneumonia. • The manifestations of the novel coronavirus pneumonia are diverse and change rapidly. • Radiologists should be aware of the various features of the disease and temporal changes.