In patients recovering from COVID-19 infection, four stages of evolution on chest CT were identified: early stage (0-4 days); progressive stage (5-8 days); peak stage (10-13 days); and absorption stage (≥14 days). Key Results1. In patients who recovered from COVID-19 pneumonia, initial lung findings on chest CT were small subpleural ground glass opacities (GGO) that grew larger with crazy-paving pattern and consolidation.2. Lung involvement increased to consolidation up to two weeks after disease onset.3. After two weeks, the lesions were gradually absorbed leaving extensive GGO and subpleural parenchymal bands.This copy is for personal use only. To order printed copies, contact reprints@rsna.org I n P r e s s Abstract:Background: Chest CT is used to assess the severity of lung involvement in COVID-19 pneumonia. Purpose:To determine the change in chest CT findings associated with COVID-19 pneumonia from initial diagnosis until patient recovery. Materials and Methods:This retrospective review included patients with RT-PCR confirmed COVID-19 infection presenting between 12 January 2020 to 6 February 2020. Patients with severe respiratory distress and/ or oxygen requirement at any time during the disease course were excluded.Repeat Chest CT was obtained at approximately 4 day intervals. The total CT score was the sum of lung involvement (5 lobes, score 1-5 for each lobe, range, 0 none, 25 maximum) was determined.Results: Twenty one patients (6 males and 15 females, age 25-63 years) with confirmed COVID-19 pneumonia were evaluated. These patients underwent a total of 82 pulmonary CT scans with a mean interval of 4±1 days (range: 1-8 days). All patients were discharged after a mean hospitalized period of 17±4 days (range: 11-26 days). Maximum lung involved peaked at approximately 10 days (with the calculated total CT score of 6) from the onset of initial symptoms (R2=0.25), p<0.001). Based on quartiles of patients from day 0 to day 26 involvement, 4 stages of lung CT were defined: Stage 1 (0-4 days): ground glass opacities (GGO) in 18/24 (75%) patients with the total CT score of 2±2; (2) Stage-2 (5-8d days): increased crazy-paving pattern 9/17 patients (53%) with a increase in total CT score (6±4, p=0.002); (3) Stage-3 (9-13days): consolidation 19/21 (91%) patients with the peak of total CT score (7±4) ; (4) Stage-4 (≥14 days): gradual resolution of consolidation 15/20 (75%) patients with a decreased total CT score (6±4) without crazy-paving pattern. Conclusion:In patients recovering from COVID-19 pneumonia (without severe respiratory distress during the disease course), lung abnormalities on chest CT showed greatest severity approximately 10 days after initial onset of symptoms.

Infection with SARS-CoV-2, the cause of coronavirus infectious disease-19 , has caused a pandemic with >850,000 cases worldwide and increasing. Several studies report outcomes of COVID-19 in predominately well persons. There are also some data on COVID-19 in persons with predominately solid cancer but controversy whether these persons have the same outcomes. We conducted a cohort study at two centres in Wuhan, China, of 128 hospitalised subjects with haematological cancers, 13 (10%) of whom developed COVID-19. We also studied 226 health care providers, 16 of whom developed COVID-19 and 11 of whom were hospitalised. Co-variates were compared with the 115 subjects with haematological cancers without COVID-19 and with 11 hospitalised health care providers with COVID-19. There were no significant differences in baseline co-variates between subjects with haematological cancers developing or not developing COVID-19. Case rates for COVID-19 in hospitalised subjects with haematological cancers was 10% (95% Confidence Interval [CI], 6, 17%) compared with 7% (4, 12%; P = 0.322) in health care providers. However, the 13 subjects with haematological cancers had more severe COVID-19 and more deaths compared with hospitalised health care providers with COVID-19. Case fatality rates were 62% (32, 85%) and 0 (0, 32%; P = 0.002). Hospitalised persons with haematological cancers have a similar case rate of COVID-19 compared with normal health care providers but have more severe disease and a higher case fatality rate. Because we were unable to identify specific risk factors for COVID-19 in hospitalised persons with haematological cancers, we suggest increased surveillance and possible protective isolation.

Rationale: Up to date, the exploration of clinical features in severe COVID-19 patients were mostly from the same center in Wuhan, China. The clinical data in other centers is limited. This study aims to explore the feasible parameters which could be used in clinical practice to predict the prognosis in hospitalized patients with severe coronavirus disease-19 . Methods: In this case-control study, patients with severe COVID-19 in this newly established isolation center on admission between 27 January 2020 to 19 March 2020 were divided to discharge group and death event group. Clinical information was collected and analyzed for the following objectives: 1. Comparisons of basic characteristics between two groups; 2. Risk factors for death on admission using logistic regression; 3. Dynamic changes of radiographic and laboratory parameters between two groups in the course. Results: 124 patients with severe COVID-19 on admission were included and divided into discharge group (n=35) and death event group (n=89). Sex, SpO2, breath rate, diastolic pressure, neutrophil, lymphocyte, C-reactive protein (CRP), procalcitonin (PCT), lactate dehydrogenase (LDH), and D-dimer were significantly correlated with death events identified using bivariate logistic regression. Further multivariate logistic regression demonstrated a significant model fitting with C-index of 0.845 (p<0.001), in which SpO2≤89%, lymphocyte≤0.64×10 9 /L, CRP>77.35mg/L, PCT>0.20μg/L, and LDH>481U/L were the independent risk factors with the ORs of 2. 959, 4.015, 2.852, 3.554, and 3.185, respectively (p<0.04). In the course, persistently lower lymphocyte with higher levels of CRP, PCT, IL-6, neutrophil, LDH, D-dimer, cardiac troponin I (cTnI), brain natriuretic peptide (BNP), and increased CD4+/CD8+ T-lymphocyte ratio and were observed in death events group, while these parameters stayed stable or improved in discharge group. Conclusions: On admission, the levels of SpO2, lymphocyte, CRP, PCT, and LDH could predict the prognosis of severe COVID-19 patients. Systematic inflammation with induced cardiac dysfunction was likely a primary reason for death events in severe COVID-19 except for acute respiratory distress syndrome.

Background: A cluster of patients with coronavirus disease 2019 (COVID-19) pneumonia were discharged from hospitals in Wuhan, China. We aimed to determine the cumulative percentage of complete radiological resolution at each time point, to explore the relevant affecting factors, and to describe the chest CT findings at different time points after hospital discharge. Methods: Patients with COVID-19 pneumonia confirmed by RT-PCR who were discharged consecutively from the hospital between 5 February 2020 and 10 March 2020 and who underwent serial chest CT scans on schedule were enrolled. The radiological characteristics of all patients were collected and analysed. The total CT score was the sum of non-GGO involvement determined at discharge. Afterwards, all patients underwent chest CT scans during the 1st, 2nd, and 3rd weeks after discharge. Imaging features and distributions were analysed across different time points. Results: A total of 149 patients who completed all CT scans were evaluated; there were 67 (45.0%) men and 82 (55.0%) women, with a median age of 43 years old (IQR 36-56). The cumulative percentage of complete radiological resolution was 8.1% (12 patients), 41.6% (62), 50.3% (75), and 53.0% (79) at discharge and during the 1st, 2nd, and 3rd weeks after discharge, respectively. Patients ≤44 years old showed a significantly higher cumulative percentage of complete radiological resolution than patients > 44 years old at the 3-week follow-up. The predominant patterns of abnormalities observed at discharge were ground-glass opacity (GGO) (125 [83.9%]), fibrous stripe (81 [54.4%]), and thickening of the adjacent pleura (33 [22.1%]). The positive count of GGO, fibrous stripe and thickening of the adjacent pleura gradually decreased, while GGO and fibrous stripe showed obvious resolution during the first week and the third week after discharge, respectively. "Tinted" sign and bronchovascular bundle distortion as two special features were discovered during the evolution. Conclusion: Lung lesions in COVID-19 pneumonia patients can be absorbed completely during short-term followup with no sequelae. Two weeks after discharge might be the optimal time point for early radiological estimation.

Background The chest CT manifestations of COVID-19 from hospitalization to convalescence after one year are not known. Purpose To assess chest CT manifestations of COVID-19 up to 1 year after symptom onset. Materials and Methods Patients were enrolled if they were admitted to the hospital due to COVID-19 and underwent CT scans during hospitalization at two isolation centers between 27 January and 31 March 2020. In a prospective study, three serial chest CTs were obtained at approximately 3, 7, and 12 months after symptom onset and longitudinally analyzed. The total CT score of pulmonary lobe involvement from 0 to 25 was assessed (score 1-5 for each lobe). Uni-/multi-variable logistic regression tests were performed to explore independent risk factors for residual CT abnormalities after one year. Results 209 study participants (mean age: 49±13 years, 116 women) were evaluated. At 3 months, 61% of participants (128 of 209) had resolution of CT abnormalities; at 12 months, 75% (156 of 209) had resolution. Of chest CT abnormalities that had not resolved, there were residual linear opacities in 25/209 (12%) and multifocal reticular/cystic lesions in 28/209 (13%) participants. Age≥50 years, lymphopenia, and severe/ARDS aggravation were independent risk factors for residual CT abnormalities at one year (odds ratios of 15.9, 18.9, and 43.9, respectively; P <.001, each). In 53 participants with residual CT abnormalities at 12 months, reticular lesions (41 of 53, 77%) and bronchial dilation (39 of 53, 74%) were observed at discharge and were persistent in 53% (28 of 53) and 45% (24 of 53) of participants, respectively. Conclusion One year after COVID-19 diagnosis, chest CT showed abnormal findings in 25% of participants, with 13% showing subpleural reticular/cystic lesions. Older participants with severe COVID-19 or acute respiratory distress syndrome were more likely to develop lung sequelae that persisted at 1 year. See also the editorial by Lee and Wi .

Rationale:To retrospectively analyze serial chest CT and clinical features in patients with coronavirus disease 2019 for the assessment of temporal changes and to investigate how the changes differ in survivors and nonsurvivors. Methods: The consecutive records of 93 patients with confirmed COVID-19 who were admitted to Wuhan Union Hospital from January 10, 2020, to February 22, 2020, were retrospectively reviewed. A series of chest CT findings and clinical data were collected and analyzed. The serial chest CT scans were scored on a semiquantitative basis according to the extent of pulmonary abnormalities. Chest CT scores in different periods (0 -5 days, 6 -10 days, 11 -15 days, 16 -20 days, and > 20 days) since symptom onset were compared between survivors and nonsurvivors, and the temporal trend of the radiographic-clinical features was analyzed. Results: The final cohort consisted of 93 patients: 68 survivors and 25 nonsurvivors. Nonsurvivors were significantly older than survivors. For both survivors and nonsurvivors, the chest CT scores were not different in the first period (0 -5 days) but diverged afterwards. The mortality rate of COVID-19 monotonously increased with chest CT scores, which positively correlated with the neutrophil-to-lymphocyte ratio, neutrophil percentage, D-dimer level, lactate dehydrogenase level and erythrocyte sedimentation rate, while negatively correlated with the lymphocyte percentage and lymphocyte count. Conclusions: Chest CT scores correlate well with risk factors for mortality over periods, thus they may be used as a prognostic indicator in COVID-19. While higher chest CT scores are associated with a higher mortality rate, CT images taken at least 6 days since symptom onset may contain more prognostic information than images taken at an earlier period.

Multislice spiral CT allows a comprehensively assessment of various congenital inner ear malformations through high-quality MPR and VRT reconstructions. Volume-rendering technique images can display the site and degree of the malformation 3-dimensionally and intuitionisticly. This is very useful to the cochlear implantation.

This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19. 95 patients with confirmed COVID-19 and a total of 465 serial chest CT scans were involved, including 61 moderate patients (moderate group, 319 chest CT scans) and 34 severe patients (severe group, 146 chest CT scans). Conventional CT scoring and deep learning-based quantification were performed for all chest CT scans for two study goals: (1) Correlation between these two estimations; (2) Exploring the dynamic patterns using these two estimations between moderate and severe groups. The Spearman’s correlation coefficient between these two estimation methods was 0.920 (p < 0.001). predicted pulmonary involvement (CT score and percent of pulmonary lesions calculated using deep learning-based quantification) increased more rapidly and reached a higher peak on 23rd days from symptom onset in severe group, which reached a peak on 18th days in moderate group with faster absorption of the lesions. The deep learning-based quantification for COVID-19 showed a good correlation with the conventional CT scoring and demonstrated a potential benefit in the estimation of disease severities of COVID-19.