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Organizing pneumonia of COVID-19: Time-dependent evolution and outcome in CT findings.

ABSTRACT: BACKGROUND:As a pandemic, a most-common pattern resembled organizing pneumonia (OP) has been identified by CT findings in novel coronavirus disease (COVID-19). We aimed to delineate the evolution of CT findings and outcome in OP of COVID-19. MATERIALS AND METHODS:106 COVID-19 patients with OP based on CT findings were retrospectively included and categorized into non-severe (mild/common) and severe (severe/critical) groups. CT features including lobar distribution, presence of ground glass opacities (GGO), consolidation, linear opacities and total severity CT score were evaluated at three time intervals from symptom-onset to CT scan (day 0-7, day 8-14, day > 14). Discharge or adverse outcome (admission to ICU or death), and pulmonary sequelae (complete absorption or lesion residuals) on CT after discharge were analyzed based on the CT features at different time interval. RESULTS:79 (74.5%) patients were non-severe and 103 (97.2%) were discharged at median day 25 (range, day 8-50) after symptom-onset. Of 67 patients with revisit CT at 2-4 weeks after discharge, 20 (29.9%) had complete absorption of lesions at median day 38 (range, day 30-53) after symptom-onset. Significant differences between complete absorption and residuals groups were found in percentages of consolidation (1.5% vs. 13.8%, P = 0.010), number of involved lobe > 3 (40.0% vs. 72.5%, P = 0.030), CT score > 4 (20.0% vs. 65.0%, P = 0.010) at day 8-14. CONCLUSION:Most OP cases had good prognosis. Approximately one-third of cases had complete absorption of lesions during 1-2 months after symptom-onset while those with increased frequency of consolidation, number of involved lobe > 3, and CT score > 4 at week 2 after symptom-onset may indicate lesion residuals on CT.

SUBMITTER: Wang Y

PROVIDER: S-EPMC7657520 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Organizing pneumonia of COVID-19: Time-dependent evolution and outcome in CT findings.

Wang Yan Y Jin Chao C Wu Carol C CC Zhao Huifang H Liang Ting T Liu Zhe Z Jian Zhijie Z Li Runqing R Wang Zekun Z Li Fen F Zhou Jie J Cai Shubo S Liu Yang Y Li Hao H Liang Yukun Y Tian Cong C Yang Jian J

PloS one 20201111 11

<h4>Background</h4>As a pandemic, a most-common pattern resembled organizing pneumonia (OP) has been identified by CT findings in novel coronavirus disease (COVID-19). We aimed to delineate the evolution of CT findings and outcome in OP of COVID-19.<h4>Materials and methods</h4>106 COVID-19 patients with OP based on CT findings were retrospectively included and categorized into non-severe (mild/common) and severe (severe/critical) groups. CT features including lobar distribution, presence of gro ...[more]

PMID: 33175876

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Project description:Background: As global healthcare system is overwhelmed by novel coronavirus disease (COVID-19), early identification of risks of adverse outcomes becomes the key to optimize management and improve survival. This study aimed to provide a CT-based pattern categorization to predict outcome of COVID-19 pneumonia. Methods: One hundred and sixty-five patients with COVID-19 (91 men, 4-89 years) underwent chest CT were retrospectively enrolled. CT findings were categorized as Pattern 0 (negative), Pattern 1 (bronchopneumonia pattern), Pattern 2 (organizing pneumonia pattern), Pattern 3 (progressive organizing pneumonia pattern), and Pattern 4 (diffuse alveolar damage pattern). Clinical findings were compared across different categories. Time-dependent progression of CT patterns and correlations with clinical outcomes, i.e." discharge or adverse outcome (admission to ICU, requiring mechanical ventilation, or death), with pulmonary sequelae (complete absorption or residuals) on CT after discharge were analyzed. Results: Of 94 patients with outcome, 81 (86.2%) were discharged, 3 (3.2%) were admitted to ICU, 4 (4.3%) required mechanical ventilation, 6 (6.4%) died. 31 (38.3%) had complete absorption at median day 37 after symptom onset. Significant differences between pattern-categories were found in age, disease severity, comorbidity and laboratory results (all P < 0.05). Remarkable evolution was observed in Pattern 0-2 and Pattern 3-4 within 3 and 2 weeks after symptom-onset, respectively; most of patterns remained thereafter. After controlling for age, CT pattern significantly correlated with adverse outcomes [Pattern 4 vs. Pattern 0-3 [reference]; hazard-ratio [95% CI], 18.90 [1.91-186.60], P = 0.012]. CT pattern [Pattern 3-4 vs. Pattern 0-2 [reference]; 0.26 [0.08-0.88], P = 0.030] and C-reactive protein [>10 vs. ≤ 10 mg/L [reference]; 0.31 [0.13-0.72], P = 0.006] were risk factors associated with pulmonary residuals. Conclusion: CT pattern categorization allied with clinical characteristics within 2 weeks after symptom onset would facilitate early prognostic stratification in COVID-19 pneumonia.

Project description:ObjectivesGround-glass opacity and consolidation are recognized typical features of Coronavirus disease-19 (COVID-19) pneumonia on Chest CT, yet ancillary findings have not been fully described. We aimed to describe ancillary findings of COVID-19 pneumonia on CT, to define their prevalence, and investigate their association with clinical data.MethodsWe retrospectively reviewed our CT chest cases with coupled reverse transcriptase polymerase chain reaction (rt-PCR). Patients with negative rt-PCR or without admission chest CT were excluded. Ancillary findings included: vessel enlargement, subpleural curvilinear lines, dependent subpleural atelectasis, centrilobular solid nodules, pleural and/or pericardial effusions, enlarged mediastinal lymph nodes. Continuous data were expressed as median and 95% confidence interval (95% CI) and tested by Mann-Whitney U test.ResultsAncillary findings were represented by 106/252 (42.1%, 36.1 to 48.2) vessel enlargement, 50/252 (19.8%, 15.4 to 25.2) subpleural curvilinear lines, 26/252 (10.1%, 7.1 to 14.7) dependent subpleural atelectasis, 15/252 (5.9%, 3.6 to 9.6) pleural effusion, 15/252 (5.9%, 3.6 to 9.6) mediastinal lymph nodes enlargement, 13/252 (5.2%, 3 to 8.6) centrilobular solid nodules, and 6/252 (2.4%, 1.1 to 5.1) pericardial effusion. Air space disease was more extensive in patients with vessel enlargement or centrilobular solid nodules (p < 0.001). Vessel enlargement was associated with longer history of fever (p = 0.035) and lower admission oxygen saturation (p = 0.014); dependent subpleural atelectasis with lower oxygen saturation (p < 0.001) and higher respiratory rate (p < 0.001); mediastinal lymph nodes with shorter history of cough (p = 0.046); centrilobular solid nodules with lower prevalence of cough (p = 0.023), lower oxygen saturation (p < 0.001), and higher respiratory rate (p = 0.032), and pericardial effusion with shorter history of cough (p = 0.015). Ancillary findings associated with longer hospital stay were subpleural curvilinear lines (p = 0.02), whereas centrilobular solid nodules were associated with higher rate of intensive care unit admission (p = 0.01).ConclusionTypical high-resolution CT findings of COVID-19 pneumonia are frequently associated with ancillary findings that variably associate with disease extent, clinical parameters, and disease severity.Advances in knowledgeAncillary findings might reflect the broad range of heterogeneous mechanisms in severe acute respiratory syndrome from viral pneumonia, and potentially help disease phenotyping.

Project description:ObjectivesCT findings of COVID-19 look similar to other atypical and viral (non-COVID-19) pneumonia diseases. This study proposes a clinical computer-aided diagnosis (CAD) system using CT features to automatically discriminate COVID-19 from non-COVID-19 pneumonia patients.MethodsOverall, 612 patients (306 COVID-19 and 306 non-COVID-19 pneumonia) were recruited. Twenty radiological features were extracted from CT images to evaluate the pattern, location, and distribution of lesions of patients in both groups. All significant CT features were fed in five classifiers namely decision tree, K-nearest neighbor, naïve Bayes, support vector machine, and ensemble to evaluate the best performing CAD system in classifying COVID-19 and non-COVID-19 cases.ResultsLocation and distribution pattern of involvement, number of the lesion, ground-glass opacity (GGO) and crazy-paving, consolidation, reticular, bronchial wall thickening, nodule, air bronchogram, cavity, pleural effusion, pleural thickening, and lymphadenopathy are the significant features to classify COVID-19 from non-COVID-19 groups. Our proposed CAD system obtained the sensitivity, specificity, and accuracy of 0.965, 93.54%, 90.32%, and 91.94%, respectively, using ensemble (COVIDiag) classifier.ConclusionsThis study proposed a COVIDiag model obtained promising results using CT radiological routine features. It can be considered an adjunct tool by the radiologists during the current COVID-19 pandemic to make an accurate diagnosis.Key points• Location and distribution of involvement, number of lesions, GGO and crazy-paving, consolidation, reticular, bronchial wall thickening, nodule, air bronchogram, cavity, pleural effusion, pleural thickening, and lymphadenopathy are the significant features between COVID-19 from non-COVID-19 groups. • The proposed CAD system, COVIDiag, could diagnose COVID-19 pneumonia cases with an AUC of 0.965 (sensitivity = 93.54%; specificity = 90.32%; and accuracy = 91.94%). • The AUC, sensitivity, specificity, and accuracy obtained by radiologist diagnosis are 0.879, 87.10%, 88.71%, and 87.90%, respectively.

Project description:Background CT may play a central role in the diagnosis and management of coronavirus disease 2019 (COVID-19) pneumonia. Purpose To perform a longitudinal study to analyze the serial CT findings over time in patients with COVID-19 pneumonia. Materials and Methods During January 16 to February 17, 2020, 90 patients (33 men, 57 women; mean age, 45 years) with COVID-19 pneumonia were prospectively enrolled and followed up until being discharged, death, or the end of the study. A total of 366 CT scans were acquired and reviewed by two groups of radiologists for the patterns and distribution of lung abnormalities, total CT scores, and number of zones involved. Those features were analyzed for temporal change. Results CT scores and number of zones involved progressed rapidly, peaked during illness days 6-11 (median CT score, 5; median number of zones involved, five), and were followed by persistence of high levels. The predominant pattern of abnormalities after symptom onset was ground-glass opacity (35 of 78 scans [45%] to 49 of 79 scans [62%] in different periods). The percentage of mixed pattern peaked on illness days 12-17 (30 of 78 scans [38%]) and became the second most predominant pattern thereafter. Pure ground-glass opacity was the most prevalent subtype of ground-glass opacity after symptom onset (20 of 50 scans [40%] to 20 of 28 scans [71%]). The percentage of ground-glass opacity with irregular linear opacity peaked on illness days 6-11 (14 of 50 scans [28%]) and became the second most prevalent subtype thereafter. The distribution of lesions was predominantly bilateral and subpleural. Sixty-six of the 70 patients discharged (94%) had residual disease on final CT scans (median CT score, 4; median number of zones involved, four), with ground-glass opacity (42 of 70 patients [60%]) and pure ground-glass opacity (31 of 42 patients [74%]) the most common pattern and subtype. Conclusion The extent of lung abnormalities at CT peaked during illness days 6-11. The temporal changes of the diverse CT manifestations followed a specific pattern, which might indicate the progression and recovery of the illness. © RSNA, 2020 Online supplemental material is available for this article.

Dataset Information

Organizing pneumonia of COVID-19: Time-dependent evolution and outcome in CT findings.

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Organizing pneumonia of COVID-19: Time-dependent evolution and outcome in CT findings.

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