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1.
Curr Med Imaging ; 17(11): 1316-1323, 2021.
Article in English | MEDLINE | ID: covidwho-1574962

ABSTRACT

BACKGROUND: Though imaging manifestations of COVID-19 and other types of viral pneumonia are similar, their clinical treatment methods differ. Accurate, non-invasive diagnostic methods using CT imaging can help develop an optimal therapeutic regimen for both conditions. OBJECTIVE: To compare the initial CT imaging features in COVID-19 with those in other types of viral pneumonia. METHODS: Clinical and imaging data of 51 patients with COVID-19 and 69 with other types of viral pneumonia were retrospectively studied. All significant imaging features (Youden index >0.3) were included for constituting the combined criteria for COVID-19 diagnosis, composed of two or more imaging features with a parallel model. McNemar's chi-square test or Fisher's exact test was used to compare the validity indices (sensitivity and specificity) among various criteria. RESULTS: Ground glass opacities (GGO) dominated density, peripheral distribution, unilateral lung, clear margin of lesion, rounded morphology, long axis parallel to the pleura, vascular thickening, and crazy-paving pattern were more common in COVID-19 (p <0.05). Consolidation-dominated density, both central and peripheral distributions, bilateral lung, indistinct margin of lesion, tree-inbud pattern, mediastinal or hilar lymphadenectasis, pleural effusion, and pleural thickening were more common in other types of viral pneumonia (p < 0.05). GGO-dominated density or long axis parallel to the pleura (with the highest sensitivity), and GGO-dominated density or long axis parallel to the pleura or vascular thickening (with the highest specificity) are well combined criteria of COVID-19. CONCLUSION: The initial CT imaging features are helpful for the differential diagnosis of COVID-19 and other types of viral pneumonia.


Subject(s)
COVID-19 , COVID-19 Testing , Humans , Retrospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed
2.
Curr Med Imaging ; 17(11): 1299-1307, 2021.
Article in English | MEDLINE | ID: covidwho-1574576

ABSTRACT

BACKGROUND: An outbreak of coronavirus disease 2019 (COVID-19) has occurred worldwide. However, the small-airway disease in patients with COVID-19 has not been explored. AIM: This study aimed to explore the small-airway disease in patients with COVID-19 using inspiratory and expiratory chest high-resolution computed tomography (CT). METHODS: This multicenter study included 108 patients with COVID-19. The patients were classified into five stages (0-IV) based on the CT images. The clinical and imaging data were compared among CT images in different stages. Patients were divided into three groups according to the time interval from the initial CT scan, and the clinical and air trapping data were compared among these groups. The correlation between clinical parameters and CT scores was evaluated. RESULTS: The clinical data, including age, frequency of breath shortness and dyspnea, neutrophil percentage, lymphocyte count, PaO2, PaCO2, SaO2, and time interval between the onset of illness and initial CT, showed significant differences among CT images in different stages. A significant difference in the CT score of air trapping was observed between stage I and stage III. A low negative correlation was found between the CT score of air trapping and the time interval between the onset of symptoms and initial CT. No significant difference was noted in the frequency and CT score of air trapping among different groups. CONCLUSION: Some patients with COVID-19 developed small-airway disease. Air trapping was more distinguished in the early stage of the disease and persisted during the 2-month follow-up. Longer-term follow-up studies are needed to confirm the findings.


Subject(s)
COVID-19 , Tomography, X-Ray Computed , COVID-19/diagnosis , Humans
3.
Front Immunol ; 11: 2063, 2020.
Article in English | MEDLINE | ID: covidwho-868947

ABSTRACT

Background: Cases of excessive neutrophil counts in the blood in severe coronavirus disease (COVID-19) patients have drawn significant attention. Neutrophil infiltration was also noted on the pathological findings from autopsies. It is urgent to clarify the pathogenesis of neutrophils leading to severe pneumonia in COVID-19. Methods: A retrospective analysis was performed on 55 COVID-19 patients classified as mild (n = 22), moderate (n = 25), and severe (n = 8) according to the Guidelines released by the National Health Commission of China. Trends relating leukocyte counts and lungs examined by chest CT scan were quantified by Bayesian inference. Transcriptional signatures of host immune cells of four COVID19 patients were analyzed by RNA sequencing of lung specimens and BALF. Results: Neutrophilia occurred in 6 of 8 severe patients at 7-19 days after symptom onset, coinciding with lesion progression. Increasing neutrophil counts paralleled lesion CT values (slope: 0.8 and 0.3-1.2), reflecting neutrophilia-induced lung injury in severe patients. Transcriptome analysis revealed that neutrophil activation was correlated with 17 neutrophil extracellular trap (NET)-associated genes in COVID-19 patients, which was related to innate immunity and interacted with T/NK/B cells, as supported by a protein-protein interaction network analysis. Conclusion: Excessive neutrophils and associated NETs could explain the pathogenesis of lung injury in COVID-19 pneumonia.


Subject(s)
Betacoronavirus/genetics , Coronavirus Infections/immunology , Extracellular Traps/genetics , Neutrophil Activation/genetics , Neutrophils/immunology , Pneumonia, Viral/immunology , Adult , Aged , Bayes Theorem , COVID-19 , Coronavirus Infections/virology , Female , Humans , Leukocyte Count , Lung Injury/immunology , Lung Injury/pathology , Male , Middle Aged , Neutrophil Infiltration/immunology , Pandemics , Pneumonia, Viral/virology , Protein Interaction Maps/immunology , RNA, Viral/genetics , Retrospective Studies , SARS-CoV-2 , Transcriptome
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