CT quantitative analysis in patients with severe coronavirus disease 2019 and its correlation with laboratory examination results

OBJECTIVE: To quantitatively analyze the longitudinal changes of ground-glass opacity (GGO), consolidation and total lesion in patients infected with severe coronavirus disease 2019 (COVID-19), and its correlation with laboratory examination results. MATERIALS AND METHODS: All 76 computed tomography (CT) images and laboratory examination results from the admission to discharge of 15 patients confirmed with severe COVID-19 were reviewed, whereas the GGO volume ratio, consolidation volume ratio, and total lesion volume ratio in different stages were analyzed. The correlations of lesions volume ratio and laboratory examination results were investigated. RESULTS: Four stages were identified based on the degree of lung involvement from day 1 to day 28 after disease onset. GGO was the most common CT manifestation in the four stages. The peak of lung involvement was at around stage 2, and corresponding total lesion volume ratio, GGO volume ratio, and consolidation volume ratio were 17.48 (13.44−24.33), 12.11 (7.34−17.08), and 5.51 (2.58−8.58), respectively. Total lesion volume ratio was positively correlated with neutrophil percentage, C-reactive protein (CRP), high-sensitivity CRP (Hs-CRP), procalcitonin, lactate dehydrogenase (LD), and creatine kinase isoenzyme MB (CK-MB), but negatively correlated with lymphocyte count, lymphocyte percentage, arterial oxygen saturation, and arterial oxygen tension. Consolidation volume ratio was correlated with most above laboratory examination results except Hs-CRP, LD, and CK-MB. GGO, however, was only correlated with lymphocyte count. CONCLUSION: CT quantitative parameters could show longitudinal changes well. Total lesion volume ratio and consolidation volume ratio are well correlated with laboratory examination results, suggesting that CT quantitative parameters may be an effective tool to reflect the changes in the condition.

Self-Reported Olfactory Dysfunction and Diet Quality: Findings from the 2011-2014 National Health and Nutrition Examination Survey (NHANES).

We identified associations between self-reported olfactory dysfunction (OD) and dietary attributes in participants aged ≥40 years (n = 6,356) from the nationally representative 2011-2014 National Health and Nutrition Examination Survey (NHANES). The chemosensory questionnaire and 24-h dietary recalls were administered by trained interviewers. OD was defined as self-report of either smell problems in the last year, worse smell relative to age 25, or perceiving phantom odors. Dietary outcomes included Healthy Eating Index 2015 score (HEI) with adequacy and moderation components (higher scores indicated higher diet quality), dietary diversity, energy density, and intake of major food groups. Survey-weighted linear regression models estimated OD-diet associations, adjusting for socio-demographic, lifestyle, and clinical factors. Adjusted mean difference (95% CI) between those with versus without OD, showed that adults with OD had significantly lower HEI moderation score (-0.67 (-1.22, -0.11)) and diets higher in energy density (0.06 (0.00, 0.11)), and percent energy from saturated fat (0.47 (0.12, 0.81)), total fat (0.96 (0.22, 1.70)), and added sugar (1.00 (0.33, 1.66)). Age and sex-stratified analyses showed that younger females (40-64 years) primarily accounted for the associations with diet quality and total/saturated fat intake. These findings inform dietary screening and recommendations for adults who report OD, including those experiencing transient or persistent smell loss with COVID-19.

Differentiation between COVID‐19 and bacterial pneumonia using radiomics of chest computed tomography and clinical features

To develop and validate an effective model for distinguishing COVID‐19 from bacterial pneumonia. In the training group and internal validation group, all patients were randomly divided into a training group (n = 245) and a validation group (n = 105). The whole lung lesion on chest computed tomography (CT) was drawn as the region of interest (ROI) for each patient. Both feature selection and model construction were first performed in the training set and then further tested in the validation set with the same thresholds. Additional tests were conducted on an external multicentre cohort with 105 subjects. The diagnostic model of LightGBM showed the best performance, achieving a sensitivity of 0.941, specificity of 0.981, accuracy of 0.962 on the validation dataset. In this study, we established a differential model to distinguish between COVID‐19 and bacterial pneumonia based on chest CT radiomics and clinical indexes.

Chest CT Findings in Patients With Coronavirus Disease 2019 and Its Relationship With Clinical Features.

OBJECTIVES: The aim of this study was to investigate the chest computed tomography (CT) findings in patients with confirmed coronavirus disease 2019 (COVID-19) and to evaluate its relationship with clinical features. MATERIALS AND METHODS: Study sample consisted of 80 patients diagnosed as COVID-19 from January to February 2020. The chest CT images and clinical data were reviewed, and the relationship between them was analyzed. RESULTS: Totally, 80 patients diagnosed with COVID-19 were included. With regards to the clinical manifestations, 58 (73%) of the 80 patients had cough, and 61 (76%) of the 80 patients had high temperature levels. The most frequent CT abnormalities observed were ground glass opacity (73/80 cases, 91%), consolidation (50/80 cases, 63%), and interlobular septal thickening (47/80, 59%). Most of the lesions were multiple, with an average of 12 ± 6 lung segments involved. The most common involved lung segments were the dorsal segment of the right lower lobe (69/80, 86%), the posterior basal segment of the right lower lobe (68/80, 85%), the lateral basal segment of the right lower lobe (64/80, 80%), the dorsal segment of the left lower lobe (61/80, 76%), and the posterior basal segment of the left lower lobe (65/80, 81%). The average pulmonary inflammation index value was (34% ± 20%) for all the patients. Correlation analysis showed that the pulmonary inflammation index value was significantly correlated with the values of lymphocyte count, monocyte count, C-reactive protein, procalcitonin, days from illness onset, and body temperature (P < 0.05). CONCLUSIONS: The common chest CT findings of COVID-19 are multiple ground glass opacity, consolidation, and interlobular septal thickening in both lungs, which are mostly distributed under the pleura. There are significant correlations between the degree of pulmonary inflammation and the main clinical symptoms and laboratory results. Computed tomography plays an important role in the diagnosis and evaluation of this emerging global health emergency.

Coronavirus disease 2019: initial chest CT findings.

OBJECTIVES: To systematically analyze CT findings during the early and progressive stages of natural course of coronavirus disease 2019 and also to explore possible changes in pulmonary parenchymal abnormalities during these two stages. METHODS: We retrospectively reviewed the initial chest CT data of 62 confirmed coronavirus disease 2019 patients (34 men, 28 women; age range 20-91 years old) who did not receive any antiviral treatment between January 21 and February 4, 2020, in Chongqing, China. Patients were assigned to the early-stage group (onset of symptoms within 4 days) or progressive-stage group (onset of symptoms within 4-7 days) for analysis. CT characteristics and the distribution, size, and CT score of pulmonary parenchymal abnormalities were assessed. RESULTS: In our study, the major characteristic of coronavirus disease 2019 was ground-glass opacity (61.3%), followed by ground-glass opacity with consolidation (35.5%), rounded opacities (25.8%), a crazy-paving pattern (25.8%), and an air bronchogram (22.6%). No patient presented cavitation, a reticular pattern, or bronchial wall thickening. The CT scores of the progressive-stage group were significantly greater than those of the early-stage group (p = 0.004). CONCLUSIONS: Multiple ground-glass opacities with consolidations in the periphery of the lungs were the primary CT characteristic of coronavirus disease 2019. CT score can be used to evaluate the severity of the disease. If these typical alterations are found, then the differential diagnosis of coronavirus disease 2019 must be considered. KEY POINTS: • Multiple GGOs with consolidations in the periphery of the lungs were the primary CT characteristic of COVID-19. • The halo sign may be a special CT feature in the early-stage COVID-19 patients. • Significantly increased CT score may indicate the aggravation of COVID-19 in the progressive stage.

The Clinical and Chest CT Features Associated With Severe and Critical COVID-19 Pneumonia.

OBJECTIVE: The aim of this study was to investigate the clinical and computed tomography (CT) features associated with severe and critical coronavirus disease 2019 (COVID-19) pneumonia. MATERIALS AND METHODS: Eighty-three patients with COVID-19 pneumonia including 25 severe/critical cases and 58 ordinary cases were enrolled. The chest CT images and clinical data of them were reviewed and compared. The risk factors associated with disease severity were analyzed. RESULTS: Compared with the ordinary patients, the severe/critical patients had older ages, higher incidence of comorbidities, cough, expectoration, chest pain, and dyspnea. The incidences of consolidation, linear opacities, crazy-paving pattern, and bronchial wall thickening in severe/critical patients were significantly higher than those of the ordinary patients. Besides, severe/critical patients showed higher incidences of lymph node enlargement, pericardial effusion, and pleural effusion than the ordinary patients. The CT scores of severe/critical patients were significantly higher than those of the ordinary patients (P < 0.001). Receiver operating characteristic curve showed that the sensitivity and specificity of CT score were 80.0% and 82.8%, respectively, for the discrimination of the 2 types. The clinical factors of age older than 50 years, comorbidities, dyspnea, chest pain, cough, expectoration, decreased lymphocytes, and increased inflammation indicators were risk factors for severe/critical COVID-19 pneumonia. Computed tomography findings of consolidation, linear opacities, crazy-paving pattern, bronchial wall thickening, high CT scores, and extrapulmonary lesions were features of severe/critical COVID-19 pneumonia. CONCLUSIONS: There are significant differences in clinical symptoms, laboratory examinations, and CT manifestations between the ordinary patients and the severe/critical patients. Many factors are related to the severity of the disease, which can help clinicians to judge the severity of the patient and evaluate the prognosis.