Aged ; Humans ; Influenza, Human ; diagnostic imaging ; Male ; Pneumonia, Viral ; diagnostic imaging ; Tomography, X-Ray Computed

Coronavirus disease 2019 (COVID-19) has spread rapidly around the world. In order to diagnose COVID-19 more quickly, in this paper, a depthwise separable DenseNet was proposed. The paper constructed a deep learning model with 2 905 chest X-ray images as experimental dataset. In order to enhance the contrast, the contrast limited adaptive histogram equalization (CLAHE) algorithm was used to preprocess the X-ray image before network training, then the images were put into the training network and the parameters of the network were adjusted to the optimal. Meanwhile, Leaky ReLU was selected as the activation function. VGG16, ResNet18, ResNet34, DenseNet121 and SDenseNet models were used to compare with the model proposed in this paper. Compared with ResNet34, the proposed classification model of pneumonia had improved 2.0%, 2.3% and 1.5% in accuracy, sensitivity and specificity respectively. Compared with the SDenseNet network without depthwise separable convolution, number of parameters of the proposed model was reduced by 43.9%, but the classification effect did not decrease. It can be found that the proposed DWSDenseNet has a good classification effect on the COVID-19 chest X-ray images dataset. Under the condition of ensuring the accuracy as much as possible, the depthwise separable convolution can effectively reduce number of parameters of the model.
Betacoronavirus ; Coronavirus Infections ; diagnostic imaging ; Deep Learning ; Humans ; Pandemics ; Pneumonia, Viral ; diagnostic imaging ; X-Rays

Child ; Female ; Humans ; Influenza A Virus, H5N1 Subtype ; Influenza, Human ; complications ; diagnostic imaging ; Pneumonia, Viral ; diagnostic imaging ; virology ; Radiography

Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 and was declared a global pandemic by the World Health Organization on 11 March 2020. A definitive diagnosis of COVID-19 is made after a positive result is obtained on reverse transcription-polymerase chain reaction assay. In Singapore, rigorous contact tracing was practised to contain the spread of the virus. Nasal swabs and chest radiographs (CXR) were also taken from individuals who were suspected to be infected by COVID-19 upon their arrival at a centralised screening centre. From our experience, about 40% of patients who tested positive for COVID-19 had initial CXR that appeared "normal". In this case series, we described the temporal evolution of COVID-19 in patients with an initial "normal" CXR. Since CXR has limited sensitivity and specificity in COVID-19, it is not suitable as a first-line diagnostic tool. However, when CXR changes become unequivocally abnormal, close monitoring is recommended to manage potentially severe COVID-19 pneumonia.
Adult ; Betacoronavirus ; Clinical Laboratory Techniques ; Coronavirus Infections ; complications ; diagnosis ; diagnostic imaging ; Female ; Humans ; Lung ; diagnostic imaging ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral ; complications ; diagnostic imaging ; Radiography ; Sensitivity and Specificity

OBJECTIVE: To investigate the CT findings of patients with different clinical types of coronavirus disease 2019 (COVID-19). METHODS: A total of 67 patients diagnosed as COVID-19 by nucleic acid testing were collected and divided into 4 groups according to the clinical stages based on . The CT imaging characteristics were analyzed among patients with different clinical types. RESULTS: Among 67 patients, 3(4.5%) were mild, 35 (52.2%) were moderate, 22 (32.8%) were severe, and 7(10.4%) were critical ill. No significant abnormality in chest CT imaging in mild patients. The 35 cases of moderate type included 3 (8.6%) single lesions, the 22 cases of severe cases included 1 (4.5%) single lesion and the rest cases were with multiple lesions. CT images of moderate patients were mainly manifested by solid plaque shadow and halo sign (18/35, 51.4%); while fibrous strip shadow with ground glass shadow was more frequent in severe cases (7/22, 31.8%). Consolidation shadow as the main lesion was observed in 7 cases, and all of them were severe or critical ill patients. CONCLUSIONS CT images of patients with different clinical types of COVID-19 have characteristic manifestations, and solid shadow may predict severe and critical illness.
Betacoronavirus ; isolation & purification ; Coronavirus Infections ; classification ; diagnostic imaging ; Humans ; Lung ; diagnostic imaging ; Pandemics ; classification ; Pneumonia, Viral ; classification ; diagnostic imaging ; Tomography, X-Ray Computed

OBJECTIVE: To analyze the CT findings of patients with different clinical types of coronavirus disease 2019 (COVID-19). METHODS: A total of 67 patients diagnosed as COVID-19 by nucleic acid testing were included and divided into 4 groups according to the clinical staging based on . The CT imaging characteristics were analyzed among patients with different clinical types. RESULTS: Among 67 patients, 3 (4.5%) were mild cases, 35 (52.2%) were ordinary cases, 22 (32.8%) were severe cases, and 7 (10.4%) were critically ill. There were no abnormal CT findings in mild cases. In 35 ordinary cases, there were single lesions in 3 cases (8.6%) and multiple lesions in 33 cases (91.4%), while in severe case 1 case had single lesion (4.5%) and 21 had multiple lesions (95.5%). CT images of ordinary patients were mainly manifested as solid plaque shadow and halo sign (18/35, 51.4%); while fibrous strip shadow with ground glass shadow was more frequent in severe cases (7/22, 31.8%). Consolidation shadow as the main lesion was observed in 7 cases, and all of them were severe or critical ill patients. CONCLUSIONS CT images in patients with different clinical types of COVID-19 have characteristic manifestations, and solid shadow may predict severe and critical illness.
Betacoronavirus ; Clinical Laboratory Techniques ; Coronavirus Infections ; diagnosis ; diagnostic imaging ; Humans ; Lung ; diagnostic imaging ; pathology ; Pneumonia, Viral ; diagnostic imaging ; pathology ; Severity of Illness Index ; Tomography, X-Ray Computed ; methods

OBJECTIVE: To early differentiate between coronavirus disease 2019 (COVID-19) and adult mycoplasma pneumonia with chest CT scan. METHODS: Twenty-six patients with COVID-19 and 21 patients with adult mycoplasma pneumonia confirmed with RT-PCR test were enrolled from Zibo First Hospital and Lanshan People's Hospital during December 1st 2019 and March 14th 2020. The early chest CT manifestations were analyzed and compared between the two groups. RESULTS: The interstitial changes with ground glass density shadow (GGO) were similar in two groups during first chest CT examination (>0.05). There were more lung lobes involved on the first chest CT in COVID-19 patients, which were mostly distributed in the dorsal outer zone (23/26, 88.5%), and nearly half of them (12/26, 46.2%) were accompanied by crazy-paving sign; while the lesions in adult mycoplasma pneumonia patients were mostly distributed along the bronchi, and the bronchial wall was thickened (19/21, 90.5%), accompanied with tree buds / fog signs (19/21, 90.5%). The above CT signs were significantly different between the two kinds of pneumonia (all <0.01). COVID-19 had a longer course compared with mycoplasma pneumonia, the disease peaks of COVID-19 patients was on day (10.5±3.8), while the disease on CT was almost absorbed on day (7.9±2.2) in adult mycoplasma pneumonia. The length of hospital stay in COVID-19 patients was significantly longer than that of mycoplasma pneumonia patients [(19.5±4.3) d vs (7.9±2.2) d, <0.01]. CONCLUSIONS The lesions of adult mycoplasma pneumonia are mostly distributed along the bronchi with tree buds/fog signs, while the lesions of COVID-19 are mainly distributed in the dorsal outer zone accompanied by crazy-paving sign, which can early distinguish two diseases.
Adult ; Betacoronavirus ; Clinical Laboratory Techniques ; standards ; Coronavirus Infections ; diagnosis ; diagnostic imaging ; Diagnosis, Differential ; Humans ; Lung ; diagnostic imaging ; Pandemics ; Pneumonia, Mycoplasma ; diagnostic imaging ; Pneumonia, Viral ; diagnostic imaging ; Tomography, X-Ray Computed

Objective To compare the similarities and differences of early CT manifestations of three types of viral pneumonia induced by SARS-CoV-2 (COVID-19), SARS-CoV (SARS) and MERS-CoV (MERS) using a systemic review. Methods Electronic database were searched to identify all original articles and case reports presenting chest CT features for adult patients with COVID-19, SARS and MERS pneumonia respectively. Quality of literature and completeness of presented data were evaluated by consensus reached by three radiologists. Vote-counting method was employed to include cases of each group. Data of patients' manifestations in early chest CT including lesion patterns, distribution of lesions and specific imaging signs for the three groups were extracted and recorded. Data were compared and analyzed using SPSS 22.0. Results A total of 24 studies were included, composing of 10 studies of COVID-19, 5 studies of MERS and 9 studies of SARS. The included CT exams were 147, 40, and 122 respectively. For the early CT features of the 3 pneumonias, the basic lesion pattern with respect to "mixed ground glass opacity (GGO) and consolidation, GGO mainly, or consolidation mainly" was similar among the 3 groups (=7.966, >0.05). There were no significant differences on the lesion distribution (=13.053, >0.05) and predominate involvement of the subpleural area of bilateral lower lobes (=4.809, >0.05) among the 3 groups. The lesions appeared more focal in COVID-19 pneumonia at early phase (=23.509, <0.05). The proportions of crazy-paving pattern (=23.037, <0.001), organizing pneumonia pattern (<0.05) and pleural effusions (<0.001) in COVID-19 pneumonia were significantly lower than the other two. Although rarely shown in the early CT findings of all three viral pneumonias, the fibrotic changes were more frequent in SARS than COVID-19 and MERS (=6.275, <0.05). For other imaging signs, only the MERS pneumonia demonstrated tree-in-buds, cavitation, and its incidence rate of interlobular or intralobular septal thickening presented significantly increased as compared to the other two pneumonia (=22.412, <0.05). No pneumothorax, pneumomediastinum and lymphadenopathy was present for each group. Conclusions Imaging findings on early stage of these three coronavirus pneumonias showed similar basic lesion patterns, including GGO and consolidation, bilateral distribution, and predominant involvement of the subpleural area and the lower lobes. Early signs of COVID-19 pneumonia showed less severity of inflammation. Early fibrotic changes appeared in SARS only. MERS had more severe inflammatory changes including cavitation and pleural effusion. The differences may indicate the specific pathophysiological processes for each coronavirus pneumonia.
Betacoronavirus ; Coronavirus Infections ; diagnostic imaging ; Humans ; Lung ; diagnostic imaging ; Middle East Respiratory Syndrome Coronavirus ; Pandemics ; Pneumonia, Viral ; diagnostic imaging ; SARS Virus ; Severe Acute Respiratory Syndrome ; diagnostic imaging ; Tomography, X-Ray Computed

Objective: To identify the characteristics including clinical features and pulmonary computed tomography (CT) features of heart failure and COVID-19. Methods: This study was a retrospective study. A total of 7 patients with heart failure and 12 patients with COVID-19 in the Second Xiangya Hospital of Central South University between December 1, 2019 and February 15, 2020 were enrolled. The baseline clinical and imaging features of the two groups were statistically analyzed. Results: There was no significant difference in age and sex between the two groups(both P>0.05), but the incidence of epidemiological contact history, fever or respiratory symptoms in the COVID-19 group was significantly higher than that in the heart failure group (12/12 vs. 0, P<0.001; 12/12 vs. 4/7, P=0.013). While the proportion of cardiovascular diseases and impaired cardiac function was significantly less than that of the heart failure group(2/12 vs.7/7, P<0.001；0 vs.7/7, P<0.001). For imaging features, both groups had ground-glass opacity and thickening of interlobular septum, but the ratio of central and gradient distribution was higher in patients with heart failure than that in patients with COVID-19 (4/7 vs. 1/12, P=0.04). In heart failure group, the ratio of the expansion of pulmonary veins was also higher (3/7 vs. 0，P=0.013), and the lung lesions can be significantly improved after effective anti-heart failure treatment. Besides, there were more cases with rounded morphology in COVID-19 group（9/12 vs. 2/7, P=0.048）. Conclusions: More patients with COVID-19 have epidemiological history and fever or respiratory symptoms. There are significant differences in chest CT features, such as enlargement of pulmonary veins, lesions distribution and morphology between heart failure and COVID-19.
Betacoronavirus ; COVID-19 ; Coronavirus Infections/diagnostic imaging* ; Heart Failure/etiology* ; Humans ; Pandemics ; Pneumonia, Viral/diagnostic imaging* ; Retrospective Studies ; SARS-CoV-2 ; Tomography, X-Ray Computed

OBJECTIVE: To analyze the dynamic changes of chest CT images of patients with coronavirus disease 2019 (COVID-19). METHODS: Fifty-two cases of COVID-19 were admitted in the First Affiliated Hospital of Zhejiang University School of Medicine. The consecutive chest CT scans were followed up for all patients with an average of 4 scans performed per patient during the hospitalization. The shortest interval between each scan was 2 days and the longest was 7 days. The shape, number and distribution of lung shadows, as well as the characteristics of the lesions on the CT images were reviewed. RESULTS: The obvious shadows infiltrating the lungs were shown on CT images in 50 cases, for other 2 cases there was no abnormal changes in the lungs during the first CT examination. Ground-glass opacities (GGO) were found in 48 cases (92.3%), and 19 cases (36.5%) had patchy consolidation and sub-consolidation, which were accompanied with air bronchi sign in 17 cases (32.7%). Forty one cases (78.8%) showed a thickened leaflet interval, 4 cases (7.6%) had a small number of fibrous stripes. During hospitalization, GGO lesions in COVID-19 patients gradually became rare,the fibrous strip shadows increased and it became the most common imaging manifestation. The lesions rapidly progressed in 39 cases (75.0%) within 6-9 days after admission. On days 10-14 of admission, the lesions distinctly resolved in 40 cases (76.9%). CONCLUSIONS The chest CT images of patients with COVID-19 have certain characteristics with dynamic changes, which are of value for monitoring disease progress and clinical treatment.
Betacoronavirus ; isolation & purification ; China ; Coronavirus Infections ; diagnostic imaging ; pathology ; Disease Progression ; Humans ; Pandemics ; Pneumonia, Viral ; diagnostic imaging ; pathology ; Tomography, X-Ray Computed