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

To summarize the clinical characteristics and chest CT findings of coronavirus disease 2019(COVID-19)patients in Peking Union Medical College Hospital(PUMCH). A total of 13 patients with COVID-19 confirmed at PUMCH from January 20 to February 6,2020 were selected as the research subjects.Their epidemiological histories,clinical characteristics,laboratory tests,and chest CT findings were analyzed retrospectively.The location,distribution,density,and other accompanying signs of abnormal lung CT lesions were recorded,and the clinical types of these patients were assessed. The clinical type was "common type" in all these 13 patients aged(46.8±14.7)years(range:27-68 years).Ten patients had a travel history to Wuhan or direct contact with patients from Wuhan,2 cases had recent travel histories,and 1 case had a travel history to Beijing suburb.The white blood cell(WBC)count was normal or decreased in 92.3% of the patients and the lymphocyte count decreased in 15.4% of the patients.Twelve patients(92.3%)had a fever,among whom 11 patients were admitted due to fever and 2 patients(15.4%)had low fever.Eight patients(61.5%)had dry cough.The CT findings in these 13 patients were all abnormal.The lesions were mainly distributed along the bronchi and under the pleura.The lesions were relatively limited in 8 patients(affecting 1-3 lobes,predominantly in the right or left lower lobe),and diffuse multiple lesions of bilateral lungs were seen in 5 patients.The CT findings mainly included ground glass opacities(GGOs)(=10,76.9%),focal consolidation within GGOs(=7,53.8%),thickened vascular bundle passing through the lesions(=10,76.9%),bronchial wall thickening(=12,92.3%),air bronchogram(=10,76.9%),vacuole signs in the lesions(=7,53.8%),fine reticulation and interlobular septal thickening(=3,23.1%),reversed halo-sign(=2,15.4%),crazy-paving pattern(=2,15.4%),and pleural effusion(=2,15.4%). Most of our patients diagnosed with COVID-19 at PUMCH had a travel history to Wuhan or direct contact with patients from Wuhan.The first symptoms of COVID-19 mainly include fever and dry cough,along with normal or reduced counts of WBC and lymphocytes.CT may reveal that the lesions distribute along the bronchi and under the pleura;they are typically localized GGOs in the early stage but can become multiple GGOs and infiltrative consolidation in both lungs in the advanced stage.Scattered vacuole signs may be visible inside the lesions in some patients.
Adult ; Aged ; Betacoronavirus ; Coronavirus Infections ; diagnostic imaging ; Humans ; Lung ; Middle Aged ; Pandemics ; Pneumonia, Viral ; diagnostic imaging ; Retrospective Studies ; Tomography, X-Ray Computed

To investigate the computed tomographc(CT)features of mild/moderate and severe/critical cases of coronavirus disease 2019(COVID-19)in the recovery phase. Totally 63 discharged patients in Wuhan,China,who underwent both chest CT and reverse transcription-polymerase chain reaction(RT-PCR)from February 1 to February 29,2020,were included.With RT-PCR as a gold standard,the performance of chest CT in diagnosing COVID-19 was assessed.Patients were divided into mild/moderate and severe/critical groups according to the disease conditions,and clinical features such as sex,age,symptoms,hospital stay,comorbidities,and oxygen therapy were collected.CT images in the recovery phase were reviewed in terms of time from onset,CT features,location of lesions,lobe score,and total CT score. There were 37 patients in the mild/moderate group and 26 in the severe/critical group. Compared with the mild/moderate patients,the severe/critical patients had older age [(43±16) years (52±16) years; =2.10, =0.040], longer hospital stay [(15±6)d (19±7)d; =2.70, =0.009], higher dyspnea ratio (5.41% 53.85%; =18.90, <0.001), lower nasal oxygen therapy ratio (81.08% 19.23%;=23.66, <0.001), and higher bi-level positive airway pressure ventilation ratio (0 57.69%; =25.62, <0.001). Time from onset was (23±6) days in severe/critical group, significantly longer than that in mild/moderate group [(18±7) days] (=3.40, <0.001). Severe/critical patients had significantly higher crazy-paving pattern ratio (46.15% 10.81%;=4.24, =0.039) and lower ground-glass opacities ratio (15.38% 67.57%; =16.74, <0.001) than the mild/moderate patients. The proportion of lesions in peripheral lung was significantly higher in mild/moderate group than in severe/critical group (78.38% 34.61%; =13.43, <0.001), and the proportion of diffusely distributed lesions was significantly higher in severe/critical group than in mild/moderate group (65.38% 10.81%; =20.47, <0.001). Total CT score in severe/critical group was also significantly higher in severe/critical group than in mild/moderate group [11 (8,17) points 7 (4,9) points; =3.81, <0.001]. The CT features in the recovery stage differ between mild/moderate and severe/critical COVID-19 patients.The lung infiltration is remarkably more severe in the latter.
Adult ; Aged ; Betacoronavirus ; China ; Coronavirus Infections ; diagnostic imaging ; Humans ; Middle Aged ; Pandemics ; Pneumonia, Viral ; diagnostic imaging ; Retrospective Studies ; Tomography, X-Ray Computed