1.Research on coronavirus disease 2019 (COVID-19) detection method based on depthwise separable DenseNet in chest X-ray images.
Yibo FENG ; Dawei QIU ; Hui CAO ; Junzhong ZHANG ; Zaihai XIN ; Jing LIU
Journal of Biomedical Engineering 2020;37(4):557-565
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
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Coronavirus Infections
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diagnostic imaging
;
Deep Learning
;
Humans
;
Pandemics
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Pneumonia, Viral
;
diagnostic imaging
;
X-Rays
2.Similarities and Differences of Early Pulmonary CT Features of Pneumonia Caused by SARS-CoV-2, SARS-CoV and MERS-CoV: Comparison Based on a Systemic Review.
Xu CHEN ; Gang ZHANG ; Shuai Ying HAO ; Lin BAI ; Jing Jing LU
Chinese Medical Sciences Journal 2020;35(3):254-261
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
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Coronavirus Infections
;
diagnostic imaging
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Humans
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Lung
;
diagnostic imaging
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Middle East Respiratory Syndrome Coronavirus
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Pandemics
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Pneumonia, Viral
;
diagnostic imaging
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SARS Virus
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Severe Acute Respiratory Syndrome
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diagnostic imaging
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Tomography, X-Ray Computed
3.CT imaging features of patients with different clinical types of COVID-19.
Qi ZHONG ; Zhi LI ; Xiaoyong SHEN ; Kaijin XU ; Yihong SHEN ; Qiang FANG ; Feng CHEN ; Tingbo LIANG
Journal of Zhejiang University. Medical sciences 2020;49(2):198-202
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
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isolation & purification
;
Coronavirus Infections
;
classification
;
diagnostic imaging
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Humans
;
Lung
;
diagnostic imaging
;
Pandemics
;
classification
;
Pneumonia, Viral
;
classification
;
diagnostic imaging
;
Tomography, X-Ray Computed
4.CT imaging features of patients with different clinical types of coronavirus disease 2019 (COVID-19).
Qi ZHONG ; Zhi LI ; Xiaoyong SHEN ; Kaijin XU ; Yihong SHEN ; Qiang FANG ; Feng CHEN ; Tingbo LIANG
Journal of Zhejiang University. Medical sciences 2020;49(1):198-202
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
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Clinical Laboratory Techniques
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Coronavirus Infections
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diagnosis
;
diagnostic imaging
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Humans
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Lung
;
diagnostic imaging
;
pathology
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Pneumonia, Viral
;
diagnostic imaging
;
pathology
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Severity of Illness Index
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Tomography, X-Ray Computed
;
methods
5.Chest Radiography in Coronavirus Disease 2019 (COVID-19): Correlation with Clinical Course.
Joel C ZHOU ; Terrence Ch HUI ; Cher Heng TAN ; Hau Wei KHOO ; Barnaby E YOUNG ; David C LYE ; Yeong Shyan LEE ; Gregory Jl KAW
Annals of the Academy of Medicine, Singapore 2020;49(7):456-461
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
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Betacoronavirus
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Clinical Laboratory Techniques
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Coronavirus Infections
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complications
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diagnosis
;
diagnostic imaging
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Female
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Humans
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Lung
;
diagnostic imaging
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Male
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Middle Aged
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Pandemics
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Pneumonia, Viral
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complications
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diagnostic imaging
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Radiography
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Sensitivity and Specificity
6.Diagnosis and treatment recommendation for pediatric COVID-19 (the second edition).
Zhimin CHEN ; Junfen FU ; Qiang SHU ; Wei WANG ; Yinghu CHEN ; Chunzhen HUA ; Fubang LI ; Ru LIN ; Lanfang TANG ; Tianlin WANG ; Yingshuo WANG ; Weize XU ; Zihao YANG ; Sheng YE ; Tianming YUAN ; Chenmei ZHANG ; Yuanyuan ZHANG
Journal of Zhejiang University. Medical sciences 2020;49(2):139-146
The coronavirus disease 2019 (COVID-19) has caused a global pandemic. All people including children are generally susceptible to COVID-19, but the condition is relatively mild for children. The diagnosis of COVID-19 is largely based on the epidemiological evidence and clinical manifestations, and confirmed by positive detection of virus nucleic acid in respiratory samples. The main symptoms of COVID-19 in children are fever and cough; the total number of white blood cell count is usually normal or decreased; the chest imaging is characterized by interstitial pneumonia, which is similar to other respiratory virus infections and infections. Early identification, early isolation, early diagnosis and early treatment are important for clinical management. The treatment of mild or moderate type of child COVID-19 is mainly symptomatic. For severe and critical ill cases, the oxygen therapy, antiviral drugs, antibacterial drugs, glucocorticoids, mechanical ventilation or even extracorporeal membrane oxygenation (ECMO) may be adopted, and the treatment plan should be adjusted timely through multi-disciplinary cooperation.
Betacoronavirus
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isolation & purification
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Child
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Coronavirus Infections
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diagnosis
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pathology
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therapy
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Humans
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Pandemics
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Pneumonia, Viral
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diagnosis
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diagnostic imaging
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etiology
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pathology
;
therapy
8.Comparison of heart failure and COVID-19 in chest CT features and clinical characteristics.
Zhao Wei ZHU ; Jian Jun TANG ; Xiang Ping CHAI ; Zhen Fei FANG ; Qi Ming LIU ; Xin Qun HU ; Dan Yan XU ; Liang TANG ; Shi TAI ; Yu Zhi WU ; Sheng Hua ZHOU
Chinese Journal of Cardiology 2020;48(6):467-471
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
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COVID-19
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Coronavirus Infections/diagnostic imaging*
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Heart Failure/etiology*
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Humans
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Pandemics
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Pneumonia, Viral/diagnostic imaging*
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Retrospective Studies
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SARS-CoV-2
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Tomography, X-Ray Computed
9.Preliminary Study on Clinical Features and CT Findings of Common-type Coronavirus Disease 2019 Patients in Peking Union Medical College Hospital.
Lan SONG ; Wei SONG ; Xin SUI ; Tiekuan DU ; Wu LIU ; Baiyu WANG ; Xiaoping LU ; Yan XU ; Qiwen YANG ; Wei CAO ; Zhengyu JIN
Acta Academiae Medicinae Sinicae 2020;42(3):376-382
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
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Aged
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Betacoronavirus
;
Coronavirus Infections
;
diagnostic imaging
;
Humans
;
Lung
;
Middle Aged
;
Pandemics
;
Pneumonia, Viral
;
diagnostic imaging
;
Retrospective Studies
;
Tomography, X-Ray Computed
10.Comparison of Recovery Phase CT Features between Mild/moderate and Severe/critical Coronavirus Disease 2019 Patients.
Wenbin ZOU ; Changyu LIU ; Yixin CAI ; Zhilin ZENG ; Ni ZHANG ; Xiangning FU
Acta Academiae Medicinae Sinicae 2020;42(3):370-375
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
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Aged
;
Betacoronavirus
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China
;
Coronavirus Infections
;
diagnostic imaging
;
Humans
;
Middle Aged
;
Pandemics
;
Pneumonia, Viral
;
diagnostic imaging
;
Retrospective Studies
;
Tomography, X-Ray Computed