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1.
IEEE Trans Med Imaging ; 39(8): 2595-2605, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-690930

ABSTRACT

The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 2020. Detecting COVID-19 at early stage is essential to deliver proper healthcare to the patients and also to protect the uninfected population. To this end, we develop a dual-sampling attention network to automatically diagnose COVID-19 from the community acquired pneumonia (CAP) in chest computed tomography (CT). In particular, we propose a novel online attention module with a 3D convolutional network (CNN) to focus on the infection regions in lungs when making decisions of diagnoses. Note that there exists imbalanced distribution of the sizes of the infection regions between COVID-19 and CAP, partially due to fast progress of COVID-19 after symptom onset. Therefore, we develop a dual-sampling strategy to mitigate the imbalanced learning. Our method is evaluated (to our best knowledge) upon the largest multi-center CT data for COVID-19 from 8 hospitals. In the training-validation stage, we collect 2186 CT scans from 1588 patients for a 5-fold cross-validation. In the testing stage, we employ another independent large-scale testing dataset including 2796 CT scans from 2057 patients. Results show that our algorithm can identify the COVID-19 images with the area under the receiver operating characteristic curve (AUC) value of 0.944, accuracy of 87.5%, sensitivity of 86.9%, specificity of 90.1%, and F1-score of 82.0%. With this performance, the proposed algorithm could potentially aid radiologists with COVID-19 diagnosis from CAP, especially in the early stage of the COVID-19 outbreak.

2.
EClinicalMedicine ; 2020.
Article | WHO COVID | ID: covidwho-689222

ABSTRACT

BackgroundThe outbreak of a new coronavirus (SARS-CoV-2) poses a great challenge to global public health New and effective intervention strategies are urgently needed to combat the disease

3.
EClinicalMedicine ; 2020.
Article | WHO COVID | ID: covidwho-684336

ABSTRACT

Background The outbreak of a new coronavirus (SARS-CoV-2) poses a great challenge to global public health New and effective intervention strategies are urgently needed to combat the disease Methods We conducted an open-label, non-randomized, clinical trial involving moderate COVID-19 patients according to study protocol Patients were assigned in a 1:2 ratio to receive either aerosol inhalation treatment with IFN-κ and TFF2, every 48 h for three consecutive dosages, in addition to standard treatment (experimental group), or standard treatment alone (control group) The end point was the time to discharge from the hospital This study is registered with chictr org cn, ChiCTR2000030262 Findings A total of thirty-three eligible COVID-19 patients were enrolled from February 1, 2020 to April 6, 2020, eleven were assigned to the IFN-κ plus TFF2 group, and twenty-two to the control group Safety and efficacy were evaluated for both groups No treatment-associated severe adverse effects (SAE) were observed in the group treated with aerosol inhalation of IFN-κ plus TFF2, and no significant differences in the safety evaluations were observed between experimental and control groups CT imaging was performed in all patients with the median improvement time of 5 0 days (IQR 3 0–9 0) in the experimental group versus 8 5 days (IQR 3 0–17 0) in the control group (p<0 05) In addition, the experimental group had a significant shorten median time in cough relief (4 5 days [IQR 2 0–7 0]) than the control group did (10 0 days [IQR 6 0–21 0])(p<0 005), in viral RNA reversion of 6 0 days (IQR 2 0–13 0) in the experimental group vs 9 5 days (IQR 3 0–23 0) in the control group (p < 0 05), and in the median hospitalization stays of 12 0 days (IQR 7 0–20 0) in the experimental group vs 15 0 days (IQR 10 0–25 0) in the control group (p<0 001), respectively Interpretation Aerosol inhalation of IFN-κ plus TFF2 is a safe treatment and is likely to significantly facilitate clinical improvement, including cough relief, CT imaging improvement, and viral RNA reversion, thereby achieves an early release from hospitalization These data support to explore a scale-up trial with IFN-κ plus TFF2 Funding National Major Project for Control and Prevention of Infectious Disease in China, Shanghai Science and Technology Commission, Shanghai Municipal Health Commission

4.
Emerg Microbes Infect ; 9(1): 1537-1545, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-611841

ABSTRACT

Background: Novel coronavirus pneumonia (COVID-19) is prevalent around the world. We aimed to describe epidemiological features and clinical course in Shanghai. Methods: We retrospectively analysed 325 cases admitted at Shanghai Public Health Clinical Center, between January 20 and February 29, 2020. Results: 47.4% (154/325) had visited Wuhan within 2 weeks of illness onset. 57.2% occurred in 67 clusters; 40% were situated within 53 family clusters. 83.7% developed fever during the disease course. Median times from onset to first medical care, hospitalization and negative detection of nucleic acid by nasopharyngeal swab were 1, 4 and 8 days. Patients with mild disease using glucocorticoid tended to have longer viral shedding in blood and feces. At admission, 69.8% presented with lymphopenia and 38.8% had elevated D-dimers. Pneumonia was identified in 97.5% (314/322) of cases by chest CT scan. Severe-critical patients were 8% with a median time from onset to critical disease of 10.5 days. Half required oxygen therapy and 7.1% high-flow nasal oxygen. The case fatality rate was 0.92% with median time from onset to death of 16 days. Conclusion: COVID-19 cases in Shanghai were imported. Rapid identification, and effective control measures helped to contain the outbreak and prevent community transmission.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Adolescent , Adult , Aged , Aged, 80 and over , China/epidemiology , Coronavirus Infections/complications , Coronavirus Infections/diagnosis , Coronavirus Infections/therapy , Female , Follow-Up Studies , Health Status Indicators , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , Retrospective Studies , Time Factors , Treatment Outcome , Virus Shedding , Young Adult
5.
J Magn Reson Imaging ; 52(2): 397-406, 2020 08.
Article in English | MEDLINE | ID: covidwho-505553

ABSTRACT

BACKGROUND: Chest computed tomography (CT) has shown tremendous clinical potential for screening, diagnosis, and surveillance of COVID-19. However, safety concerns are warranted due to repeated exposure of X-rays over a short period of time. Recent advances in MRI suggested that ultrashort echo time MRI (UTE-MRI) was valuable for pulmonary applications. PURPOSE: To evaluate the effectiveness of UTE-MRI for assessing COVID-19. STUDY TYPE: Prospective. POPULATION: In all, 23 patients with COVID-19 and with an average interval of 2.81 days between hospital admission and image examination. FIELD STRENGTH/SEQUENCE: 3T; Respiratory-gated three-dimensional radial UTE pulse sequence. ASSESSMENT: Image quality score. Patient- and lesion-based interobserver and intermethod agreement for identifying the representative image findings of COVID-19. STATISTICAL TESTS: Wilcoxon-rank sum test, Kendall's coefficient of concordance (Kendall's W), intraclass coefficients (ICCs), and weighted kappa statistics. RESULTS: There was no significant difference between the image quality of CT and UTE-MRI (CT vs. UTE-MRI: 4.3 ± 0.4 vs. 4.0 ± 0.5, P = 0.09). Moreover, both patient- and lesion-based interobserver agreement of CT and UTE-MRI for evaluating the image signs of COVID-19 were determined as excellent (ICC: 0.939-1.000, P < 0.05; Kendall's W: 0.894-1.000, P < 0.05.). In addition, the intermethod agreement of two image modalities for assessing the representative findings of COVID-19 including affected lobes, total severity score, ground glass opacities (GGO), consolidation, GGO with consolidation, the number of crazy paving pattern, and linear opacities, as well as pseudocavity were all determined as substantial or excellent (kappa: 0.649-1.000, P < 0.05; ICC: 0.913-1.000, P < 0.05). DATA CONCLUSION: Pulmonary MRI with UTE is valuable for assessing the representative image findings of COVID-19 with a high concordance to CT. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 3 J. Magn. Reson. Imaging 2020;52:397-406.

6.
Ann. Transl. Med. ; 7(8)20200401.
Article in English | ELSEVIER | ID: covidwho-252339

ABSTRACT

Background: To evaluate the diagnostic efficacy of Densely Connected Convolutional Networks (DenseNet) for detection of COVID-19 features on high resolution computed tomography (HRCT). Methods: The Ethic Committee of our institution approved the protocol of this study and waived the requirement for patient informed consent. Two hundreds and ninety-five patients were enrolled in this study (healthy person: 149; COVID-19 patients: 146), which were divided into three separate non-overlapping cohorts (training set, n=135, healthy person, n=69, patients, n=66; validation set, n=20, healthy person, n=10, patients, n=10; test set, n=140, healthy person, n=70, patients, n=70). The DenseNet was trained and tested to classify the images as having manifestation of COVID-19 or as healthy. A radiologist also blindly evaluated all the test images and rechecked the misdiagnosed cases by DenseNet. Receiver operating characteristic curves (ROC) and areas under the curve (AUCs) were used to assess the model performance. The sensitivity, specificity and accuracy of DenseNet model and radiologist were also calculated. Results: The DenseNet algorithm model yielded an AUC of 0.99 (95% CI: 0.958-1.0) in the validation set and 0.98 (95% CI: 0.972-0.995) in the test set. The threshold value was selected as 0.8, while for validation and test sets, the accuracies were 95% and 92%, the sensitivities were 100% and 97%, the specificities were 90% and 87%, and the F1 values were 95% and 93%, respectively. The sensitivity of radiologist was 94%, the specificity was 96%, while the accuracy was 95%. Conclusions: Deep learning (DL) with DenseNet can accurately classify COVID-19 on HRCT with an AUC of 0.98, which can reduce the miss diagnosis rate (combined with radiologists' evaluation) and radiologists' workload.

7.
Theranostics ; 10(12): 5613-5622, 2020.
Article in English | MEDLINE | ID: covidwho-203318

ABSTRACT

Rationale: Some patients with coronavirus disease 2019 (COVID-19) rapidly develop respiratory failure or even die, underscoring the need for early identification of patients at elevated risk of severe illness. This study aims to quantify pneumonia lesions by computed tomography (CT) in the early days to predict progression to severe illness in a cohort of COVID-19 patients. Methods: This retrospective cohort study included confirmed COVID-19 patients. Three quantitative CT features of pneumonia lesions were automatically calculated using artificial intelligence algorithms, representing the percentages of ground-glass opacity volume (PGV), semi-consolidation volume (PSV), and consolidation volume (PCV) in both lungs. CT features, acute physiology and chronic health evaluation II (APACHE-II) score, neutrophil-to-lymphocyte ratio (NLR), and d-dimer, on day 0 (hospital admission) and day 4, were collected to predict the occurrence of severe illness within a 28-day follow-up using both logistic regression and Cox proportional hazard models. Results: We included 134 patients, of whom 19 (14.2%) developed any severe illness. CT features on day 0 and day 4, as well as their changes from day 0 to day 4, showed predictive capability. Changes in CT features from day 0 to day 4 performed the best in the prediction (area under the receiver operating characteristic curve = 0.93, 95% confidence interval [CI] 0.87~0.99; C-index=0.88, 95% CI 0.81~0.95). The hazard ratios of PGV and PCV were 1.39 (95% CI 1.05~1.84, P=0.023) and 1.67 (95% CI 1.17~2.38, P=0.005), respectively. CT features, adjusted for age and gender, on day 4 and in terms of changes from day 0 to day 4 outperformed APACHE-II, NLR, and d-dimer. Conclusions: CT quantification of pneumonia lesions can early and non-invasively predict the progression to severe illness, providing a promising prognostic indicator for clinical management of COVID-19.


Subject(s)
Coronavirus Infections/diagnostic imaging , Coronavirus Infections/pathology , Lung/pathology , Pneumonia, Viral/diagnostic imaging , Pneumonia, Viral/pathology , Adult , Aged , Algorithms , Artificial Intelligence , Betacoronavirus , China , Disease Progression , Female , Humans , Image Processing, Computer-Assisted , Lung/diagnostic imaging , Male , Middle Aged , Pandemics , Prognosis , Retrospective Studies , Tomography, X-Ray Computed
8.
Chin. J. Med. Imaging Technol. ; 3(36): 411-414, 20200320.
Article in Chinese | ELSEVIER | ID: covidwho-142401

ABSTRACT

Objective: To observe the clinical application value of chest low-dose CT (LDCT) in auxiliary diagnosis of corona virus disease 2019 (COVID-19). Methods: Totally 50 COVID-19 patients with positive 2019 novel coronavirus nucleic acid test of pharynx swabs were selected. All patients underwent routine dose chest CT examination on the first time (routine dose group), and followed chest LDCT for the review examination after treatment (LD group). The image quality of was evaluated by 2 imaging doctors. Kappa test was used to analyze the consistency of the image quality Results: of 2 groups evaluated by the two physicians. The X-ray radiation dose of the two CT scanning schemes were compared. Results: The consistency of image quality scores of 2 groups evaluated by 2 physicians was relatively high (Kappa=0.65, P<0.05). There was no significant difference of image quality between LD group and routine dose group (Z=-0.93, P=0.35). The effective radiation dose (ED)in LD group ([2.43±0.66]mSv) reduced by 39.55% (t=0.85, P<0.01) compared with that of the routine dose group ([4.02±1.03]mSv). Conclusion: Chest LDCT scan can be used for clinical screening and auxiliary diagnosis of COVID-19, which can ensure the image quality, meet clinical diagnosis requirements and reduce the dose of X-ray radiation.

9.
J Med Virol ; 2020 Apr 16.
Article in English | MEDLINE | ID: covidwho-66308

ABSTRACT

The aim of our study was to evaluate the therapeutic effect of antiviral drugs on coronavirus disease 2019 (COVID-19) pneumonia. Patients confirmed with COVID-19 pneumonia were enrolled and divided into seven groups according to the treatment option. Information including age, sex, and duration from illness onset to admission, clinical manifestations, and laboratory data at admission, and length of hospital stay were evaluated. The chest computed tomography (CT) imaging obtained at admission and after a 5-day treatment cycle were assessed. The clinical symptoms and laboratory tests at discharge were also assessed. At admission, no significant differences were found among the groups, including the duration from illness onset to admission, clinical symptoms, and main laboratory results. No significant differences were found among the groups in terms of the proportion of patients with pneumonia resolution (P = .151) after treatment or the length of hospital stay (P = .116). At discharge, 7 of 184 (4%) patients had a mild cough while their other symptoms had disappeared, and the proportion of patients with abnormal liver function and with increased leukocytes, neutrophils or erythrocyte sedimentation rate among the 184 patients were close to those at admission. According to the results, the inclusion of antiviral drugs in therapeutic regimens based on symptomatic treatment had no significant additional impact on the improvement in COVID-19 patients. In addition, the results of chest CT imaging, clinical manifestations, and laboratory tests at discharge were not completely consistent.

11.
Radiology ; 295(1): 210-217, 2020 04.
Article in English | MEDLINE | ID: covidwho-13063

ABSTRACT

BackgroundThe chest CT findings of patients with 2019 Novel Coronavirus (2019-nCoV) pneumonia have not previously been described in detail.PurposeTo investigate the clinical, laboratory, and imaging findings of emerging 2019-nCoV pneumonia in humans.Materials and MethodsFifty-one patients (25 men and 26 women; age range 16-76 years) with laboratory-confirmed 2019-nCoV infection by using real-time reverse transcription polymerase chain reaction underwent thin-section CT. The imaging findings, clinical data, and laboratory data were evaluated.ResultsFifty of 51 patients (98%) had a history of contact with individuals from the endemic center in Wuhan, China. Fever (49 of 51, 96%) and cough (24 of 51, 47%) were the most common symptoms. Most patients had a normal white blood cell count (37 of 51, 73%), neutrophil count (44 of 51, 86%), and either normal (17 of 51, 35%) or reduced (33 of 51, 65%) lymphocyte count. CT images showed pure ground-glass opacity (GGO) in 39 of 51 (77%) patients and GGO with reticular and/or interlobular septal thickening in 38 of 51 (75%) patients. GGO with consolidation was present in 30 of 51 (59%) patients, and pure consolidation was present in 28 of 51 (55%) patients. Forty-four of 51 (86%) patients had bilateral lung involvement, while 41 of 51 (80%) involved the posterior part of the lungs and 44 of 51 (86%) were peripheral. There were more consolidated lung lesions in patients 5 days or more from disease onset to CT scan versus 4 days or fewer (431 of 712 lesions vs 129 of 612 lesions; P < .001). Patients older than 50 years had more consolidated lung lesions than did those aged 50 years or younger (212 of 470 vs 198 of 854; P < .001). Follow-up CT in 13 patients showed improvement in seven (54%) patients and progression in four (31%) patients.ConclusionPatients with fever and/or cough and with conspicuous ground-glass opacity lesions in the peripheral and posterior lungs on CT images, combined with normal or decreased white blood cells and a history of epidemic exposure, are highly suspected of having 2019 Novel Coronavirus (2019-nCoV) pneumonia.© RSNA, 2020.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections/diagnostic imaging , Lung/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Tomography, X-Ray Computed , Adolescent , Adult , Age Factors , China/epidemiology , Clinical Laboratory Techniques , Coronavirus Infections/complications , Coronavirus Infections/diagnosis , Coronavirus Infections/pathology , Cough/etiology , Female , Fever/etiology , Humans , Leukocyte Count , Lung/pathology , Male , Middle Aged , Pneumonia, Viral/complications , Pneumonia, Viral/pathology , Real-Time Polymerase Chain Reaction , Retrospective Studies , Young Adult
12.
Radiology ; 295(1): 210-217, 2020 04.
Article in English | MEDLINE | ID: covidwho-465

ABSTRACT

BackgroundThe chest CT findings of patients with 2019 Novel Coronavirus (2019-nCoV) pneumonia have not previously been described in detail.PurposeTo investigate the clinical, laboratory, and imaging findings of emerging 2019-nCoV pneumonia in humans.Materials and MethodsFifty-one patients (25 men and 26 women; age range 16-76 years) with laboratory-confirmed 2019-nCoV infection by using real-time reverse transcription polymerase chain reaction underwent thin-section CT. The imaging findings, clinical data, and laboratory data were evaluated.ResultsFifty of 51 patients (98%) had a history of contact with individuals from the endemic center in Wuhan, China. Fever (49 of 51, 96%) and cough (24 of 51, 47%) were the most common symptoms. Most patients had a normal white blood cell count (37 of 51, 73%), neutrophil count (44 of 51, 86%), and either normal (17 of 51, 35%) or reduced (33 of 51, 65%) lymphocyte count. CT images showed pure ground-glass opacity (GGO) in 39 of 51 (77%) patients and GGO with reticular and/or interlobular septal thickening in 38 of 51 (75%) patients. GGO with consolidation was present in 30 of 51 (59%) patients, and pure consolidation was present in 28 of 51 (55%) patients. Forty-four of 51 (86%) patients had bilateral lung involvement, while 41 of 51 (80%) involved the posterior part of the lungs and 44 of 51 (86%) were peripheral. There were more consolidated lung lesions in patients 5 days or more from disease onset to CT scan versus 4 days or fewer (431 of 712 lesions vs 129 of 612 lesions; P < .001). Patients older than 50 years had more consolidated lung lesions than did those aged 50 years or younger (212 of 470 vs 198 of 854; P < .001). Follow-up CT in 13 patients showed improvement in seven (54%) patients and progression in four (31%) patients.ConclusionPatients with fever and/or cough and with conspicuous ground-glass opacity lesions in the peripheral and posterior lungs on CT images, combined with normal or decreased white blood cells and a history of epidemic exposure, are highly suspected of having 2019 Novel Coronavirus (2019-nCoV) pneumonia.© RSNA, 2020.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections/diagnostic imaging , Lung/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Tomography, X-Ray Computed , Adolescent , Adult , Age Factors , China/epidemiology , Clinical Laboratory Techniques , Coronavirus Infections/complications , Coronavirus Infections/diagnosis , Coronavirus Infections/pathology , Cough/etiology , Female , Fever/etiology , Humans , Leukocyte Count , Lung/pathology , Male , Middle Aged , Pneumonia, Viral/complications , Pneumonia, Viral/pathology , Real-Time Polymerase Chain Reaction , Retrospective Studies , Young Adult
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