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1.
Natl Sci Rev ; 8(4): nwab006, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1254806

ABSTRACT

After a short recovery period, COVID-19 reinfections could occur in convalescent patients, even those with measurable levels of neutralizing antibodies. Effective vaccinations and protective public health measures are recommended for the convalescent COVID-19 patients.

2.
Optik (Stuttg) ; 241: 167100, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1220866

ABSTRACT

Since discovered in Hubei, China in December 2019, Corona Virus Disease 2019 named COVID-19 has lasted more than one year, and the number of new confirmed cases and confirmed deaths is still at a high level. COVID-19 is an infectious disease caused by SARS-CoV-2. Although RT-PCR is considered the gold standard for detection of COVID-19, CT plays an important role in the diagnosis and evaluation of the therapeutic effect of COVID-19. Diagnosis and localization of COVID-19 on CT images using deep learning can provide quantitative auxiliary information for doctors. This article proposes a novel network with multi-receptive field attention module to diagnose COVID-19 on CT images. This attention module includes three parts, a pyramid convolution module (PCM), a multi-receptive field spatial attention block (SAB), and a multi-receptive field channel attention block (CAB). The PCM can improve the diagnostic ability of the network for lesions of different sizes and shapes. The role of SAB and CAB is to focus the features extracted from the network on the lesion area to improve the ability of COVID-19 discrimination and localization. We verify the effectiveness of the proposed method on two datasets. The accuracy rate of 97.12%, specificity of 96.89%, and sensitivity of 97.21% are achieved by the proposed network on DTDB dataset provided by the Beijing Ditan Hospital Capital Medical University. Compared with other state-of-the-art attention modules, the proposed method achieves better result. As for the public COVID-19 SARS-CoV-2 dataset, 95.16% for accuracy, 95.6% for F1-score and 99.01% for AUC are obtained. The proposed network can effectively assist doctors in the diagnosis of COVID-19 CT images.

3.
Int J Infect Dis ; 104: 77-82, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1065180

ABSTRACT

BACKGROUND AND PURPOSE: An increasing number of reports have observed thrombosis in severe cases of COVID-19. The aim of this study was to evaluate the incidence of thromboembolism in mild/moderate cases of COVID-19. All of the patients had normal coagulation tests and none had any overt thrombotic complications. Our findings indicate that it is important to screen the thrombotic status of cases with mild/moderate COVID-19. METHODS: Between 11 June and 8 July 2020, 23 patients with mild/moderate COVID-19 pneumonia consented to having computed tomography pulmonary angiography (CPTA) and computed tomography venography (CTV) scans of the lungs and extremity veins. Doppler ultrasound (DUS) was also performed in all patients for screening. The incidence, clinical manifestations, laboratory examinations, imaging features, and prognosis, of patients with venous thromboembolism (VTE) were analyzed and compared with those of patients with COVID-19 pneumonia without VTE. RESULTS: Nineteen patients (82.6%) had VTE, mainly distal limb thrombosis. Only one of the VTE patients was positive when screened by DUS; the other VTE patients were negative by DUS. All of the mild/moderate patients with VTE were screened by CTPA + CTV. Blood tests for inflammatory, coagulation, and biochemical, parameters were all within the normal range, except for WBC and LDH. CONCLUSIONS: When using CTV screening for DVT, we found that the incidence of thrombosis in patients with mild/moderate COVID-19 markedly increased to 82.6% (19/23). Screening for thrombosis is therefore important in patients with COVID-19. CTV is more sensitive than DUS for the detection of thrombosis. More research is now needed to evaluate the significance of thrombosis in COVID-19 pneumonia.


Subject(s)
COVID-19/complications , SARS-CoV-2 , Venous Thromboembolism/epidemiology , Adult , Female , Humans , Male , Middle Aged , Prevalence , Tomography, X-Ray Computed/methods , Ultrasonography, Doppler , Venous Thromboembolism/diagnostic imaging
4.
Quant Imaging Med Surg ; 11(1): 380-391, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-958500

ABSTRACT

Background: With the global outbreak of coronavirus disease 2019 (COVID-19), chest computed tomography (CT) is vital for diagnosis and follow-up. The increasing contribution of CT to the population-collected dose has become a topic of interest. Radiation dose optimization for chest CT of COVID-19 patients is of importance in clinical practice. The present study aimed to investigate the factors affecting the detection of ground-glass nodules and exudative lesions in chest CT among COVID-19 patients and to find an appropriate combination of imaging parameters that optimize detection while effectively reducing the radiation dose. Methods: The anthropomorphic thorax phantom, with 9 spherical nodules of different diameters and CT values of -800, -630, and 100 HU, was used to simulate the lesions of COVID-19 patients. Four custom-simulated lesions of porcine fat and ethanol were also scanned at 3 tube potentials (120, 100, and 80 kV) and corresponding milliampere-seconds (mAs) (ranging from 10 to 100). Separate scans were performed at pitches of 0.6, 0.8, 1.0, 1.15, and 1.49, and at collimations of 10, 20, 40, and 80 mm at 80 kV and 100 mAs. CT values and standard deviations of simulated nodules and lesions were measured, and radiation dose quantity (volume CT dose index; CTDIvol) was collected. Contrast-to-noise ratio (CNR) and figure of merit (FOM) were calculated. All images were subjectively evaluated by 2 radiologists to determine whether the nodules were detectable and if the overall image quality met diagnostic requirements. Results: All simulated lesions, except -800 HU nodules, were detected at all scanning conditions. At a fixed voltage of 120 or 100 kV, with increasing mAs, image noise tended to decrease, and the CNR tended to increase (F=9.694 and P=0.033 for 120 kV; F=9.028 and P=0.034 for 100 kV). The FOM trend was the same as that of CNR (F=2.768 and P=0.174 for 120 kV; F=1.915 and P=0.255 for 100 kV). At 80 kV, the CNRs and FOMs had no significant change with increasing mAs (F=4.522 and P=0.114 for CNRs; F=1.212 and P=0.351 for FOMs). For the 4 nodules of -800 and -630 HU, CNRs had no statistical differences at each of the 5 pitches (F=0.673, P=0.476). The CNRs and FOMs at each of the 4 collimations had no statistical differences (F=2.509 and P=0.125 for CNRs; F=1.485 and P=0.309 for FOMs) for each nodule. CNRs and subjective evaluation scores increased with increasing parameter values for each imaging iteration. The CNRs of 4 -800 HU nodules in the qualified images at the thresholds of scanning parameters of 120 kV/20 mAs, 100 kV/40 mAs, and 80 kV/80 mAs, had statistical differences (P=0.038), but the FOMs had no statistical differences (P=0.085). Under the 3 threshold conditions, the CNRs and FOMs of the 4 nodules were highest at 100 kV and 40 mAs (1.6 mGy CTDIvol). Conclusions: For chest CT among COVID-19 patients, it is recommended that 100 kV/40 mAs is used for average patients; the radiation dose can be reduced to 1.6 mGy with qualified images to detect ground-glass nodules and exudation lesions.

5.
Chin. J. Radiol. ; 6(54): 544-547, 20200610.
Article in Chinese | ELSEVIER | ID: covidwho-682774

ABSTRACT

Objective: To investigate the value of CT findings in predicting thetransformation of clinical types of COVID-19. Methods: From January 24 to February 6, 2020, the clinical and chest CT data of patients with common COVID-19 were analyzed retrospectively. A total of 64 patients were enrolled, including 32 males and 32 females, aged 18-76 (45±15) years. Based on the fact whether patients’ conditions had deteriorated into severe type, all the cases were divided into common type group (51 cases) and deteriorated type group (13 cases). Differences of CT findings in the two groups of patients were analyzed, and visual semi-quantitative scores were introduced to evaluate the pneumonia. Results: Compared with the common type group, the deteriorated type group was more likely to involve the left upper lobe, the right middle lobe and the lung far away from the pleura. The differences between the two groups were statistically significant (χ²= 5.897, P=0.027; χ²=8.549, P=0.005; χ²=10.169,P=0.002). The median of the involved lobes were 2 (1,5) in the common type group and 5 (4,5) in the deteriorated type group. The difference between the two groups was statistically significant (Z =-3.303, P=0.001). Taking the involved lobes (n=4) as the threshold, the sensitivity and specificity of the diagnosis of the common type to the deteriorated type patients were the highest, 76.9% and 74.5% respectively, and the area under the ROC curve was 0.787. Pneumonia score of the deteriorated group was 10 (4,16), higher than that of the common group [4 (1,13)], and the difference was statistically significant (Z=-4.040, P<0.001). Pneumonia score 8 as the threshold, the sensitivity and specificity of the general severe group were the highest, 69.2% and 86.3% respectively, and the area under ROC curve was 0.863. Conclusions: CT imaging has a profound value in the early prediction of deterioration in clinical type of COVID-19. It can help evaluate the severity of pneumonia in early stage. Range of lesions might be an important indicator for prognosis of common type COVID-19.

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