COVID-CAPS: A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray Images.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory disease coronavirus 2 (SARS-CoV-2), has led to millions of confirmed cases and deaths worldwide. Efficient diagnostic tools are in high demand, as rapid and large-scale testing plays a pivotal role in patient management and decelerating disease spread. This paper reviews current technologies used to detect SARS-CoV-2 in clinical laboratories as well as advances made for molecular, antigen-based, and immunological point-of-care testing, including recent developments in sensor and biosensor devices. The importance of the timing and type of specimen collection is discussed, along with factors such as disease prevalence, setting, and methods. Details of the mechanisms of action of the various methodologies are presented, along with their application span and known performance characteristics. Diagnostic imaging techniques and biomarkers are also covered, with an emphasis on their use for assessing COVID-19 or monitoring disease severity or complications. While the SARS-CoV-2 literature is rapidly evolving, this review highlights topics of interest that have occurred during the pandemic and the lessons learned throughout. Exploring a broad armamentarium of techniques for detecting SARS-CoV-2 will ensure continued diagnostic support for clinicians, public health, and infection prevention and control for this pandemic and provide advice for future pandemic preparedness.

https://cmr.asm.org/content/cmr/34/3/e00228-20.full.pdf

Tools and Techniques for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)/COVID-19 Detection.

The COVID-19 pneumonia is a global threat since it emerged in early December 2019. Driven by the desire to develop a computer-aided system for the rapid diagnosis of COVID-19 to assist radiologists and clinicians to combat with this pandemic, we retrospectively collected 206 patients with positive reverse-transcription polymerase chain reaction (RT-PCR) for COVID-19 and their 416 chest computed tomography (CT) scans with abnormal findings from two hospitals, 412 non-COVID-19 pneumonia and their 412 chest CT scans with clear sign of pneumonia are also retrospectively selected from participating hospitals. Based on these CT scans, we design an artificial intelligence (AI) system that uses a multi-scale convolutional neural network (MSCNN) and evaluate its performance at both slice level and scan level. Experimental results show that the proposed AI has promising diagnostic performance in the detection of COVID-19 and differentiating it from other common pneumonia under limited number of training data, which has great potential to assist radiologists and physicians in performing a quick diagnosis and mitigate the heavy workload of them especially when the health system is overloaded. The data is publicly available for further research at https://data.mendeley.com/datasets/3y55vgckg6/1https://data.mendeley.com/datasets/3y55vgckg6/1.

Automatic distinction between COVID-19 and common pneumonia using multi-scale convolutional neural network on chest CT scans

Role of computed tomography in COVID-19.

Point of Care Detection of COVID-19: Advancement in Biosensing and Diagnostic Methods

The purpose of this article was to perform a systematic review and meta-analysis regarding the diagnostic test accuracy of chest CT for detecting coronavirus disease 2019 (COVID-19). PubMed, Embase, Web of Science, and CNKI were searched up to March 12, 2020. We included studies providing information regarding diagnostic test accuracy of chest CT for COVID-19 detection. The methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity and specificity were pooled. Sixteen studies (n = 3186 patients) were included. The risks of bias in all studies were moderate in general. Pooled sensitivity was 92% (95% CI = 86–96%), and two studies reported specificity (25% [95% CI = 22–30%] and 33% [95% CI = 23–44%], respectively). There was substantial heterogeneity according to Cochran’s Q test (p < 0.01) and Higgins I2 heterogeneity index (96% for sensitivity). After dividing the studies into two groups based on the study site, we found that the sensitivity of chest CT was great in Wuhan (the most affected city by the epidemic) and the sensitivity values were very close to each other (97%, 96%, and 99%, respectively). In the regions other than Wuhan, the sensitivity varied from 61 to 98%. Chest CT offers the great sensitivity for detecting COVID-19, especially in a region with severe epidemic situation. However, the specificity is low. In the context of emergency disease control, chest CT provides a fast, convenient, and effective method to early recognize suspicious cases and might contribute to confine epidemic. • Chest CT has a high sensitivity for detecting COVID-19, especially in a region with severe epidemic, which is helpful to early recognize suspicious cases and might contribute to confine epidemic.

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Chest CT for detecting COVID-19: a systematic review and meta-analysis of diagnostic accuracy.

Background: No previous studies exist investigating the optimal intensity of uninterrupted anticoagulation with warfarin during radiofrequency catheter ablation (RFCA) for atrial fibrillation (AF) 

Efficacy and Safety of Uninterrupted Low-Intensity Warfarin for Radiofrequency Catheter Ablation of Atrial Fibrillation in the Elderly.

Background Left atrial appendage (LAA) morphology predicts stroke risk in patients with atrial fibrillation. However, it is not precisely understood how LAA morphology influences stroke risk. The present study aimed to investigate the relationship between LAA morphology and local thrombogenesis-related blood parameters in LAA. Methods and Results We enrolled 205 patients undergoing catheter ablation of atrial fibrillation. The prevalence of chicken wing-, cactus-, windsock-, and cauliflower-type LAAs were 23.9%, 32.7%, 29.3%, and 14.1%, respectively. Blood samples were collected from the femoral vein, left atrium, and LAA in each patient. The levels of blood parameters were tested for each blood sample. The cauliflower-type LAA was associated with elevated platelet P-selectin expression, and interleukin-6 levels and with lower NO levels in LAA blood samples (P<0.05) independent of LAA flow velocity and LAA volume. LAA flow velocity, which was lowest in the cauliflower-type LAA, was the only independent predictor of von Willebrand factor antigen and plasminogen activator inhibitor-1 levels in LAA blood samples. In femoral vein blood samples, no significant difference was detected in the above blood parameters among the four LAA morphological types. In all blood samples, the levels of thrombin-antithrombin complex, D-dimer, fibrinogen, and tissue plasminogen activator were comparable among the four LAA morphological types. Conclusions In patients with atrial fibrillation, LAA morphological types might be associated with local platelet activity, fibrinolysis function, endothelial dysfunction, and inflammation.

Left Atrial Appendage Morphology and Local Thrombogenesis-Related Blood Parameters in Patients With Atrial Fibrillation.

Background Circulating endothelial progenitor cells (EPCs) have regenerative capacities and play an important role in vessel wall homeostasis. When attracted to the site of vessel wall injury, EPCs rapidly differentiate into a functional layer as part of the healing process. The Genous TM endothelial progenitor cell (EPC) capturing stent is coated with anti-human CD34+ antibodies which combine with circulating EPCs from the peripheral blood to the stent surface. Objective This meta-analysis aims to explore the Genous TM endothelial progenitor cell capturing stent in coronary artery disease (CAD) adverse event rate after one-year follow-up. Methods PubMed, EMBASE and, Google Scholar databases were searched for eligible studies. CAD survival data and clinicopathological features were analyzed by expected shortfall (ES) and 95% CI. Fixed-effect model and random-effect model are used for summary statistics. Results 12 studies, including 15985 coronary artery disease (CAD) patients who received PCI treatment were included in this study. After 1-year follow-up, the rate of adverse event showed that the target vessel failure (TVF) was 8.5% (7.6%-17.4%), target vessel revascularization was 4.1% (TVR, 0-15.6%), target lesion revascularization was 4.2% (TLR, 3.7%-22%), myocardial infarction was 2.0% (MI, 1.8%-5.2%), major adverse cardiac events was 8.7% (MACE, 6.4%-28%), and the all-cause death was 4.0% (0-9.2). Conclusion After one-year follow-up, the incidence rate of Genous stent adverse events was stable in CAD patients. The study showed a better evaluation of Genous stent, and it provides a better reference for CAD clinical treatment.

Yong Sun

Papers

Chest CT for detecting COVID-19: a systematic review and meta-analysis of diagnostic accuracy.

Efficacy and Safety of Uninterrupted Low-Intensity Warfarin for Radiofrequency Catheter Ablation of Atrial Fibrillation in the Elderly.

Left Atrial Appendage Morphology and Local Thrombogenesis-Related Blood Parameters in Patients With Atrial Fibrillation.

The Adverse Events Rate of Endothelial Progenitor Cell Capturing Stent in the Treatment of CAD Patients.