cord-000308-cxr1ul7q	2011	
cord-005573-mryrl1s1	2018	
cord-010871-qyqs293j	2020	
cord-013065-oj0wsstz	2020	
cord-015352-2d02eq3y	2017	Lapierre; Montreal/CA Summary: Objectives: To review the classification of visceroatrial situs To describe the associated cardiac and non-cardiac anomalies To illustrate typical findings in fetuses, neonates and children To discuss the surgical consideration and the long-term follow-up in these patients Abstract: By definition, the type of situs is determined by the relationship between the atria and the adjacent organs. As is often the case, radiology in JIA is all about: knowing your clinicians (i.e. the pretest likelihood for disease) being technically eloquent (e.g. using high-resolution US probes, not delaying post-contrast MRI acquisitions) knowing what is normal (e.g. normal undulations in the articular surface, focal bone marrow signal variation) not being dogmatic about individual observations or measurements interpreting your findings in a clinical context The lecture will demonstrate similarities and differences among joints and modalities in children with variable-severity JIA.
cord-029675-7lmqp4jd	2020	
cord-252784-wfsq0u9o	2020	
cord-253572-9qixiew8	2020	
cord-257566-56h2jmn9	2020	
cord-261062-9zhe3ejy	2020	
cord-261328-prczsz9m	2020	
cord-262778-7vk6vcgk	2020	
cord-276225-tv70aakj	2020	
cord-282198-ugmv9om1	2020	
cord-285369-ktg2b9jb	2020	
cord-286071-zb8o95yf	2014	
cord-292341-uo54ghf3	2020	
cord-300013-6m1f4q5r	2020	
cord-303284-xwhxyy3d	2020	
cord-309194-jtouafgd	2020	
cord-309660-s8neq5x4	2020	In this study, we trained a neural network using LUS images of B lines from 3 different etiologies (hydrostatic pulmonary edema (HPE), ARDS and COVID-19). 16 The goal of this study was to determine if a deep neural network could distinguish between the B line profiles of 3 different disease profiles, namely 1) hydrostatic pulmonary edema (HPE); 2) non-COVID ARDS (NCOVID) causes; and 3) COVID-19 ARDS (COVID). On this independent data, the model demonstrated a strong ability to distinguish between the 3 relevant causes of B lines with AUCs at the encounter level of 1.0 (COVID), 0.934 (NCOVID), and 1.0 (HPE), producing an overall AUC of 0.978 for the classifier. In this study, a deep learning model was successfully trained to distinguish the underlying pathology in similar point-of-care lung ultrasound images containing B lines.
cord-318878-auk0hpk9	2020	
cord-320171-ifbpz42a	2020	We sought to determine the utility of lung ultrasound for early detection of pneumonia and for assessment of respiratory failure among patients with coronavirus disease 2019 (COVID-19). CONCLUSIONS: Lung ultrasound is feasible and useful as a rapid, sensitive, and affordable point-of-care screening tool to detect pneumonia and assess the severity of respiratory failure in patients hospitalized with COVID-19. In South Korea, there have been multiple confirmed cases related to local outbreak clusters, but there are no rapid, sensitive, affordable screening tools available to assess the presence of pneumonia, disease severity, or risk of respiratory fail-The Korean Journal of Internal Medicine. LUS performed on Day 4 showed a worsening of her pneumonia, with the lung aeration score of 5 points (Supplementary Fig. 5C ). In conclusion, LUS was feasible and useful for a rapid, sensitive, affordable point-of-care screening tool to detect pneumonia without radiation hazard and suggest the severity of respiratory failure for COVID-19 patients.
cord-320174-q364nq1f	2020	
cord-325352-k7aapnx3	2020	
cord-326051-p9017jx8	2020	
cord-333483-nr0akd7k	2020	
cord-334495-7y1la856	2020	From a clinical point of view, cardiac involvement during COVID-19 may present a wide spectrum of severity ranging from subclinical myocardial injury to well-defined clinical entities (myocarditis, myocardial infarction, pulmonary embolism and heart failure), whose incidence and prognostic implications are currently largely unknown due to a significant lack of imaging data. The use of integrated heart and lung multimodality imaging plays a central role in different clinical settings and is essential in diagnosis, risk stratification and management of COVID-19 patients. In this context, the use of multiple diagnostic imaging techniques may apply to both heart and lung to provide an integrated assessment of cardiac and pulmonary function and to refine diagnosis, risk stratification and management of COVID-19 patients. patients not requiring ICU, when clinical presentation and biomarker alterations suggest acute-onset myocardial inflammation, if the diagnosis is likely to impact on management, CMR may be considered to confirm acute myocarditis, after exclusion of alternative relevant clinical conditions, including ACS and HF, by means of other rapidly available imaging modalities (i.e. cardiac CT scan or TTE).
cord-338005-kbkvk94k	2020	
cord-341627-21m8rdhy	2020	
cord-344117-lr6roxej	2020	Reports from health services around the world have indicated that patients with diabetes mellitus and hypertension, two of the main causes of ESRD worldwide, and also advanced age and cardiovascular complications, two frequent accompanying conditions in dialysis patients, are more susceptible to SARS-CoV-2 infection and more prone to develop severe COVID-19 pneumonia, eventually requiring intensive care treatment [2, 6, 7] . The typical patterns detected by LUS in patients with COVID-19 pneumonia are characterized by B-lines in different forms, both separated and coalescent, an irregular and/or fragmented pleural line, peripheral small consolidations, and large consolidations with dynamic air bronchograms [3] (Fig. 7) (Additional file 5). If the B-lines pattern that can be observed by LUS in dialytic patients does not fully respect the typical characteristics of a COVID-19 pneumonia and cannot allow a definitive conclusion, we suggest to extend the ultrasound scan to the heart and the inferior vena cava (IVC).
cord-347631-78h9w2ty	2020	
cord-349641-4g4nue5s	2020	
cord-354204-23xkug85	2020	
cord-354411-4emzxu09	2020