Wolstenhulme, S and McLaughlan, JR orcid.org/0000-0001-5795-4372 (2021) Lung ultrasound education: simulation and hands-on. The British Journal of Radiology, 94 (1119). 20200755. ISSN 0007-1285
Abstract
COVID-19 can cause damage to the lung, which can result in progressive respiratory failure and potential death. Chest radiography and CT are the imaging tools used to diagnose and monitor patients with COVID-19. Lung ultrasound (LUS) during COVID-19 is being used in some areas to aid decision-making and improve patient care. However, its increased use could help improve existing practice for patients with suspected COVID-19, or other lung disease. A limitation of LUS is that it requires practitioners with sufficient competence to ensure timely, safe, and diagnostic clinical/imaging assessments. This commentary discusses the role and governance of LUS during and beyond the COVID-19 pandemic, and how increased education and training in this discipline can be undertaken given the restrictions in imaging highly infectious patients. The use of simulation, although numerical methods or dedicated scan trainers, and machine learning algorithms could further improve the accuracy of LUS, whilst helping to reduce its learning curve for greater uptake in clinical practice.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Authors. Published by the British Institute of Radiology under the terms of the Creative Commons Attribution 4.0 Unported License http://creativecommons.org/licenses/by/4. 0/, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 26 May 2021 13:25 |
Last Modified: | 26 May 2021 13:25 |
Status: | Published |
Publisher: | British Institute of Radiology |
Identification Number: | 10.1259/bjr.20200755 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:174606 |