You are here

Article Text

Article menu
Download PDFPDF
Editorial
Augmenting reality in echocardiography
  1. Veer Sangha1,2
  1. 1 Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, Connecticut, USA
  2. 2 Department of Engineering Science, Oxford University, Oxford, UK
  1. Correspondence to Mr Veer Sangha, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, Connecticut, USA; veer.sangha{at}yale.edu

https://doi.org/10.1136/heartjnl-2023-323443

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Echocardiography is a vital first-line imaging tool for the diagnosis and management of many cardiovascular diseases. Its availability and low cost have encouraged widespread use by clinicians for the diagnosis and management of patients with heart failure.1 Visual estimation is widely used to assess ejection fraction (EF), the percentage of blood the left ventricle pumps out during a contraction. Accurately determining the EF in patients with heart failure is crucial for the implementation of timely guideline-directed medical treatment. There is a substantial need for high-fidelity determination of EF in emergency settings. However, there is high interobserver variability with visual estimation methods, which can be compounded by inadequate quality of capture and lack of specialised training in both obtaining and interpreting echocardiograms in these settings.2

    The work presented by Choi et al 3 represents an important advance in reducing the burden of time and cost constraints in measuring cardiac function at the bedside. The authors demonstrate that providing …

    View Full Text

    Footnotes

    • Contributors VS is the sole contributor.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests VS is a coinventor on patents filed for several AI-ECG algorithms.

    • Provenance and peer review Commissioned; internally peer reviewed.

    Linked Articles