Us2.ai Echo Copilot

Provides automated echo analysis of all heart chambers, using both 2D and Doppler views.

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Overview

Heart disease remains a significant cause of death around the world.¹ Echocardiography is a safe, affordable, front-line tool used to diagnose and assess heart disease.² However, widespread application of Echo is currently limited by lack of access, inter-operator variability and shortage and burnout of sonographers.³

Us2.ai's AI solution aims to reduce the time to process and interpret echocardiograms with zero variability and with accuracy comparable to expert clinicians.⁴

The first fully automated AI software with validated global longitudinal strain in patients with and without atrial fibrillation; plus regional strain validated in real-world datasets; plus accurate identification of patients with heart failure, as well as those with regional wall-motion abnormalities.⁵

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Features

  • Fully automated reporting with disease detection and editable measurements.
  • Facilitates the possible detection of multiple disease conditions and longitudinal surveillance through AI structuring of echo images.
  • Reports on heart structure and function, with fully automated analyses of all heart chambers using both 2D and Doppler views. 
  • International reference guidelines are integrated into the full report.
  • Provides an interactive report and breakdown of each measurement. The operator may choose to manually amend individual measurements and once done the report will automatically be updated to reflect the new values.

Us2.ai is FDA-cleared and CE-marked and is also available in UK, Canada, Australia, New Zealand and Singapore.

Benefits

  • Aims for greater workflow efficiency in echo labs, reducing the echo analysis time and preserving the sonographer taskforce, who can then focus on patient interaction and care.
  • Provides full reporting on 23 measurements with the ability to provide indications for disease detection.
  • Agreement between Al processing and expert human interpretation was demonstrated across a wide range of echocardiographic measurements.⁴
  • A study showed that deep learning algorithms can automatically annotate 2D videos and Doppler modalities with similar accuracy to manual measurements by expert sonographers. Use of an automated workflow might accelerate access, improve quality, and reduce costs in diagnosing and managing heart failure globally.⁶

 

Image examples

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If you’re interested in learning more about this solution, or the 100+ other applications we have available on Blackford platform book a call with our friendly team now!

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We’d welcome the opportunity to learn more about your AI needs and to explain how partnering with Blackford can drive efficiency and provide ongoing value.

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¹World Health Organization. Cardiovascular diseases (CVDs) [Internet]. World Health Organization. World Health Organization; 2021. Available from: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds)
 
²Papolos, A., Narula, J., Bavishi, C., Chaudhry, F. A. & Sengupta, P.P. U. S. Hospital use of echocardiography: insights from the nationwide inpatient sample. J. Am. Coll. Cardiol. 67, 502–511 (2016).
 
³Urgent action required to rebuild echo workforce [Internet, cited 2023 Sep 8]. Available at: https://www.bsecho.org/Public/Public/News/Articles/2023/2023-06/202306-workforce.asp
 

⁴Tromp J, et al. A formal validation of a deep learning- based automated workflow for the interpretation of the echocardiogram. Nat Commun 13.1 (2022): 6776 

⁵Myhre PL, Hung C, Frost M, Jiang Z, Wouter Ouwerkerk, Teramoto K, et al. External validation of a deep learning algorithm for automated echocardiographic strain measurements. European heart journal. 2023 Nov 20;‌

⁶Tromp J, Seekings PJ, Hung CL, Iversen MB, Frost MJ, Ouwerkerk W, et al. Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study. The Lancet Digital Health [Internet]. 2021 Dec 1;