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Related Concept Videos

Imaging Studies for Cardiovascular System I:Echocardiography01:17

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Cardiac imaging studies encompass a wide range of noninvasive and minimally invasive techniques designed to visualize the heart's structure and function in detail. One such technique is echocardiography, which uses high-frequency ultrasound waves to produce detailed images of the heart, known as echocardiograms.
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Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
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Echocardiography plays a role in assessing cardiac health and detecting heart conditions, with various types providing critical insights for diagnosis and treatment.
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Related Experiment Video

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Evaluation of Left Ventricular Structure and Function using 3D Echocardiography
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Real-time deep learning-based image guiding and automated left ventricular measurements to reduce test-retest

Håkon Pettersen1,2, Sigbjorn Sabo1,3, David Pasdeloup1

  • 1Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Trøndelag, Norway.

Open Heart
|December 8, 2025
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Summary

Artificial intelligence (AI)-assisted echocardiography, combining deep learning (DL)-based real-time guiding and automated measurements, significantly reduced variability in left ventricular (LV) measurements. Automated measurements proved more beneficial than real-time guiding for experienced operators.

Keywords:
Diagnostic ImagingEchocardiographyHeart Failure

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Area of Science:

  • Cardiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Echocardiography is crucial for assessing left ventricular (LV) function.
  • Variability in manual measurements can impact diagnostic accuracy.
  • Deep learning (DL) offers potential for improving echocardiographic analysis.

Purpose of the Study:

  • To evaluate the impact of combining real-time DL-based guiding and automated measurements on LV volumetric and strain analysis.
  • To compare the variability of LV measurements using AI-assisted echocardiography versus standard echocardiography.

Main Methods:

  • 47 patients with cardiac pathology underwent echocardiography by two sonographers and a reference cardiologist.
  • One sonographer per patient used a real-time DL guiding tool to prevent LV foreshortening.
  • AI-assisted echocardiography (automated DL measurements) was compared to standard echocardiography (manual measurements).

Main Results:

  • AI-assisted echocardiography showed significantly lower coefficients of variation for LV end-diastolic volume (EDV), end-systolic volume (ESV), and global longitudinal strain (GLS) compared to standard echocardiography.
  • Coefficients of variation for LV ejection fraction (EF) were similar between the two methods.
  • Exploratory analyses indicated that automated measurements, not the guiding tool, were responsible for the improved variability.

Conclusions:

  • AI-assisted echocardiography, integrating DL guiding and automated measurements, substantially decreases variability in LV EDV, ESV, and GLS.
  • For experienced operators, automated measurements offer greater benefits than real-time guiding in echocardiography.