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Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Related Experiment Video

Updated: May 13, 2026

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
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High-Resolution Maps of Left Atrial Displacements and Strains Estimated With 3D Cine MRI Using Online Learning Neural

Christoforos Galazis, Samuel Shepperd, Emma J P Brouwer

    IEEE Transactions on Medical Imaging
    |March 3, 2025
    PubMed
    Summary

    We developed Aladdin, a novel tool using neural networks for analyzing left atrial (LA) function via 3D Cine MRI. Aladdin accurately assesses LA motion and deformation, aiding in diagnosing cardiac conditions like atrial fibrillation.

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    Area of Science:

    • Cardiovascular Imaging
    • Artificial Intelligence in Medicine
    • Cardiac Mechanics

    Background:

    • Left atrial (LA) function is crucial for cardiac health and understanding diseases such as atrial fibrillation.
    • Cine MRI offers detailed 3D characterization of LA motion and deformation, but lacks adequate analysis tools.
    • Current methods for assessing LA function are limited in scope and detail.

    Purpose of the Study:

    • To introduce Aladdin (Analysis of Left Atrial Displacements and DeformatIons using online learning neural Networks), a novel tool for 3D LA functional analysis.
    • To present a technical feasibility study of Aladdin's capability in characterizing global and regional 3D LA function.
    • To establish an atlas of LA function biomarkers from healthy volunteers.

    Main Methods:

    • Development of an online segmentation and image registration network within Aladdin.
    • Implementation of a specialized strain calculation pipeline for the LA.
    • Creation of LA Displacement Vector Field (DVF) magnitude and principal strain maps from Cine MRI data of healthy volunteers and cardiovascular disease (CVD) patients.

    Main Results:

    • Aladdin accurately tracks LA wall motion and deformation throughout the cardiac cycle.
    • Global LA function markers derived from Aladdin correlate well with 2D Cine MRI estimates.
    • Healthy individuals exhibited a more pronounced active contraction phase compared to CVD patients, who showed reduced overall LA function.
    • Aladdin identified regional abnormalities in LA deformation, potentially indicating focal pathology.

    Conclusions:

    • Aladdin provides a comprehensive, non-invasive method for characterizing 3D LA function.
    • The tool demonstrates potential for identifying subtle regional functional changes indicative of atrial pathophysiology.
    • Aladdin is expected to have significant clinical applications in the assessment and management of cardiovascular diseases affecting the left atrium.