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Related Concept Videos

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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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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: Sep 16, 2025

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging
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Inter-AI Agreement in Measuring Cine MRI-Derived Cardiac Function and Motion Patterns: A Pilot Study.

Kai Lin1, Roberto Sarnari2, Daniel Z Gordon2

  • 1Department of Radiology, Northwestern University, 737 N Michigan Avenue, Suite 1600, Chicago, IL, 60611, USA. kai-lin@northwestern.edu.

Journal of Imaging Informatics in Medicine
|July 8, 2025
PubMed
Summary
This summary is machine-generated.

AI tools for cardiac MRI analysis show agreement in some measurements but variations exist. These differences in cardiac function and motion indices must be considered when comparing study results.

Keywords:
AgreementArtificial intelligenceCardiac functionCine MRIMotion

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Area of Science:

  • Cardiovascular Imaging
  • Artificial Intelligence in Medicine
  • Medical Image Analysis

Background:

  • Manual analysis of cardiac MRI for heart motion is time-consuming.
  • AI tools automate cardiac MRI analysis, but their result consistency is unknown.

Purpose of the Study:

  • To investigate the agreement between AI-powered tools for measuring cardiac function and motion from cine MRI.
  • To evaluate the consistency of automated cardiac MRI analysis.

Main Methods:

  • Cine MRI datasets from 23 healthy volunteers were analyzed using two AI tools: Heart Deformation Analysis (HDA) and Circle CVI 42.
  • Key cardiac function indices (e.g., LVEF, LVM) and motion indices (e.g., strain rate) were calculated.
  • Agreement was assessed using t-tests, Pearson correlation (r), interclass correlation (ICC), and coefficient of variation (CoV).

Main Results:

  • Systematic biases were observed in cardiac function and motion index measurements.
  • Left ventricular ejection fraction (LVEF) and left ventricular mass (LVM) showed good agreement and were considered exchangeable between tools.
  • Circumferential strain rate demonstrated good agreement between the two AI tools.

Conclusions:

  • AI-powered tools for cine MRI analysis yield related but potentially differing results for cardiac function and motion indices.
  • Variations in measurements obtained from different AI tools should be carefully considered when interpreting and comparing study findings.
  • The study highlights the need for standardization or awareness of inter-tool variability in automated cardiac MRI analysis.