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Updated: Oct 2, 2026
Cardiac Magnetic Resonance for the Evaluation of Suspected Cardiac Thrombus: Conventional and Emerging Techniques
Published on: June 11, 2019
Factor analysis of medical image sequences improves evaluation of first-pass MR imaging acquisitions for myocardial
Marc F Janier1, Alejandro N Mazzadi, Martine Lionnet
1From the Centre d'Exploration et de Recherche Médicales par Emission de Positons, Hôpital Cardio-Vasculaire et Pneumologique, Lyon, France.
Rationale And Objectives:
Factor analysis of medical image sequences (FAMIS) applied to gadolinium chelate-enhanced subsecond magnetic resonance (MR) imaging was evaluated as a postprocessing method for assessing myocardial perfusion in coronary artery disease (CAD).
Materials And Methods:
To assess the accuracy of motion correction, five normal volunteers underwent MR imaging at rest. Thirteen patients with well-documented CAD and no myocardial infarction underwent MR imaging at rest and after dipyridamole administration. After motion correction, a single myocardial tissue factor (FAMISt) image was obtained with FAMIS for each raw MR imaging series acquisition. To evaluate how FAMIS could improve the analysis of these acquisitions, five readers visually assessed myocardial perfusion with FAMISt and raw MR images, and a multicase, multireader receiver operating characteristic analysis was performed.
Results:
FAMISt images significantly improved detection of the perfusion defects when compared with raw MR images (P = .002). Areas under the receiver operating characteristic curves ranged from 0.84 to 0.93 with FAMISt images and from 0.48 to 0.85 with raw MR images.
Conclusion:
FAMIS applied to first-pass MR imaging series provided myocardial perfusion images that improve the objective assessment of myocardial perfusion in patients with CAD.
Insights
Factor analysis of medical image sequences (FAMIS) improves myocardial perfusion assessment in coronary artery disease (CAD) using MRI. FAMIS-generated images enhance the detection of perfusion defects compared to raw MRI data.
Area of Science:
- Cardiovascular Imaging
- Medical Image Analysis
- Radiology
Background:
- Assessing myocardial perfusion is crucial for diagnosing coronary artery disease (CAD).
- Subsecond, gadolinium-enhanced magnetic resonance (MR) imaging offers a method for evaluating blood flow in the heart muscle.
- Postprocessing techniques are needed to optimize the interpretation of complex MR imaging data.
Purpose of the Study:
- To evaluate Factor Analysis of Medical Image Sequences (FAMIS) as a postprocessing tool for myocardial perfusion assessment in CAD.
- To determine if FAMIS-generated images (FAMISt) improve the detection of perfusion defects compared to raw MR images.
- To assess the diagnostic performance of FAMISt images using a reader-based analysis.
Main Methods:
- FAMIS was applied to gadolinium-enhanced, subsecond MR imaging of the myocardium.
- Motion correction was performed on the MR imaging series.
- Five readers visually assessed myocardial perfusion using both FAMISt images and raw MR images.
- A multicase, multireader receiver operating characteristic (ROC) analysis was conducted.
Main Results:
- FAMISt images significantly improved the detection of myocardial perfusion defects compared to raw MR images (P = .002).
- Areas under the ROC curves were substantially higher for FAMISt images (0.84–0.93) than for raw MR images (0.48–0.85).
- This indicates a marked improvement in diagnostic accuracy with the FAMIS postprocessing method.
Conclusions:
- FAMIS applied to first-pass MR imaging series effectively generates myocardial perfusion images.
- The FAMIS technique significantly enhances the objective assessment of myocardial perfusion in patients with CAD.
- FAMIS represents a valuable advancement in the postprocessing of MR imaging for cardiovascular applications.
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