Improved visualization of free-running cardiac magnetic resonance by respiratory phase using principal component analysis

Ummul Afia Shammi ¹, Zhijian Luan ², Jia Xu ³

⁰Department of Biomedical, Biological & Chemical Engineering, University of Missouri, Columbia, MO, USA.

Research in Diagnostic and Interventional Imaging +

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December 16, 2024

View abstract on PubMed

Summary

New software mitigates respiratory motion during cardiac MRI (CMR) without ECG. It separates heartbeats by breathing phase, improving image quality and enabling clearer cardiac assessments, even with arrhythmias.

Area Of Science

Medical Imaging
Cardiovascular Imaging
Biomedical Engineering

Background

Cardiac Magnetic Resonance (CMR) imaging is crucial for diagnosing heart conditions.
Acquiring high-quality CMR images during free breathing without electrocardiogram (ECG) gating is challenging due to respiratory motion artifacts.
Existing methods often require ECG synchronization, limiting flexibility.

Purpose Of The Study

To develop and evaluate novel software for mitigating respiratory motion artifacts in cardiac MRI acquisitions.
To enable robust CMR imaging during breathing without ECG synchronization.
To improve the diagnostic quality of cardiac images by resolving respiratory and cardiac cycles.

Main Methods

Developed software utilizing principal component analysis (PCA) to resolve respiratory motions and cardiac cycles from DICOM files.
Algorithm automatically detects heartbeats from expiration and inspiration phases.
Evaluated respiratory motion correction on short-axis CMR images of 11 healthy subjects and 8 cardiac patients.
Two expert radiologists assessed image quality, including blood-myocardial contrast, endocardial interface definition, and motion artifacts.

Main Results

Software significantly improved correlation coefficients between cardiac cycles segregated by respiratory phase (0.94±0.03 at end-expiration, 0.90±0.08 at end-inspiration) compared to original scans (0.79).
Clinical assessment favored end-expiratory cardiac cycles, maintaining or enhancing image quality scores in 90% of healthy subjects and 83% of cardiac patients.
High performance was maintained even in the presence of arrhythmias and irregular breathing.

Conclusions

The developed software effectively mitigates respiratory motion in real-time CMR by segregating heartbeats from end-expiratory phases.
End-expiratory data provides improved image quality for cardiac assessments.
Inspiratory heartbeats can also be utilized for examining arrhythmias or specific end-inspiratory abnormalities.

Keywords:

Compressed sensing Free-breathing MRI Motion correction Post-processing Principal component analysis Real-time cardiac MRI

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