Abstract #3669

Improving Coronary Assessment in 3D Radial Cardiac MRI Using Self-Gating with K-Space Center Filtering, Motion Binning, and CS Reconstruction

Matteo Tagliabue^1,2,3, Adèle Mackowiak⁴, Li Feng⁵, Eva Peper^1,2, and Jessica Bastiaansen^1,2

¹Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland, ²Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland, ³Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland, ⁴Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁵Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States

Synopsis

Keywords: Vascular/Vessel Wall, Heart

Motivation: Accurate visualization of the coronaries is essential for cardiovascular assessment. This study aims to improve coronary sharpness by combining self-gating extracted from the k-space center of the SI-projection, motion binning, and low-rank compressed sensing reconstructions.

Goal(s): To improve coronary artery visualization with free-breathing non-contrast MRI at 3T.

Approach: Respiratory signal was extracted from the k-space center of the SI-projection in free-breathing whole-heart data. The data were binned and reconstructed with compressed sensing. Coronary sharpness was compared to the standard scanner reconstruction.

Results: Respiratory motion was extracted from whole-heart data, improving coronary artery visualization and vessel sharpness, confirming the effectiveness of the reconstruction technique.

Impact: This work presents an approach for automatic respiratory motion detection and binning that improves motion compensation of whole-heart images. It provides sharper visualization of the coronaries compared with conventional methods, potentially aiding clinicians in more reliable diagnosis of coronary disease.

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