Abstract #1642

Dynamic, Regularized, Adaptive Cluster Optimization (DRACO) for Free-breathing Cardiac Cine MRI in Patients with Atrial Fibrillation

Zhengyang Ming^1,2, Arutyun Pogosyan³, Xinyu Dong³, J. Paul Finn^1,2, Anthony G. Christodoulou^2,4, Dan Ruan^1,4,5, and Kim-Lien Nguyen^1,2,3,4

¹Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, Los Angeles, CA, United States, ²Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, ³Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States, ⁴Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, ⁵Department of Radiation Oncology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States

Synopsis

Keywords: Arrhythmia, Arrhythmia

Motivation: Irregular cardiac motion can degrade image quality and preclude the use of conventional segmented cine MRI for quantitative evaluation of cardiac function. And it can be difficult for some patients to do multiple breath holds.

Goal(s): To evaluate a cluster-based algorithm and reconstruction approach for cine MRI in patients with atrial fibrillation under free-breathing condition.

Approach: Ten atrial fibrillation patients were scanned under breath-held and free-breathing conditions. Image quality, SNR, CNR, and edge sharpness were assessed.

Results: No significant difference in image quality scores, SNR, CNR, and edge sharpness were found for images obtained under breath-held and free-breathing conditions.

Impact: Adaptive cluster-based motion binning with temporal total variation reconstruction is effective at handling irregular cardiac motion and enables high quality, free-breathing cine MRI in patients with atrial fibrillation.

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