Abstract #1048

Single Breath-held, ECG-Free Cardiac CINE MRI using Parallel Imaging and Deep Learning Combined Image Reconstruction

Fei Han¹, Ziwu Zhou¹, Vahid Ghodrati Kouzehkonan¹, Yu Gao¹, Yingli Yang², and Peng Hu¹

¹Radiology, University of California, Los Angeles, Los Angeles, CA, United States, ²Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States

Cardiac CINE MRI is widely used for evaluating ventricular wall motion and cardiac function. Conventional cardiac CINE consists of ECG-triggered k-space segmented 2D acquisitions, each performed within a breath-hold. In this study, we propose an ECG-free, cardiac CINE protocol that covers the entire LV within a single breath-hold. Our solution is based on a highly accelerated real-time imaging that is enabled by our recently proposed parallel imaging and deep learning combined (PI-DL) image reconstruction. In this study, we evaluated the proposed solution in healthy volunteers and compare its performance with cardiac CINE images acquired using conventional protocol.

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