Abstract #4124

Deep learning based whole heart T2-weighted dark blood imaging in a single breath hold

Xianghu Yan¹, Lu Huang¹, Lingping Ran¹, Yi Luo¹, Yuwei Bao¹, Shuheng Zhang², Shiyu Zhang², Yongquan Ye³, Jian Xu³, and Liming Xia¹

¹Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, ²United Imaging Healthcare, Shanghai, China, ³UIH America, Inc., Houston, TX, United States

Synopsis

Cardiovascular magnetic resonance (CMR) T2-weighted dark blood (T2W-DB) imaging has great diagnostic value for detecting myocardial edema. In this study, a novel deep learning based acceleration framework (AI-assisted Compressed Sensing, ACS) was applied to a single-shot T2W-DB sequence for single breath-hold whole heart (9 slices) imaging. Both quantitative and qualitative assessment of the images suggested that the ACS T2-DB sequence offered better image quality with greatly reduced total scan time and the simplified scanning workflow.

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