Abstract #0703

High Resolution TOF-MRA Using SmartSpeed-AI for the Visualization of Lenticulostriate Arteries at 3.0 T: a Preliminary Study

Yuya Hirano¹, Noriyuki Fujima², Kinya Ishizaka¹, Takuya Aoike¹, Jihun Kwon³, Masami Yoneyama³, and Kohsuke Kudo^4,5

¹Department of Radiological Technology, Hokkaido University Hospital, Sappro, Japan, ²Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan, ³Philips Japan, Ltd, Tokyo, Japan, ⁴Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Japan, ⁵Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sappro, Japan

Synopsis

Keywords: Blood vessels, Image Reconstruction

SmartSpeed-AI is recently introduced as a physics driven type deep learning-based novel image reconstruction technique. We investigated the utility of SmartSpeed-AI for the better visibility of lenticulostriate artery (LSA) in high spatial resolution TOF-MRA by comparing the compressed-sensing sensitivity-encoding (compressed SENSE) algorithm. Both quantitative and qualitative assessment revealed that the visibility of LSAs were significantly higher under the SmartSpeed-AI reconstruction than compressed SENSE. SmartSpeed-AI can be helpful to provide superb image quality for the depiction of small arteries like LSA in high resolution TOF-MRA.

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