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Abstract #0531

Simultaneous Non-Contrast Angiography & IntraPlaque Hemorrhage (SNAP) Imaging for Atherosclerotic Disease Evaluation

Jinnan Wang1, Peter Brnert2, Huilin Zhao3, Xihai Zhao4, Niranjan Balu5, Marina S. Ferguson5, Thomas S. Hatsukami5, Jianrong Xu3, Chun Yuan5, William S. Kerwin5

1Philips Research North America, Briarcliff Manor, NY, United States; 2Philips Research Europe; 3Renji Hospital; 4Tsinghua University; 5University of Washington

Simultaneous Non-contrast Angiography and intraPlaque hemorrhage (SNAP) imaging was proposed and validated for detecting luminal stenosis and intraplaque hemorrhage in atherosclerosis patients in 1 scan. SNAP provides robust MRA delineation and sensitive hemorrahge detection when compared to the current techniques. It has the potential to become the first line imaging methods in clinics.

Keywords

accuracy accurately achieve achieved acquisition additionally address advantage agreement allows although angiography approaches approvals array arrow arrowheads arrows arteries artery atherosclerosis become bilateral blinded branches brought care carotid characterization chosen circulation clinical coded coil color computer containing contrast coronal correlation cover coverage custom delineated delineation detection diagnosed disease displayed duration dynamic enhanced environment equation established evaluating evaluation even events facilitate features female final flow generated good hemorrhage highest histology identified identify improved inflow interpolated inversion joint jointly kappa lesions like likely limitations lumen magnetization manor matched maximized negative neighboring nevertheless normalized north optimal optimized original overall patient patients plaque portion positive post potential programmed progression propose proposed pulse pulses radiology rage reconstruction recovery recruited reliance remarkable resolution review reviewer risk robust sample sensitive sensitivity separately simulation simultaneous slice slides slightly snap stroke strong strongest strongly subject subjects takes trains type unable underwent validate validated validation view viewing visualize visualized wall yuan