Abstract #4894

Vessel Wall Imaging-Dedicated Automatic Processing Pipeline (VWI-APP): Towards Efficient and Reliable Intracranial Plaque Quantification

Hanyue Zhou^1,2, Jiayu Xiao², Dan Ruan^1,3, and Zhaoyang Fan^2,4,5

¹Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, ²Radiology, University of Southern California, Los Angeles, CA, United States, ³Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States, ⁴Radiation Oncology, University of Southern California, Los Angeles, CA, United States, ⁵Biomedical Engineering, University of Southern California, Los Angeles, CA, United States

Synopsis

We propose an automatic pipeline for atherosclerosis plaque analysis based on magnetic resonance (MR) vessel wall imaging (VWI). The pipeline consists of five modules, i.e., 1) MR angiography (MRA) to VWI registration, 2) vessel centerline tracking, 3) vessel straightening and cross-sectional slices generating, 4) deep learning -based vessel wall and lumen segmentation, and 5) plaque quantification. The pipeline achieved good to excellent reliability for the clinically relevant plaque measures and largely reduced the analysis time required for physicians.

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