Abstract #4894
Vessel Wall Imaging-Dedicated Automatic Processing Pipeline (VWI-APP): Towards Efficient and Reliable Intracranial Plaque Quantification
Hanyue Zhou1,2, Jiayu Xiao2, Dan Ruan1,3, and Zhaoyang Fan2,4,5
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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