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Abstract #1916

Hierarchical Atlas Organization and Inference for MRA-free Full Intracranial Vessel Geometry Mapping

Eric Nguyen1, Jiayu Xiao2, Zhaoyang Fan2, and Dan Ruan1,3
1Physics and Biology in Medicine Graduate Program, University of California Los Angeles, Los Angeles, CA, United States, 2Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, 3Department of Radiation Oncology, University of California Los Angeles, Los Angeles, CA, United States

Synopsis

Keywords: Blood Vessels, Vessel Wall

Motivation: 3D MR vessel wall imaging is valuable to quantify plaque burden. Current protocols require a companion angiography image to localize and define vessel to guide subsequent VWI analysis, leading to additional effort, time, and risk of misalignment to VWI.

Goal(s): To develop an MRA-free intracranial vessel mapping method.

Approach: We define distance between VWI samples based on deformation complexity. K-medoid clustering is performed on a VWI-MRA atlas and the medoids are used to represent each cluster. Vessel trees is inferred from new VWI by deforming the closest medoid MRA.

Results: Our method manage to generate vessel tree with high agreement with MRA.

Impact: By organizing atlas with clustering, our approach provides a stable approach to infer vessel from VWI alone, mainlining the intrinsic consistency. This progress would simplify and expedite VWI protocol, and improve consistency.

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Keywords