What type of study is this?

This is a Quantitative Study study.

September 17, 2025

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

Key Points

The introduced method produces vessel trees with high agreement to MRA imaging.
Utilizing K-medoid clustering allows for effective representation of VWI samples.
By eliminating the need for MRA, this method simplifies and expedites vessel wall imaging protocols.
The approach enhances the consistency of vascular assessments from VWI alone without added imaging risks.

Abstract

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.

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

Key Points

Abstract

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