Meeting Banner
Abstract #1914

Optimizing the T1-mapping GOAL-SNAP MRA with Histogram-Matching-Based Multi-Frame Combination

Jiaqi Dou1, Xiaoming Liu2,3, Ziming Xu1, Song Tian4, Jing Wang2, and Huijun Chen1
1Center for Biomedical Imaging Research, Tsinghua University, Beijing, China, 2Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Beijing, China, 3Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China, 4Philips Healthcare, Beijing, China

Synopsis

Keywords: Image Reconstruction, Vessels

Motivation: GOAL-SNAP, a sequence designed for T1 value measurement of vessel walls, shows promise in generating MRA images for intracranial vessel visualization, albeit with opportunities for further improvement.

Goal(s): To introduce a novel approach to optimize GOAL-SNAP MRA.

Approach: A histogram-matching-based approach was developed to optimize GOAL-SNAP MRA. This technique combined multiple GOAL-SNAP frames and utilizes histogram matching to suppress background signals and improve the contrast between vessels and background.

Results: Contrast-to-noise (CNR) and visualization evaluation demonstrated the effectiveness of the optimized GOAL-SNAP MRA, exhibiting comparable performance to TOF and superior visualization of distal vessels.

Impact: A novel histogram-matching-based multi-frame combination approach improved GOAL-SNAP MRA for intracranial vessel visualization and vascular stenosis assessment, with comparable performance to TOF and superior visualization of distal vessels.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords