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Abstract #2823

Vasuclar density mapping in AD mice with Super-resolution-resolved MION-based MRI

Xiaoqing Alice Zhou1,2, Xiaochen Liu1,2, Hongwei Li1,2, David Hike1,2, Charles Reilly1,2, Sohail Mohammed1,2, Changrun Lin1,2, Matthew Rosen1,2, Juan Eugenio Iglesias1,2, and Xin Yu1,2
1A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Vessels

Motivation: Altered angiogenesis is reported to be a key feature of vascular perturbation in AD brains.

Goal(s): There is missing global mapping tool to investigate the brain-wide vascular distribution pattern changes due to degenerative pathogenesis in AD brains.

Approach: Here, we applied the pre-trained 3D U-net to super-resolve iron-particle (MION)-based CBV images from 75µm to 37.5 µm.

Results: By performing voxel-wise differential vascular density mapping analysis, we have revealed AD-specific vascular distribution changes from in vivo MION-based MRI images.

Impact: We developed an ultra-high resolution MION-based vascular density mapping method to verify the altered brain-wide vascular distribution pattern in AD mice. Using a pre-trained 3D U-net neural network, we can produce vascular maps with super-resolved 37.5µm isotropic resolution.

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Keywords