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Abstract #5222

Improved assessment of microbleeds by highly-accelerated 3D SWAN imaging with deep learning-based reconstruction.

Yuka Ishimoto1, Tomohiro Shintaku1, Satoru Ide2, Keita Watanabe3, Kazuhiko Oyu1, Sera Kasai1, Miho Sasaki1, Haruka Nagaya1, Soichiro Tatsuo1, Atsushi Nozaki4, Xucheng Zhu5, Brian Burns5, Tetsuya Wakayama4, and Shingo Kakeda1
1Radiology, Hirosaki University Graduate School of Medicine, Hirosaki-shi, Japan, 2Radiology, University of Occupational and Environmental Health, Kitakyushu-shi, Japan, 3Kyoto Prefectural University of Medicine, Kyoto, Japan, 4GE HealthCare, Hino, Japan, 5GE HealthCare, Menlo Park, CA, United States

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Neuro

Motivation: While T2* weighted imaging evaluates microbleeds, high-resolution 3D SWI requires long acquisition times with motion artifact risks. Fast imaging is needed for monitoring ARIA-H in Alzheimer's treatment.

Goal(s): To evaluate the diagnostic performance of DL Speed (DLS), a vendor-supplied prototype version of Sonic DL, which enables high acceleration rates and short scan times, in detecting microbleeds using DLS-reconstructed 3D SWAN.

Approach: 71 cognitive decline patients underwent T2*WI and 2mm DLS-SWAN. Two neuroradiologists conducted readings with and without DLS-SWAN.

Results: 2mm DLS-SWAN achieved whole-brain imaging with high resolution in less than 2 minutes, resulting in detection of significantly more definite microbleeds than T2*WI.

Impact: DLS-SWAN can potentially be useful as a rapid 3D T2* technique for screening MRI at baseline in patients undergoing monoclonal antibody therapy for Alzheimer disease.

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