Abstract #1429

A novel multicomponent T2 analysis for identification of sub-voxel compartments and quantification of myelin water fraction

Noam Omer¹, Tamar Blumenfeld-Katzir¹, Natalie Bnaiahu¹, Meirav Galun², and Noam Ben-Eliezer^1,3,4

¹Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel, ²Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel, ³Center for Advanced Imaging Innovation and Research (CAI2R), New-York University Langone Medical Center, New York, New York, NY, United States, ⁴Sagol School of Neuroscience, Tel-Aviv University, Tel Aviv, Israel

Multicomponent T₂ analysis (mcT₂) can be highly valuable for probing tissue microstructure. However, it remains challenging due to its ill-conditioned nature, and due to inherent contamination of multi spin-echo signals by stimulated echoes. We present a novel mcT₂ algorithm that tackles the high-dimensionality of this problem, using correlations between local and global features of the anatomy in question. The accuracy of this tool is demonstrated on phantoms and in vivo. Our results suggest that the method can accurately identify microscopic compartments, operate at realistic scan times, and be used estimate to estimate myelin content in vivo.

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