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Abstract #2042

In vivo validation of a data driven algorithm for multicomponent T2 mapping on a mice model of demyelination

Noam Omer1, Ella Wilczynski1, Neta Stern1, Tamar Blumenfeld-Katzir1, Meirav Galun2, and Noam Ben-Eliezer1,3,4,5,6
1Department of Biomedical Engineering, Tel-Aviv University, Tel-Aviv, Israel, 2Department of Computer Science and Applied Mathematics, Weitzman institute of science, Rehovot, Israel, 3Department of Orthopedics, Shamir Medical Center, Zerifin, Israel, 4Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel, 5Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel, 6Center for Advanced Imaging Innovation and Research (CAI2R), New-York University Langone Medical Center, New York, NY, United States

Multicomponent T2 analysis (mcT2) can provide a clinically-useful myelin biomarker in vivo. Its clinical applicability, however, is hindered by lack of gold standard technique that can overcome the ambiguity of fitting several T2 components to a single experimental signal. In this study we aimed to validate the utility of a novel data-driven mcT2 mapping algorithm for quantifying myelin content. To that end, we applied the mcT2 algorithm to 14 mice divided into two groups of mice: cuprizone-induced demyelination model, and controls. Results show excellent agreement between the mcT2 based myelin biomarker and ground truth quantification of myelin from immunohistochemical staining.

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