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Abstract #4407

Estimating distributions of diffusion tensors and longitudinal relaxation rates in the brain via Monte-Carlo inversion: a proof of principle

Alexis Reymbaut1,2, Jeffrey Critchley3, Giuliana Durighel3, Tim Sprenger4,5, Michael Sughrue6, and Daniel Topgaard1,2
1Physical Chemistry, Lund University, Lund, Sweden, 2Random Walk Imaging AB, Lund, Sweden, 3Spectrum Medical Imaging, Sydney, Australia, 4Karolinska Institute, Stockholm, Sweden, 5GE Healthcare, Stockholm, Sweden, 6Charlie Teo Foundation, Sydney, Australia

Conventional $$$T_1$$$-mapping techniques are only sensitive to voxel-averaged $$$T_1$$$ values, which hinders the study of fiber-specific myelination changes in the developing, aging or diseased brain. While recent works have focused on combining diffusion- and $$$T_1$$$- weightings to access orientation-resolved $$$T_1$$$ values, they rely on assumptions regarding the voxel content. This work combines a prototype diffusion-relaxation MR acquisition and a Monte-Carlo inversion method to extract intra-voxel nonparametric 5D distributions of diffusion tensors and longitudinal relaxation rates $$$R_1=1/T_1$$$ without the use of limiting assumptions. Estimated $$$R_1$$$ values are then mapped onto nonparametric orientation distribution functions, thereby yielding fiber-specific longitudinal relaxation rates.

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