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Towards non-parametric fiber-specific $T_1$ relaxometry in the human brain

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Document pages: 11 pages

Abstract: Purpose: To estimate fiber-specific $T 1$ values, i.e. proxies for myelincontent, in heterogeneous brain tissue. Methods: A diffusion-$T 1$ correlationexperiment was carried out on an in vivo human brain using tensor-valueddiffusion encoding and multiple repetition times. The acquired data wasinverted using a Monte-Carlo inversion algorithm that retrieves non-parametricdistributions $ mathcal{P}( mathbf{D},R 1)$ of diffusion tensors andlongitudinal relaxation rates $R 1 = 1 T 1$. Orientation distribution functions(ODFs) of the highly anisotropic components of $ mathcal{P}( mathbf{D},R 1)$were defined to visualize orientation-specific diffusion-relaxation properties.Finally, Monte-Carlo density-peak clustering (MC-DPC) was performed to quantifyfiber-specific features and investigate microstructural differences betweenwhite-matter fiber bundles. Results: Parameter maps corresponding to$ mathcal{P}( mathbf{D},R 1)$ s statistical descriptors were obtained,exhibiting the expected $R 1$ contrast between brain-tissue types. Our ODFsrecovered local orientations consistent with the known anatomy and indicatedpossible differences in $T 1$ relaxation between major fiber bundles. Thesedifferences, confirmed by MC-DPC, were in qualitative agreement with previousmodel-based works but seem biased by the limitations of our currentexperimental setup. Conclusions: Our Monte-Carlo framework enables thenon-parametric estimation of fiber-specific diffusion-$T 1$ features, therebyshowing potential for characterizing developmental or pathological changes in$T 1$ within a given fiber bundle, and for investigating inter-bundle $T 1$differences.

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