Abstract
Assessing the effects of white matter (WM) lesions on structural connectivity as measured by diffusion MRI (dMRI) is invaluable for understanding structure-function relationships. These WM lesions have many etiologies that ultimately lead to attenuation of the anisotropic signature in dMRI signals. Attenuation can produce inaccurate reconstructions of the underlying model of the fiber population. In this paper, we combine methods from image inpainting and estimation theory to develop a novel approach for restoring the fiber model in small to moderate sized WM lesions. Our approach begins by taking healthy reconstructed WM fiber models at the boundary of the lesion and filling in lesioned voxels with their optimal affine estimate moving iteratively in a fast-marching method style until the fiber models in the lesion are restored. We demonstrate with in-vivo simulations on diffusion tensors (DTs) and fiber orientation distributions (FODs) that our approach offers superior performance over multiple restoration approaches. We restore lesioned fiber models in three stroke patients suffering hemiparesis from damaged corticospinal tracts (CST). We show that our method restores diffusivities, anisotropy and orientation of lesioned DTs as well as the amplitudes and orientations of fiber populations in lesioned FODs enhancing tractography and enabling more accurate characterization of lesion connectivity and changes in tissue microstructure in patient populations.
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Greene, C., Revill, K., Buetefisch, C., Rose, K., Grafton, S. (2020). Optimal Fiber Diffusion Model Restoration. In: Bonet-Carne, E., Hutter, J., Palombo, M., Pizzolato, M., Sepehrband, F., Zhang, F. (eds) Computational Diffusion MRI. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-030-52893-5_4
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DOI: https://doi.org/10.1007/978-3-030-52893-5_4
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