4.7 Article

A novel framework for in-vivo diffusion tensor distribution MRI of the human brain

Journal

NEUROIMAGE
Volume 271, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2023.120003

Keywords

Diffusion; MRI; Concomitant gradients; Pulsed field gradients; Normal distribution; Tensor variate; mPFG; B-tensor; DTI; DTD; Heterogeneity; Anisotropy; Monte Carlo; DWI; microFA; microODF; MD distribution; B-matrix; Tractography

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Neural tissue microstructure plays a crucial role in various processes, and diffusion tensor distribution (DTD) MRI provides a new framework for investigating subvoxel heterogeneity. By employing pulsed field gradients (iPFG), the researchers developed a method to acquire multiple diffusion encoding (MDE) images and estimate DTD in the human brain. Through this technique, they were able to reveal microscopic anisotropy and capture complex white matter fiber organization, which could aid in improving neurological disease diagnosis.
Neural tissue microstructure plays an important role in developmental, physiological and pathophysiological processes. Diffusion tensor distribution (DTD) MRI helps probe subvoxel heterogeneity by describing water diffusion within a voxel using an ensemble of non-exchanging compartments characterized by a probability density function of diffusion tensors. In this study, we provide a new framework for acquiring multiple diffusion encoding (MDE) images and estimating DTD from them in the human brain in vivo. We interfused pulsed field gradients (iPFG) in a single spin echo to generate arbitrary b-tensors of rank one, two, or three without introducing concomitant gradient artifacts. Employing well-defined diffusion encoding parameters we show that iPFG retains salient features of a traditional multiple-PFG (mPFG/MDE) sequence while reducing the echo time and coherence pathway artifacts thereby extending its applications beyond DTD MRI. Our DTD is a maximum entropy tensor-variate normal distribution whose tensor random variables are constrained to be positive definite to ensure their physicality. In each voxel, the second-order mean and fourth-order covariance tensors of the DTD are estimated using a Monte Carlo method that synthesizes micro-diffusion tensors with corresponding size, shape, and orientation distributions to best fit the measured MDE images. From these tensors we obtain the spectrum of diffusion tensor ellipsoid sizes and shapes, and the microscopic orientation distribution function (mu ODF) and microscopic fractional anisotropy (mu FA) that disentangle the underlying heterogeneity within a voxel. Using the DTD-derived mu ODF, we introduce a new method to perform fiber tractography capable of resolving complex fiber configurations. The results revealed microscopic anisotropy in various gray and white matter regions and skewed MD distributions in cerebellar gray matter not observed previously. DTD MRI tractography captured complex white matter fiber organization consistent with known anatomy. DTD MRI also resolved some degeneracies associated with diffusion tensor imaging (DTI) and elucidated the source of diffusion heterogeneity which may help improve the diagnosis of various neurological diseases and disorders.

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