Abstract
Several neurological conditions are associated with microstructural changes in the hippocampus that can be observed using DWI. Imaging studies often use protocols with whole-brain coverage, imposing limits on image resolution and worsening partial-volume effects. Also, conventional single-diffusion-encoding methods confound microscopic diffusion anisotropy with size variance of microscopic diffusion environments. This study addresses these issues by implementing a multidimensional diffusion-encoding protocol for microstructural imaging of the hippocampus at high resolution. The hippocampus of 8 healthy volunteers was imaged at 1.5-mm isotropic resolution with a multidimensional diffusion-encoding sequence developed in house. Microscopic fractional anisotropy (µFA) and normalized size variance (CMD ) were estimated using q-space trajectory imaging, and their values were compared with DTI metrics. The overall scan time was 1 hour. The reproducibility of the protocol was confirmed with scan-rescan experiments, and a shorter protocol (14 minutes) was defined for situations with time constraints. Mean µFA (0.47) was greater than mean FA (0.20), indicating orientation dispersion in hippocampal tissue microstructure. Mean CMD was 0.17. The reproducibility of q-space trajectory imaging metrics was comparable to DTI, and microstructural metrics in the healthy hippocampus are reported. This work shows the feasibility of high-resolution microscopic anisotropy imaging in the human hippocampus at 3 T and provides reference values for microstructural metrics in a healthy hippocampus.
Highlights
Because the diffusion of water in the brain is constrained by the presence of microscopic obstacles such as cell organelles, myelin, and macromolecules, DWI enables the study of neural tissue microstructure in vivo by probing the displacements of water molecules.[1,2] Diffusion tensor imaging is a widely used diffusion MRI approach in which the mean apparent diffusion propagator in an imaging voxel is characterized by a diffusion tensor, from which quantitative metrics such as fractional anisotropy (FA) and mean diffusivity (MD) can be derived.[3,4] Despite its utility in research and clinical settings, the diffusion tensor cannot capture non-Gaussian diffusion and confounds orientation dispersion of anisotropic neurites with isotropic diffusion
In contrast to single-diffusion encoding, multidimensional diffusion encoding (MDE) renders the diffusion MRI (dMRI) signal sensitive to the displacements of water molecules that occur in a plane or in a volume.12–14 Multidimensional diffusion encoding enables the disentanglement of microscopic diffusion anisotropy from the size variance of microenvironments and can be used to measure microscopic fractional anisotropy.10,15–18 The value of μFA is a normalized metric of the average eigenvalue variance of the microscopic diffusion tensors that is equal to conventional FA in voxels where all the microscopic compartments are aligned.[11,19]
Averaged across the hippocampus volumes of all volunteers, MD was 1.06 ± 0.37 μm2/ms, FA was 0.20 ± 0.09, μFA was 0.47 ± 0.13, and CMD was 0.17 ± 0.05, where the reported numbers correspond to the mean and SD, respectively
Summary
Because the diffusion of water in the brain is constrained by the presence of microscopic obstacles such as cell organelles, myelin, and macromolecules, DWI enables the study of neural tissue microstructure in vivo by probing the displacements of water molecules.[1,2] Diffusion tensor imaging is a widely used diffusion MRI (dMRI) approach in which the mean apparent diffusion propagator in an imaging voxel is characterized by a diffusion tensor, from which quantitative metrics such as fractional anisotropy (FA) and mean diffusivity (MD) can be derived.[3,4] Despite its utility in research and clinical settings, the diffusion tensor cannot capture non-Gaussian diffusion and confounds orientation dispersion of anisotropic neurites with isotropic diffusion. Diffusion tensor imaging belongs to a class of single- diffusion-encoding methods, in which diffusion is measured along a single dimension corresponding to the direction of the applied diffusion-weighting gradient.[8,9] Single-diffusion-encoding acquisitions confound the orientation dispersion of anisotropic neurites with size variance of diffusion microenvironments, resulting in a lack of specificity.[10,11] In contrast to single-diffusion encoding, multidimensional diffusion encoding (MDE) renders the dMRI signal sensitive to the displacements of water molecules that occur in a plane or in a volume.12–14 Multidimensional diffusion encoding enables the disentanglement of microscopic diffusion anisotropy from the size variance of microenvironments and can be used to measure microscopic fractional anisotropy (μFA).10,15–18 The value of μFA is a normalized metric of the average eigenvalue variance of the microscopic diffusion tensors that is equal to conventional FA in voxels where all the microscopic compartments are aligned.[11,19] The μFA does not depend on the orientation dispersion of axons, providing more information on tissue microstructure
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