High B-value diffusion tensor imaging for early detection of hippocampal microstructural alteration in a mouse model of multiple sclerosis

Abstract

Several studies have highlighted the value of diffusion tensor imaging (DTI) with strong diffusion weighting to reveal white matter microstructural lesions, but data in gray matter (GM) remains scarce. Herein, the effects of b-values combined with different numbers of diffusion-encoding directions (NDIRs) on DTI metrics to capture the normal hippocampal microstructure and its early alterations were investigated in a mouse model of multiple sclerosis (experimental autoimmune encephalomyelitis [EAE]). Two initial DTI datasets (B2700-43Dir acquired with b = 2700 s.mm^-2 and NDIR = 43; B1000-22Dir acquired with b = 1000 s.mm^-2 and NDIR = 22) were collected from 18 normal and 18 EAE mice at 4.7 T. Three additional datasets (B2700-22Dir, B2700-12Dir and B1000-12Dir) were extracted from the initial datasets. In healthy mice, we found a significant influence of b-values and NDIR on all DTI metrics. Confronting unsupervised hippocampal layers classification to the true anatomical classification highlighted the remarkable discrimination of the molecular layer with B2700-43Dir compared with the other datasets. Only DTI from the B2700 datasets captured the dendritic loss occurring in the molecular layer of EAE mice. Our findings stress the needs for both high b-values and sufficient NDIR to achieve a GM DTI with more biologically meaningful correlations, though DTI-metrics should be interpreted with caution in these settings.

Figure 1

Example of brain fractional anisotropy (FA) parametric maps (A) with a magnification (B) on the hippocampus with and without the segmentations of the three volumes of interest corresponding to the three main hippocampal layers (i.e., Stratum Radiatum, Stratum Lacunosum Molecular and Molecular Layer).

Figure 2

Coronal views of the four brain parametric maps and sum of square residual (SSR) after applying the DTI model, reconstructed using each of the five-diffusion tensor imaging (DTI) datasets in a same control mouse at a spatial-resolution of 82 × 81 × 200 µm². All diffusivity maps (axial, mean and radial diffusivities) are presented in µm²/ms. AD axial diffusivity, B b-value, Dir number of diffusion encoding directions, FA fractional anisotropy, MD mean diffusivity, RD Radial Diffusivity, SSE sum of square error.

Figure 3

Comparisons of diffusion tensor imaging (DTI) metrics in the three main hippocampal layers of healthy mice depending on the DTI dataset: (A) axial diffusivity (AD), (B) fractional anisotropy (FA), (C) mean diffusivity (MD) and (D) radial diffusivity (RD). AD, MD and RD are expressed in μm².ms⁻¹. B b-value, Dir number of diffusion gradient direction, ML molecular layer, SLM stratum lacunosum moleculare, SR stratum radiatum. *P < 0.05; **P < 0.005; ***P < 0.001.

Figure 4

Comparative views of the unsupervised clustering results and the real anatomical classification for each diffusion tensor imaging (DTI) dataset: (A) B1000-12Dir, (B) B1000-22Dir, (C) B2700-12Dir, (D) B2700-22Dir, and (E) B2700-43Dir. Each point corresponds to one segmentation, characterized by its DTI metrics and is plotted with the same three axes: x: fractional anisotropy (FA), y: mean diffusivity (MD), z: radial diffusivity (RD). AD, MD and RD are expressed in μm².ms⁻¹. ML molecular layer, SLM stratum lacunosum moleculare, SR stratum radiatum.

Figure 5

Comparisons between the diffusion tensor imaging (DTI) metrics from the five datasets in the molecular layer of control healthy mice (CTL) versus the mouse model of multiple sclerosis (experimental autoimmune encephalomyelitis [EAE]): (A) axial diffusivity, (B) fractional anisotropy, (C) mean diffusivity, (D) radial diffusivity. Diffusivities are expressed in μm².ms⁻¹. *P < 0.05. B b-value, Dir number of diffusion gradient directions.