Dependence of brain DTI maps of fractional anisotropy and mean diffusivity on the number of diffusion weighting directions

Abstract

The rotational variance dependence of diffusion tensor imaging (DTI) derived parameters on the number of diffusion weighting directions (N) has been investigated by several Monte Carlo simulation studies. However, the dependence of fractional anisotropy (FA) and mean diffusivity (MD) maps on N, in terms of accuracy and contrast between different anatomical structures, has not been assessed in detail. This experimental study further investigated in vivo the effect of the number of diffusion weighting directions on DTI maps of FA and MD. Human brain FA and MD maps of six healthy subjects were acquired at 1.5T with varying N (6, 11, 19, 27, 55). Then, FA and MD mean values in high (FAH, MDH) and low (FAL, MDL) anisotropy segmented brain regions were measured. Moreover, the contrast-to-signal variance ratio (CVRFA, CVRMD) between the main white matter and the surrounding regions was calculated. Analysis of variance showed that FAL, FAH and CVRFA significantly (p < 0.05) depend on N. In particular, FAL decreased (6%-11%) with N, whereas FAH (1.6%-2.5%) and CVRFA (4%-6.5%) increased with N. MDL, MDH and CVRMD did not significantly (p>0.05) depend on N. Unlike MD values, FA values significantly vary with N. It is noteworthy that the observed variation is opposite in low and high anisotropic regions. In clinical studies, the effect of N may represent a confounding variable for anisotropy measurements and the employment of DTI acquisition schemes with high N (> 20) allows an increased CVR and a better visualization of white matter structures in FA maps.

Figure 1

Masks of low (A) and high (B) anisotropy regions and FA map (C) of a healthy subject.

Figure 2

The logarithm of water phantom signal loss $(\text{ln}[\mathrm{S}(\mathrm{b})/{\mathrm{S}}_0])$ as a function of b‐value. The diffusion sensitizing gradient pulse was applied along the R/L (A), S/I (B) and A/P (C) directions.

Figure 3

Signal‐to‐noise ratio data of diffusion unweighted images ${(\mathrm{b}}_0)$ of a healthy subjects group: SNR values $(\text{mean}\pm \text{standard deviation})$ as a function of N.

Figure 4

MD (mm²/sec) maps of the same healthy subject obtained by using DTI acquisition schemes with $\mathrm{N}=6$ (A) and $\mathrm{N}=55$ (B) do not reveal appreciable differences in detecting brain structures.

Figure 5

FA maps of the same healthy subject obtained by using DTI acquisition schemes with $\mathrm{N}=6$ (A) and $\mathrm{N}=55$ (B). The increased contrast between gray and white matter in the image (B) with respect to image A allows a better delineation of the gray‐white matter junction that is recognizable along all the white matter borders. In particular, the improvement of image quality is detectable in the insular circumvolutions where the subcortical “U” fibers are clearly visualized only on image (B).

Figure 6

Contrast‐to‐signal variance ratio data of human brain FA maps of a healthy subjects group: ${\text{CVR}}_{\text{FA}}$ values $(\text{mean}\pm \text{standard error of the mean})$ as a function of N.

Figure 7

Human brain anisotropy data of a healthy subjects group: ${\text{FA}}_{\mathrm{L}}$ values $(\text{mean}\pm \text{standard error of the mean})$ as a function of N.

Figure 8

Human brain anisotropy data of a healthy subjects group: ${\text{FA}}_{\mathrm{H}}$ values $(\text{mean}\pm \text{standard error of the mean})$ as a function of N.

Figure 9

Human brain diffusion data of a healthy subjects group: ${\text{MD}}_{\mathrm{L}}$ values $(\text{mean}\pm \text{standard error of the mean})$ as a function of N.

Figure 10

Human brain diffusion data of a healthy subjects group: ${\text{MD}}_{\mathrm{H}}$ values $(\text{mean}\pm \text{standard error of the mean})$ as a function of N.

Figure 11

FA values of an isotropic water phantom obtained by applying DTI acquisition schemes with different N. The anisotropy values are normalized (100) to the FA value (0.054) measured by using the DTI scheme with $\mathrm{N}=6$.