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 false(FAH,.2emMDHfalse) and low false(FAL,.2emMDLfalse) anisotropy segmented brain regions were measured. Moreover, the contrast‐to‐signal variance ratio false(CVRFA,.2emCVRMDfalse) between the main white matter and the surrounding regions was calculated. Analysis of variance showed that FAL,.2emFAH and CVRFA significantly false(p<0.05false) depend on N. In particular, FAL decreased (6%–11%) with N, whereas FAH (1.6%–2.5%) and CVRFA (4%–6.5%) increased with normalN..2emMDL,.2emMDH and CVRMD did not significantly false(p>0.05false) 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 normalN.2emfalse(>.2em20false) allows an increased CVR and a better visualization of white matter structures in FA maps.PACS number: 87.61.Tg, 82.56.Lz

Changes in mild cognitive impairment and its subtypes as seen on diffusion tensor imaging

“…FA has been shown to vary significantly depending on the number of diffusion-weighted directions used; in contrast, MD has been found to be unaffected by the number of diffusion directions used (Giannelli et al, 2009). This may explain why no significant FA differences were observed in this study.…”

Investigating brain connectivity heritability in a twin study using diffusion imaging data

“…The reproducibility of diffusion MR image using DTI-based metrics such as FA and diffusivity was studied mainly through ROI-based analyses (Besseling et al, 2012; Bisdas et al, 2008; Bonekamp et al, 2007; Ciccarelli et al, 2003; Farrell et al, 2007; Giannelli et al, 2010; Hakulinen et al, 2012; Heiervang et al, 2006; Huang et al, 2012; Jansen et al, 2007; Jones, 2004; Landman et al, 2007; Pfefferbaum et al, 2003; Vollmar et al, 2010, for review see Vollmar et al, 2010). Voxel-wise analysis of FA was conducted by Farrell et al (2007), which found that the voxel-wise measure of FA in WM was more reproducible than in GM.…”

Harmonization of multi-site diffusion tensor imaging data

“…As with other imaging modalities, DTI images are subject to technical variability across scans, including heterogeneity in the imaging protocol, variations in the scanning parameters and differences in the scanner manufacturers [Zhu et al, 2009, 2011]. Among others, the reliability of FA and MD maps have been shown to be affected by angular and spatial resolution [Zhan et al, 2010, Alexander et al, 2001, Kim et al, 2006], the number of diffusion weighting directions [Giannelli et al, 2009], the number of gradient sampling orientations [Jones, 2004], the number of b-values [Correia et al, 2009], and the b-values themselves.…”