Acquisition and voxelwise analysis of multi-subject diffusion data with Tract-Based Spatial Statistics

Abstract

There is much interest in using magnetic resonance diffusion imaging to provide information on anatomical connectivity in the brain by measuring the diffusion of water in white matter tracts. Among the measures, the most commonly derived from diffusion data is fractional anisotropy (FA), which quantifies local tract directionality and integrity. Many multi-subject imaging studies are using FA images to localize brain changes related to development, degeneration and disease. In a recent paper, we presented a new approach, tract-based spatial statistics (TBSS), which aims to solve crucial issues of cross-subject data alignment, allowing localized cross-subject statistical analysis. This works by transforming the data from the centers of the tracts that are consistent across a study's subjects into a common space. In this protocol, we describe the MRI data acquisition and analysis protocols required for TBSS studies of localized change in brain connectivity across multiple subjects.

Motion‐related artifacts in structural brain images revealed with independent estimates of in‐scanner head motion

“…Such problems with image registration may be exacerbated in cross‐cohort comparisons by warping T1w anatomical scans to a template image with varying degrees of success due to differences in motion‐related artifacts. The implication of this naturally extends to other measurements based on accurate estimates of brain anatomy including analysis of structural covariance networks [e.g., Zielinski et al, 2010; Montembeault et al, 2012], volume based morphometry [e.g., Schmitter et al, 2015], tract‐based spatial statistics [e.g., fractional anisotropy, diffusivity; Smith et al, 2006, 2007], and brain lesions imaged with FLAIR [e.g., white matter hyper‐intensities, infarctions; Hajnal et al, 1992; Brant‐Zawadzki et al, 1996], among many others.…”

White Matter Tract Integrity of Anterior Limb of Internal Capsule in Major Depression and Type 2 Diabetes

“…Although we did not perform cardiac gating due to time constraints, we carefully conducted quality control on the raw images and removed all subjects with artifacts due to head movement. Lastly, our ratio of non-diffusion weighted to diffusion weighted volumes may not be optimal based on the criteria proposed in (Smith et al, 2007), which recommends 1 non-diffusion weighted for every 8 diffusion weighted images.…”

Reconciling Variable Findings of White Matter Integrity in Major Depressive Disorder

“…This mean FA map was then thinned to create a mean FA skeleton representing centers of tracts common to all subjects. FA values less than 0.2 were judged as noise and eliminated to reduce potential confounds introduced by inter-subject variability and partial volume effects (Smith et al, 2006;Smith et al, 2007). The aligned and threshold FA map of each subject was projected onto the mean FA skeleton for the voxel-wise statistical analysis.…”

“…VBM of DTI data is a fully automated method that allows investigation of WM integrity in the whole brain, at each voxel (Ashburner and Friston, 2000;Good et al, 2001). TBSS is a newer analytic technique developed to reduce the alignment and smoothing problems that have been reported with VBM (Smith et al, 2006(Smith et al, , 2007. Both approaches have been used to assess for differences in WM integrity in a variety of psychiatric disorders including MDD (Bae et al, 2006;Li et al, 2009;Xie et al, 2006).…”