Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI.

Sijia Wang,Daniel J Peterson,Wenbin Li,Tara M Madhyastha,Thomas J Grabowski,J C Gatenby

doi:10.3389/fninf.2017.00017

Abstract

Correction of echo planar imaging (EPI)-induced distortions (called “unwarping”) improves anatomical fidelity for diffusion magnetic resonance imaging (MRI) and functional imaging investigations. Commonly used unwarping methods require the acquisition of supplementary images during the scanning session. Alternatively, distortions can be corrected by nonlinear registration to a non-EPI acquired structural image. In this study, we compared reliability using two methods of unwarping: (1) nonlinear registration to a structural image using symmetric normalization (SyN) implemented in Advanced Normalization Tools (ANTs); and (2) unwarping using an acquired field map. We performed this comparison in two different test-retest data sets acquired at differing sites (N = 39 and N = 32). In both data sets, nonlinear registration provided higher test-retest reliability of the output fractional anisotropy (FA) maps than field map-based unwarping, even when accounting for the effect of interpolation on the smoothness of the images. In general, field map-based unwarping was preferable if and only if the field maps were acquired optimally.

Highlights

Diffusion imaging is a widely-used technique to examine white matter microstructure in vivo
We examined a measure of reliability across the entire brain, including areas where we expect signal dropout, by calculating the absolute value of the difference in fractional anisotropy (FA) maps for each subject at each time point after registering to the structural image obtained at the first-time point using rigid-body registration
We found that distortion correction of diffusion data using the symmetric normalization (SyN) algorithm implemented in Advanced Normalization Tools (ANTs) resulted in higher reliability, both as measured after processing using Tract-Based Spatial Statistics (TBSS) and by examining mean difference scores (Figure 5), than using a field map for unwarping

Summary

Introduction

Diffusion imaging is a widely-used technique to examine white matter microstructure in vivo. EPI causes geometric distortions (Jones and Cercignani, 2010) that stem from the inhomogeneity of the underlying B0 field, which is in turn due to the varying magnetic susceptibilities of air, bone and tissue. B0 Field mapping techniques (Jezzard and Balaban, 1995; Wan et al, 1997) can be used to reduce EPI distortion by ‘‘unwarping’’ the images. Unwarping using field mapping requires that we obtain phase images at two different echo times (Reber et al, 1998). Using these two-phase images, one can calculate the degree of EPI distortion present along the phaseencode direction of the EPI images, and apply an equal and opposite pixel-shift, thereby unwarping the distortions in the original images

Methods

Results

Conclusion