Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses

fMRI data is typically collected with gradient-echo echo-planar imaging (GE-EPI) sequences, which are particularly prone to the susceptibility artifact as a result of B0 field inhomogeneity. The component derived from in-plane spin dephasing induces pixel intensity variations and, more critically, geometric distortions. Despite the physical mechanisms underlying the susceptibility artifact being well established, a systematic investigation on the impact of the associated geometric distortions, and the direct comparison of different approaches to tackle them, on fMRI data analyses is missing. Here, we compared two different distortion correction approaches, by acquiring additional: 1) EPI data with reversed phase encoding direction (TOPUP; Andersson et al. 2003), and 2) standard (and undistorted) GE data at two different echo times (GRE). We first characterized the geometric distortions and the correction approaches based on the estimated field and voxel shift maps, and then conducted three types of analyses on the distorted and corrected fMRI data: 1) registration into structural data, 2) identification of resting-state networks, and 3) mapping of task-related brain regions of interest. GRE estimated the largest voxel shifts and more positively impacted the quality of the analyses, in terms of the (significantly lower) cost function of the registration, the (higher) spatial overlap between the resting-state networks and appropriate templates, and the (significantly higher) sensitivity of the task-related mapping based on the Z-score values of the associated activation maps, although also evident when considering TOPUP. fMRI data should thus be corrected for geometric distortions, possibly via the TOPUP approach because of its shorter acquisition times and higher computational efficiency, or ultimately using the GRE approach for the best performance, although requiring additional scanning time for acquiring field map images.