Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

Connectivity analysis on diffusion MRI data of the whole- brain suffers from distortions caused by the standard echo- planar imaging acquisition strategies. These images show characteristic geometrical deformations and signal destruction that are an important drawback limiting the success of tractography algorithms. Several retrospective correction techniques are readily available. In this work, we use a digital phantom designed for the evaluation of connectivity pipelines. We subject the phantom to a âeurooetheoretically correctâeuro and plausible deformation that resembles the artifact under investigation. We correct data back, with three standard methodologies (namely fieldmap-based, reversed encoding-based, and registration- based). Finally, we rank the methods based on their geometrical accuracy, the dropout compensation, and their impact on the resulting connectivity matrices.

Connectivity and tissue microstructural alterations in right and left temporal lobe epilepsy revealed by diffusion spectrum imaging.

Focal epilepsy is increasingly recognized as the result of an altered brain network, both on the structural and functional levels and the characterization of these widespread brain alterations is crucial for our understanding of the clinical manifestation of seizure and cognitive deficits as well as for the management of candidates to epilepsy surgery. Tractography based on Diffusion Tensor Imaging allows non-invasive mapping of white matter tracts in vivo. Recently, diffusion spectrum imaging (DSI), based on an increased number of diffusion directions and intensities, has improved the sensitivity of tractography, notably with respect to the problem of fiber crossing and recent developments allow acquisition times compatible with clinical application. We used DSI and parcellation of the gray matter in regions of interest to build whole-brain connectivity matrices describing the mutual connections between cortical and subcortical regions in patients with focal epilepsy and healthy controls. In addition, the high angular and radial resolution of DSI allowed us to evaluate also some of the biophysical compartment models, to better understand the cause of the changes in diffusion anisotropy. Global connectivity, hub architecture and regional connectivity patterns were altered in TLE patients and showed different characteristics in RTLE vs LTLE with stronger abnormalities in RTLE. The microstructural analysis suggested that disturbed axonal density contributed more than fiber orientation to the connectivity changes affecting the temporal lobes whereas fiber orientation changes were more involved in extratemporal lobe changes. Our study provides further structural evidence that RTLE and LTLE are not symmetrical entities and DSI-based imaging could help investigate the microstructural correlate of these imaging abnormalities.