Improved Framework for Tractography Reconstruction of the Optic Radiation

Abstract

The optic radiation (OR) is one of the major components of the visual system and a key structure at risk in white matter diseases such as multiple sclerosis (MS). However, it is challenging to perform track reconstruction of the OR using diffusion MRI due to a sharp change of direction in the Meyer’s loop and the presence of kissing and crossing fibers along the pathway. As such, we aimed to provide a highly precise and reproducible framework for tracking the OR from thalamic and visual cortex masks. The framework combined the generation of probabilistic streamlines by high order fiber orientation distributions estimated with constrained spherical deconvolution and an automatic post-processing based on anatomical exclusion criteria (AEC) to compensate for the presence of anatomically implausible streamlines. Specifically, those ending in the contralateral hemisphere, cerebrospinal fluid or grey matter outside the visual cortex were automatically excluded. We applied the framework to two distinct high angular resolution diffusion-weighted imaging (HARDI) acquisition protocols on one cohort, comprised of ten healthy volunteers and five MS patients. The OR was successfully delineated in both HARDI acquisitions in the healthy volunteers and MS patients. Quantitative evaluation of the OR position was done by comparing the results with histological reference data. Compared with histological mask, the OR reconstruction into a template (OR-TCT) was highly precise (percentage of voxels within the OR-TCT correctly defined as OR), ranging from 0.71 to 0.83. The sensitivity (percentage of voxels in histological reference mask correctly defined as OR in OR-TCT) ranged from 0.65 to 0.81 and the accuracy (measured by F1 score) was 0.73 to 0.77 in healthy volunteers. When AEC was not applied the precision and accuracy decreased. The absolute agreement between both HARDI datasets measured by the intraclass correlation coefficient was 0.73. This improved framework allowed us to reconstruct the OR with high reliability and accuracy independently of the acquisition parameters. Moreover, the reconstruction was possible even in the presence of tissue damage due to MS. This framework could also be applied to other tracts with complex configuration.

Structural networks involved in attention and executive functions in multiple sclerosis

“…optic radiations) (Martínez-Heras et al, 2015). Here, we further support the use of this framework in structural connectivity analyses.…”

“…Subjects with MS can present topology alterations of networks related to the spatial distribution of WM lesions that could affect tractography results. The use of high order probabilistic fiber tracking and AEC postprocessing partially resolves this handicap by improving tract reconstruction in the presence of lesions (Bucci et al, 2013, Mormina et al, 2015) and decreasing low confidence and spurious streamlines (Martínez-Heras et al, 2015). Further research on tractography methodology to solve the effect of lesions in tract reconstruction is warranted.…”

“…In MS participants, normal appearing WM and lesions mask were considered as WM tissue type in the 5TT format. AEC was applied to every track file from each pair of nodes (3486 specific connections of interest linking 84 GM regions) to reduce the presence of false positive streamlines (Martínez-Heras et al, 2015). This included the application of a 1% threshold based on track-weights for each connection and the exclusion of any streamline outside the direct link between each pair of nodes.…”

“…Albeit, tractography generates biologically unrealistic streamlines that can be reduced by the application of an anatomical exclusion criteria (AEC) postprocessing. AEC removes streamlines of low confidence and excludes pathways reaching GM areas outside the seeds masks, reducing the amount of anatomically implausible streamlines and increasing tractography reliability in healthy volunteers (HV) and in patients with MS (Martínez-Heras et al, 2015). …”

“…In this way, the characterization of the brain structural network has the potential to improve our understanding of the pathophysiology of MS and its clinical manifestations. In this study, we aimed to investigate changes in structural connectivity in patients with MS and their association with attention and executive functioning applying an improved framework for tractography reconstruction by combining iFOD2 and automatic postprocessing based on AEC (Martínez-Heras et al, 2015). We hypothesized that the disruption of the structural network connectivity contributes to cognitive difficulties characteristics of this disease, especially in attention and executive functions.…”