Comparison of probabilistic tractography and tract-based spatial statistics for assessing optic radiation damage in patients with autoimmune inflammatory disorders of the central nervous system
- PMID: 29984162
- PMCID: PMC6029567
- DOI: 10.1016/j.nicl.2018.05.004
Comparison of probabilistic tractography and tract-based spatial statistics for assessing optic radiation damage in patients with autoimmune inflammatory disorders of the central nervous system
Abstract
Background: Diffusion Tensor Imaging (DTI) can evaluate microstructural tissue damage in the optic radiation (OR) of patients with clinically isolated syndrome (CIS), early relapsing-remitting multiple sclerosis and neuromyelitis optica spectrum disorders (NMOSD). Different post-processing techniques, e.g. tract-based spatial statistics (TBSS) and probabilistic tractography, exist to quantify this damage.
Objective: To evaluate the capacity of TBSS-based atlas region-of-interest (ROI) combination with 1) posterior thalamic radiation ROIs from the Johns Hopkins University atlas (JHU-TBSS), 2) Juelich Probabilistic ROIs (JUEL-TBSS) and tractography methods using 3) ConTrack (CON-PROB) and 4) constrained spherical deconvolution tractography (CSD-PROB) to detect OR damage in patients with a) NMOSD with prior ON (NMOSD-ON), b) CIS and early RRMS patients with ON (CIS/RRMS-ON) and c) CIS and early RRMS patients without prior ON (CIS/RRMS-NON) against healthy controls (HCs).
Methods: Twenty-three NMOSD-ON, 18 CIS/RRMS-ON, 21 CIS/RRMS-NON, and 26 HCs underwent 3 T MRI. DTI data analysis was carried out using JUEL-TBSS, JHU-TBSS, CON-PROB and CSD-PROB. Optical coherence tomography (OCT) and visual acuity testing was performed in the majority of patients and HCs.
Results: Absolute OR fractional anisotropy (FA) values differed between all methods but showed good correlation and agreement in Bland-Altman analysis. OR FA values between NMOSD and HC differed throughout the methodologies (p-values ranging from p < 0.0001 to 0.0043). ROC-analysis and effect size estimation revealed higher AUCs and R2 for CSD-PROB (AUC = 0.812; R2 = 0.282) and JHU-TBSS (AUC = 0.756; R2 = 0.262), compared to CON-PROB (AUC = 0.742; R2 = 0.179) and JUEL-TBSS (AUC = 0.719; R2 = 0.161). Differences between CIS/RRMS-NON and HC were only observable in CSD-PROB (AUC = 0.796; R2 = 0.094). No significant differences between CIS/RRMS-ON and HC were detected by any of the methods.
Conclusions: All DTI post-processing techniques facilitated the detection of OR damage in patient groups with severe microstructural OR degradation. The comparison of distinct disease groups by use of different methods may lead to different - either false-positive or false-negative - results. Since different DTI post-processing approaches seem to provide complementary information on OR damage, application of distinct methods may depend on the relevant research question.
Keywords: AD, axial diffusivity; AUC, area under the curve; CIS, clinically isolated syndrome; CON, Contrack; CSD, constrained spherical deconvolution; DTI; DTI, diffusion tensor imaging; DW-MRI, diffusion weighted magnetic resonance imaging; DWI, diffusion weighted imaging; FA, fractional anisotropy; FOD, fiber orientation distribution; HC, Healthy Control; JHU, Johns Hopkins University DTI white matter atlas; JUEL, Juelich histological atlas; LGN, lateral geniculate nucleus; MD, mean diffusivity; MS, multiple sclerosis; Multiple sclerosis; NMOSD, neuromyelitis optica spectrum disorder; Neuromyelitis optica; OCT, optical coherence tomography; ON, optic neuritis; OR, optic radiation; Optic radiation; PROB, probabilistic tractography; Probabilistic tractography; RD, radial diffusivity; RNFL, retinal nerve fiber layer thickness; ROC, receiver operating characteristic; ROI, region of interest; RRMS, relapsing-remitting multiple sclerosis; SD, standard deviation; SEM, standard error of the mean; TBSS; TBSS, tract-based spatial statistics.
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