White Matter Abnormalities in Multiple Sclerosis Evaluated by Quantitative Synthetic MRI, Diffusion Tensor Imaging, and Neurite Orientation Dispersion and Density Imaging

Abstract

BACKGROUND AND PURPOSE: A number of MR-derived quantitative metrics have been suggested to assess the pathophysiology of MS, but the reports about combined analyses of these metrics are scarce. Our aim was to assess the spatial distribution of parameters for white matter myelin and axon integrity in patients with relapsing-remitting MS by multiparametric MR imaging. MATERIALS AND METHODS: Twenty-four patients with relapsing-remitting MS and 24 age-and sex-matched controls were prospectively scanned by quantitative synthetic and 2-shell diffusion MR imaging. Synthetic MR imaging data were used to retrieve relaxometry parameters (R1 and R2 relaxation rates and proton density) and myelin volume fraction. Diffusion tensor metrics (fractional anisotropy and mean, axial, and radial diffusivity) and neurite orientation and dispersion index metrics (intracellular volume fraction, isotropic volume fraction, and orientation dispersion index) were retrieved from diffusion MR imaging data. These data were analyzed using Tract-Based Spatial Statistics. RESULTS: Patients with MS showed significantly lower fractional anisotropy and myelin volume fraction and higher isotropic volume fraction in widespread white matter areas. Areas with different isotropic volume fractions were included within areas with lower fractional anisotropy. Myelin volume fraction showed no significant difference in some areas with significantly decreased fractional anisotropy in MS, including in the genu of the corpus callosum and bilateral anterior corona radiata, whereas myelin volume fraction was significantly decreased in some areas where fractional anisotropy showed no significant difference, including the bilateral posterior limb of the internal capsule, external capsule, sagittal striatum, fornix, and uncinate fasciculus. CONCLUSIONS: We found differences in spatial distribution of abnormality in fractional anisotropy, isotropic volume fraction, and myelin volume fraction distribution in MS, which might be useful for characterizing white matter in patients with MS. ABBREVIATIONS: AVF ¼ axon volume fraction; EDSS ¼ Expanded Disability Status Scale; FA ¼ fractional anisotropy; ICVF ¼ intracellular volume fraction; ISO ¼ isotropic volume fraction; MNI ¼ Montreal Neurological Institute; MVF ¼ myelin volume fraction; NAWM ¼ normal-appearing white matter; NODDI ¼ neurite orientation dispersion and density imaging; ODI ¼ orientation dispersion index; QRAPMASTER ¼ quantification of relaxation times and proton density by multiecho acquisition of a saturation-recovery using turbo spin-echo readout

Estimating axial diffusivity in the NODDI model

“…Neurite Orientation Dispersion and Density Imaging (NODDI) [5] is one of the most commonly used microstructural models in diffusion MR which, due to its clinically feasible scan times, has featured in numerous studies of patient populations [78, 79, 80, 81, 82]. However, to estimate the neurite density or signal fraction, NODDI must assume a fixed, predefined value of the intra-axonal axial diffusivity, which is typically set to 1.7 μm 2 /ms.…”

Variability and Standardization of Quantitative Imaging

“…This is important when the ROI size can be variable due to treatment response or disease progression, when monitoring the effect of treatment on lesions such as tumors, 30 or when the ROI size is small such as in the case of measuring multiple sclerosis focal plaques. 31 – 33 The appropriate selection of an ROI size and estimation of size effect would help adjust the decision threshold by a QIB in monitoring a treatment effect. 29 The ROI placement procedure can also be variable among radiologists.…”

Myelin Measurement Using Quantitative Magnetic Resonance Imaging: A Correlation Study Comparing Various Imaging Techniques in Patients with Multiple Sclerosis

“…This was done by running Bloch equations and optimizing model parameters in a spatially normalized and averaged brain from a group of healthy controls. Damage to myelin, even in the NAWM of patients with MS [18], is supposed to cause deviation from the R1, R2, and PD in the healthy state, leading to a decrease in the calculated SyMRI MVF . Using this model, MVF maps were created from R1, R2, and PD maps via SyMRI software (version 8.04; SyntheticMR, Linköping, Sweden).…”