Similar cortical lesion distribution and cortical atrophy location in patients with relapsing-remitting multiple sclerosis.

Introduction Pathological mechanisms leading cortical tissue loss in Multiple Sclerosis (MS) are largely unknown. Nevertheless cortical lesions (CLs) are detectable in MS by using novel sequences as the double inversion recovery (DIR) and their anatomical location and spatial distribution can be assessed by generating a CL probability map (CLPM). Voxel based Morphometry (VBM) has been successfully used in MS studies to assess anatomical and spatial localization of GM volume decreases. Against this background, we aimed here to ascertain the spatial relationship between CLs distribution and GM atrophy. Methods Study Population and MRI examination We consecutively selected 103 patients with a diagnosis of Relapsing-Remitting MS and 30 healthy controls age and sex matched. All patients underwent the same brain MRI protocol performed to the MS Center in Padova and were assessed clinically with the Expanded Disability Status Scale (EDSS) on the day of scanning. All images were on a 1.5-T scanner (Achieva, Philips Medical Systems, Best, the Netherlands) with a maximum gradient strength of 33 mT/m, using a 16-channel head coil. The following images were acquired from each subject: 1 DIR, 3 consecutive 3-dimensional fast-field echo (FFE) T1-weighted (T1W) sequence and 1 fast fluid-attenuated inversion recovery (FLAIR). MR data analysis. Creation of Cortical and WM Lesion masks. For each patient, CL were identified on the DIR image, manually outlined and segmented into a binarized CL mask using a thresholding technique based on Fuzzy C-mean algorithm. Creation of FLAIR WM binarized lesion mask was obtained in each patient by a single observer, unaware of subjects' identity, employing a segmentation technique based on user-supervised local thresholding Creation of “unbiased” T1-W images To improve the signal-to-noise ratio, the 3 distinct T1-W images were co-aligned and averaged by using the mri_motion_correct. fsl included into the FreeSurfer softwares library. To make the segmentation and non-linear registration steps better performing, the WM lesion mask of each subject was linearly registered to the averaged T1-W by using FLIRT, the linear registration tool of the FMRIB Software Library (FSL; www.fmrib.ox.ac.uk) and there each single lesion was refilled with intensities similar to the intensities of voxels surrounding it, generating an “unbiased” T1-W image. Volume Measurements For each subject, Normalized Cortical Volume (NCV) was assessed from the “unbiased” T1-W image using the SIENAx method. A VBM-FSL procedure was carried out with FSL tools. 30 “unbiased” T1-W images for each subjects group were affinely registered to the MNI152 standard brain and averaged to create a symmetric study-specific template. All the “unbiased” T1-W images were segmented using FAST4 and the resulting grey-matter partial volume images were then non-linearly registered to the study template previously created. Finally the registered partial volume GM images were modulated by dividing by the Jacobian of the warp field and smoothed with an isotropic Gaussian kernel with a sigma of 2.5 mm. Localization was assessed by using the MNI and the Harvard-Oxford atlases provided by FSL. Creation of cortical lesion probability maps. cLPM was created following steps previously described 1 : 1) CL masks were firstly linearly aligned to the respective “unbiased” T1W image and after non-linearly registered to the same VBM symmetric study-specific template created using the transformation parameters derived by registering each “unbiased” T1W image on the template. 2) Finally a cLPM was created by averaging all the standard-space CL masks. In this map, voxel intensity represents the probability of that voxel being lesion. Localization was assessed by using the MNI and the Harvard-Oxford atlases provided by FSL.Statistical analysis Differences between HS, patient with presence of CL (CL-p ) and with absence of CL (CL-a patients) were assessed using analysis of variance (ANOVA) followed by pairwise post hoc comparison using Tukey's HSD procedure to account for multiple comparisons. Data were considered significant at the 0.05 level. Voxelwise analysis To test for differences in GM local density, Randomise program within FSL was used