2.3. Data analysis

All MR images were analyzed using Image J software (imagej.nih.gov/ij/). Supratentorial lesions were analyzed side-by-side on axial GRE-T2*, 3D-SWI and QSM images. For each lesion, the following morphological imaging characteristics were recorded: 1) lesion count, 2) largest cross-sectional diameter, 3) location, 4) the presence of one or multiple central intralesional venules, and 5) signal intensity pattern within the lesions. Based upon the largest cross-sectional diameter, lesions were classified as small (<5 mm) or large (>5 mm). Lesions were classified as “iron-laden” if they demonstrated hypointense signal on T2*-weighted GRE images and/or SWI as well as hyperintense signals on QSM. Lesions were considered “non-iron-laden” if they were hyperintense on GRE-T2*/SWI and isointense or hyperintense on QSM. All MR images (GRE-T2, SWI and QSM) were analyzed and interpreted at both time points by two investigators (IK and SC) jointly. These investigators worked together in achieving the final consensus. In event of disagreement in evaluating data, a senior author (YG, with over 22 years of experience in the field of advanced MR imaging in studying MS/NMOSD diseases) was consulted.

Additionally, the brain extraction tool (BET) (Smith SM, 2002) and the automated segmentation tool from the FMRIB Software Library (Zhang et al., 2001) was used to segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) regions and to measure corresponding tissue volumes using T1-weighted 3D-MPRAGE images. To assess brain atrophy from patients at both time points, the fractional brain parenchymal volume (fBPV) was computed as the ratio of brain parenchymal volume (GM + WM) to the total intracranial volume (GM + WM + CSF) as described previously (Marshall et al., 2016).