All increasingly pliable deformations, as previously reported (58). Each

All of the GRASE (T2w images acquired at different echo times) images were
coregistered to the T1w TFE images followed by the reslicing the images to 1 mm3
resolution using “reslice_img.m”. The skull stripping of all the
images was then performed using a two-step procedure, whereby subject-specific
brain masks were generated in SPM12, which were then manually refined using the
ROIEditor toolbox in MRIStudio. The coregistered and skull-stripped mean images for each subject were then normalized to the “JHU_MNI_SS_T1_ss” template (55) in Montreal
Neurological Institute (MNI) coordinate space (56). This step was
implemented using the DiffeoMap toolbox in MRIStudio to carry out a
12-parameter affine (linear) transformation with Automated Image Registration
(AIR), followed by high-dimensional, non-linear warping with the large
deformation diffeomorphic metric mapping (LDDMM) algorithm (57). The LDDMM
analysis was performed with cascading elasticity
(i.e., alpha values of 0.01, 0.005, and 0.002) to allow increasingly pliable
deformations, as previously reported (58). Each subjects’
images were warped to normalized International Consortium for Brain
Mapping (ICBM) space (56) by applying the
overall Kimap (linear affine + non-linear
LDDMM) transformation, as previously described (58). The
MWF maps were then computed voxel-by-voxel basis using a regularized
non-negative least squares algorithm to extract individual T2 components from
multi-exponential T2 decay curves (21). In addition,
extended phase graph algorithm was used to compensate stimulated echoes due to
B1 heterogeneities  (21,59).

MWF was calculated as the ratio of T2 signal from 10-40 ms to the
total signal (29).

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