Accurate GM atrophy quantification in MS using lesion-filling with co-registered 2D lesion masks☆

BACKGROUND In multiple sclerosis (MS), brain atrophy quantification is affected by white matter lesions. LEAP and FSL-lesion_filling, replace lesion voxels with white matter intensities; however, they require precise lesion identification on 3DT1-images. AIM To determine whether 2DT2 lesion masks co-registered to 3DT1 images, yield grey and white matter volumes comparable to precise lesion masks. METHODS 2DT2 lesion masks were linearly co-registered to 20 3DT1-images of MS patients, with nearest-neighbor (NNI), and tri-linear interpolation. As gold-standard, lesion masks were manually outlined on 3DT1-images. LEAP and FSL-lesion_filling were applied with each lesion mask. Grey (GM) and white matter (WM) volumes were quantified with FSL-FAST, and deep gray matter (DGM) volumes using FSL-FIRST. Volumes were compared between lesion mask types using paired Wilcoxon tests. RESULTS Lesion-filling with gold-standard lesion masks compared to native images reduced GM overestimation by 1.93 mL (p < .001) for LEAP, and 1.21 mL (p = .002) for FSL-lesion_filling. Similar effects were achieved with NNI lesion masks from 2DT2. Global WM underestimation was not significantly influenced. GM and WM volumes from NNI, did not differ significantly from gold-standard. GM segmentation differed between lesion masks in the lesion area, and also elsewhere. Using the gold-standard, FSL-FAST quantified as GM on average 0.4% of the lesion area with LEAP and 24.5% with FSL-lesion_filling. Lesion-filling did not influence DGM volumes from FSL-FIRST. DISCUSSION These results demonstrate that for global GM volumetry, precise lesion masks on 3DT1 images can be replaced by co-registered 2DT2 lesion masks. This makes lesion-filling a feasible method for GM atrophy measurements in MS.