White matter hyperintensities segmentation: a new semi-automated method

• Main Authors: Mariangela eIorio, Gianfranco eSpalletta, Chiara eChiapponi, Giacomo eLuccichenti, Claudia eCacciari, Maria Donata Orfei, Carlo eCaltagirone, Fabrizio ePiras
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2013-12-01
• Series: Frontiers in Aging Neuroscience
• Subjects: MRI; MCI; white matter hyperintensities; lesion segmentation; FLAIR
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fnagi.2013.00076/full

White matter hyperintensities (WMH) are brain areas of increased signal on T2-weighted or fluid attenuated inverse recovery magnetic resonance imaging (MRI) scans. In this study we present a new semi-automated method to measure WMH load that is based on the segmentation of the intensity histogram of fluid-attenuated inversion recovery images. Thirty patients with Mild Cognitive Impairment with variable WMH load were enrolled. The semi-automated WMH segmentation included: removal of non-brain tissue, spatial normalization, removal of cerebellum and brain stem, spatial filtering, thresholding to segment probable WMH, manual editing for correction of false positives and negatives, generation of WMH map and volumetric estimation of the WMH load. Accuracy was quantitatively evaluated by comparing semi-automated and manual WMH segmentations performed by two independent raters. Differences between the two procedures were assessed using Student’s t tests and similarity was evaluated using linear regression model and Dice Similarity Coefficient (DSC). The volumes of the manual and semi-automated segmentations did not statistically differ (t-value= -1.79, DF=29, p= 0.839 for rater 1; t-value= 1.113, DF=29, p= 0.2749 for rater 2), were highly correlated (R²= 0.921, F (1,29) =155,54, p