Subcortical and periventricular white matter hyperintensities (WMHs) may have different associations with cognition and pathophysiology. The aim of the present study is to develop an automated method for construction of periventricular WMH maps that enables the analysis of between-group differences in WMH location and characteristics in the periventricular region without the requirement of prior boundary definition. To avoid influence of WMHs on spatial normalization, a reference image of the lateral ventricles was constructed based on images of 24 subjects. Construction was not biased to a single subject. WMHs were segmented by k-nearest neighbor-based classification of magnetic resonance inversion recovery and fluid attenuated inversion recovery images. Cerebrospinal fluid segmentations of individual subjects were nonrigidly mapped to the reference image of the lateral ventricles. The subject’s WMHs were transformed to the reference space accordingly. Spatial normalization accuracy was validated using measures of overlap and of displacement relative to the boundary of the lateral ventricles. After spatial normalization, the boundaries of the lateral ventricles closely matched the reference image and in an area of approximately 1 cm around the lateral ventricles the relative displacement was less than 1 mm. To illustrate the method, it was applied to 61 patients with Type 2 diabetes and 26 control subjects, whereupon periventricular WMH maps were constructed and compared. The proposed method is particularly suited to analyze WMH distribution differences at the level of the lateral ventricles between large groups of patients.

Copyright 2009 Wiley-Liss, Inc