Changes in DWI and MRS associated with white matter hyperintensities in elderly subjects

Abstract

Damage associated with WMH is detectable in NAWM.

Longitudinal 1H MRS changes in mild cognitive impairment and Alzheimer's disease

“…With a larger group of aMCI and control subjects in this study, the trend we previously observed was statistically significant, which is in agreement with two other recent studies [5] [6]. Normal appearing white matter NAA/Cr is negatively associated with the volume of white matter hyperintensities in elderly subjects [12]. However, we did not find an association between the leukoaraiosis ratings and metabolite ratios in the predominantly gray matter posterior cingulate voxel after accounting for age.…”

White Matter Hyperintensities Are Associated With Impairment of Memory, Attention, and Global Cognitive Performance in Older Stroke Patients

“…The method of WMH volume measure has been described in detail previously and validated using a manually adjusted contour threshold technique. 26 FLAIR images were spatially normalized to the T1-weighted Montreal Neurological Institute (MNI) template, which approximates Talairach space, 27 using a 12-parameter affine transformation and nonlinear iterations. 28 Images were then resampled to a voxel size of 2ϫ2ϫ2 mm 3 using bilinear interpolation and automatically segmented using a cluster analysis into gray matter, white matter, cerebrospinal fluid, and a fourth partition consisting of skull, fat muscle, and voxels with a high degree of partial voluming.…”

“…This semiautomated process for identifying WMH has been previously validated by comparison with a manual region of interest approach with excellent concordance (correlation Ͼ0.95). 26 …”

Elevated Plasma Homocysteine Is Associated with Increased Brain Atrophy Rates in Older Subjects with Mild Hypertension

“…This analysis is described in more detail elsewhere [15]. The non-brain regions of the image were removed using the segmentation routines in SPM99 (http://www.fil.ion.ucl.ac.uk/spm/), and the WML were segmented on a slice-by-slice basis (with the images in native space) using a threshold determined from the histogram of pixel intensities for each image slice.…”

“…The non-brain regions of the image were removed using the segmentation routines in SPM99 (http://www.fil.ion.ucl.ac.uk/spm/), and the WML were segmented on a slice-by-slice basis (with the images in native space) using a threshold determined from the histogram of pixel intensities for each image slice. We have previously compared the automated segmentation with a semi-automated technique, and found the mean difference between the two techniques to be 0.53 ml (SD 3.4 ml) [15]. A periventricular region was defined automatically, and separate volumes for periventricular and deep WMLs calculated separately.…”