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Diffusion-weighted imaging predicts cognitive impairment in multiple sclerosis
Ralph H Benedict1*,
Jared Bruce2,
Michael G Dwyer2,
Bianca Weinstock-Guttman1,
Chris Tjoa1,
E Tavazzi2,
F E Munschauer1,
Robert Zivadinov1
1 Department of Neurology, State University of New York (SUNY) at
Buffalo, School of Medicine, Buffalo, NY, USA
2 Jacobs Neurological Institute, Buffalo, NY, USA
* To whom correspondence should be addressed.
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Abstract |
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Following a previous study with diffusion tensor imaging, we investigated the
correlation between diffusion-weighted imaging (DWI) and cognitive dysfunction in
multiple sclerosis (MS). We studied 60 MS patients (mean age 45.8±9.0
years) using 1.5-T MRI. Disease course was RR=40 and SP=20.
Mean disease duration was 12.8±8.7 years. Mean EDSS was
3.4±1.7. Whole brain, gray and white matter normalized volumes were
calculated on 3D SPGR T1-WI using a fully automated Hybrid SIENAX method.
Parenchymal mean diffusivity (PMD) maps were created after automated segmentation of
the brain parenchyma and cerebrospinal fluid using T2-WI and DW images. Histogram
analysis was performed and DWI indices of peak position (PP), peak height (PH), mean
parenchymal diffusivity (MPD) and entropy were obtained. Neuropsychological (NP)
evaluation emphasized auditory/verbal and visual/spatial memory, as well as
processing speed and executive function. We found significant correlations between
DWI and performance in all cognitive domains. Overall, stronger correlations emerged
for MPD and entropy than other DWI measures, although all correlations were in the
expected direction. The strongest association was between DWI entropy and
performance on the Symbol Digit Modalities Test, which assesses processing speed and
working memory (r= - 0.54). Fisher r to z
transformations revealed that DWI, gray matter (GMF) and whole brain (BPF) atrophy,
T1-lesion volume (LV) and T2-LV all accounted for similar amounts of variance in NP
testing. Stepwise regression models determined whether multiple MRI measures
predicted unique additive variance in test performance. GMF (R
2=0.35, F=30.82, P<0.01)
and entropy ( R
2=0.06, F=5.47,
P<0.05) both accounted for unique variance in processing speed. Our
data make a stronger case for the clinical validity of DWI in MS than heretofore
reported. DWI has very short acquisition times, and the segmentation method applied
in the present study is reliable and fully automated. Given its overall simplicity
and moderate correlation with cognition, DWI may offer several logistic
advantages over more traditional MRI measures when predicting the presence of NP impairment.
Key Words:
cognition, diffusion-weighted imaging, magnetic resonance imaging, multiple sclerosis, neuropsychology
First published on March 15, 2007, doi:10.1177/1352458507075592
Multiple Sclerosis 2007;13:722.
A more recent version of this article appeared on July 1, 2007

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