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Neuroradiology |
1 From the Max-Planck-Institut für Psychiatrie, Kraepelinstrasse 10, 80804 Munich, Germany (D.P.A., B.P., C.G., G.K.E.), and the Department of Neurology, Klinikum Grosshadern, Ludwig-Maximilians-Universität, Munich, Germany (T.G., M.D.). Received March 28, 2000; revision requested May 14; revision received June 28; accepted July 25. Address correspondence to D.P.A. (e-mail: auer@mpipsykl.mpg.de).
PURPOSE: To differentiate lesion patterns in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) from those in patients with sporadic subcortical arteriosclerotic encephalopathy (sSAE).
MATERIALS AND METHODS: Magnetic resonance (MR; T2-weighted and fluid-attenuated inversion-recovery) images obtained in 28 patients with CADASIL were compared with images obtained in 24 patients with sSAE by using an automated pixel-based group comparison with statistical parametric mapping and regional semiquantitative rating.
RESULTS: Visual rating showed higher lesion scores for CADASIL in the temporal and temporopolar white matter (WM). Statistical parametric mapping group analysis independently revealed more extensive bilateral involvement of the anterior temporal and superior frontal WM in CADASIL. There were bilateral signal intensity reductions within the dentate nucleus, deep cerebellar WM, crus cerebri, and thalamus. Lesions extended remarkably more often into arcuate fibers in the temporopolar and paramedian superior frontal lobes in CADASIL. Linear discriminant analysis was used to classify 96% (50 of 52) of the cases correctly, with temporopolar WM and arcuate fiber involvement contributing most to the discrimination function.
CONCLUSION: The presented MR imaging criteria are useful in the diagnostic work-up in patients with leukoencephalopathy and help to differentiate CADASIL from sSAE. The observed pattern of vulnerability in CADASIL suggests future directions for research in the pathophysiology of this disorder. In addition, the study demonstrates the potential of automated image analysis to explore MR imaging lesion patterns.
Index terms: Brain, cortex, 10.184, 10.879 • Brain, diseases, 10.184, 10.879 • Brain, infarction, 10.78 • Brain, MR, 10.121411, 10.121413 • Chromosomes, abnormalities, 10.184
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