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Acad Radiol. 2011 Oct;18(10):1217-24. doi: 10.1016/j.acra.2011.06.007. Epub 2011 Jul 23.

Parkinson's disease: interhemispheric textural differences in MR images.

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  • 1Medical Imaging Center, Tampere University Hospital, Finland. minna.sikio@iki.fi

Abstract

RATIONALE AND OBJECTIVES:

Early-stage diagnosis of Parkinson's disease (PD) is essential in making decisions related to treatment and prognosis. However, there is no specific diagnostic test for the diagnosis of PD. The aim of this study was to evaluate the role of texture analysis (TA) of magnetic resonance images in detecting subtle changes between the hemispheres in various brain structures in patients with early symptoms of parkinsonism. In addition, functional TA parameters for detecting textural changes are presented.

MATERIALS AND METHODS:

Fifty-one patients with symptoms of PD and 20 healthy controls were imaged using a 3-T magnetic resonance device. Co-occurrence matrix-based TA was applied to detect changes in textures between the hemispheres in the following clinically interesting areas: dentate nucleus, basilar pons, substantia nigra, globus pallidus, thalamus, putamen, caudate nucleus, corona radiata, and centrum semiovale. The TA results were statistically evaluated using the Mann-Whitney U test.

RESULTS:

The results showed interhemispheric textural differences among the patients, especially in the area of basilar pons and midbrain. Concentrating on this clinically interesting area, the four most discriminant parameters were defined: co-occurrence matrix correlation, contrast, difference variance, and sum variance. With these parameters, differences were also detected in the dentate nucleus, globus pallidus, and corona radiata.

CONCLUSIONS:

On the basis of this study, interhemispheric differences in the magnetic resonance images of patients with PD can be identified by the means of co-occurrence matrix-based TA. The detected areas correlate with the current pathophysiologic and neuroanatomic knowledge of PD.

Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.

PMID:
21784670
[PubMed - indexed for MEDLINE]
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