title: Parkinson's disease: interhemispheric textural differences in MR images.
abstract: OBJECTIVE
  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.
  
  
  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.
authors.affiliation: Medical Imaging Center, Tampere University Hospital, Finland. minna.sikio@iki.fi
authors.forename: Minna
authors.initials: M
authors.lastname: Sikiö
authors.forename: Kirsi K
authors.initials: KK
authors.lastname: Holli
authors.forename: Lara C V
authors.initials: LC
authors.lastname: Harrison
authors.forename: Hanna
authors.initials: H
authors.lastname: Ruottinen
authors.forename: Maija
authors.initials: M
authors.lastname: Rossi
authors.forename: Mika T
authors.initials: MT
authors.lastname: Helminen
authors.forename: Pertti
authors.initials: P
authors.lastname: Ryymin
authors.forename: Raija
authors.initials: R
authors.lastname: Paalavuo
authors.forename: Seppo
authors.initials: S
authors.lastname: Soimakallio
authors.forename: Hannu J
authors.initials: HJ
authors.lastname: Eskola
authors.forename: Irina
authors.initials: I
authors.lastname: Elovaara
authors.forename: Prasun
authors.initials: P
authors.lastname: Dastidar
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001921:Brain / Q000473:pathology*; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000175:diagnosis* / Q000473:pathology; D018709:Statistics, Nonparametric