title: Regional white matter integrity differentiates between vascular dementia and Alzheimer disease.
abstract: OBJECTIVE
  Considerable clinical and radiological overlap between vascular dementia (VaD) and Alzheimer disease (AD) often makes the diagnosis difficult. Diffusion-tensor imaging studies showed that fractional anisotropy (FA) could be a useful marker for white matter changes. This study aimed to identify regional FA changes to identify a biomarker that could be used to differentiate VaD from AD.
  
  
  METHODS
  T1-weighted and diffusion-tensor imaging scans were obtained in 13 VaD patients, 16 AD patients, and 22 healthy elderly controls. We used tract-based spatial statistics to study regional changes in fractional anisotropy in AD, VaD, and elderly controls. We then used probabilistic tractography to parcel the corpus callosum in 7 regions according to its connectivity with major cerebral cortices using diffusion-tensor imaging data set. We compared the volume and mean FA in each set of transcallosal fibers between groups using ANOVA and then applied a discriminant analysis based on FA and T2-weighted imaging measures.
  
  
  RESULTS
  FA reduction in forceps minor was the most significant area of difference between AD and VaD. Segmentation of the corpus callosum using tractography and comparison of FA changes of each segment confirmed the FA changes in transcallosal prefrontal tracts of patients with VaD when compared to AD. The best discriminant model was the combination of transcallosal prefrontal FA and Fazekas score with 87.5% accuracy, 100% specificity, and 93% sensitivity (P<0.0001).
  
  
  CONCLUSIONS
  Integrating mean FA in the forceps minor to the Fazekas score provides a useful quantitative marker for differentiating AD from VaD.
authors.affiliation: FMRIB Centre, University Oxford, Oxford, UK. mojtaba@fmrib.ox.ac.uk
authors.forename: Mojtaba
authors.initials: M
authors.lastname: Zarei
authors.forename: Jeske S
authors.initials: JS
authors.lastname: Damoiseaux
authors.forename: Ciro
authors.initials: C
authors.lastname: Morgese
authors.forename: Christian F
authors.initials: CF
authors.lastname: Beckmann
authors.forename: Steve M
authors.initials: SM
authors.lastname: Smith
authors.forename: Paul M
authors.initials: PM
authors.lastname: Matthews
authors.forename: Philip
authors.initials: P
authors.lastname: Scheltens
authors.forename: Serge A R B
authors.initials: SA
authors.lastname: Rombouts
authors.forename: Frederik
authors.initials: F
authors.lastname: Barkhof
mesh_terms: D000368:Aged; D000465:Algorithms; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000473:pathology*; D000704:Analysis of Variance; D016880:Anisotropy; D001921:Brain / Q000473:pathology*; D015331:Cohort Studies; D003337:Corpus Callosum / Q000473:pathology; D015140:Dementia, Vascular / Q000175:diagnosis* / Q000473:pathology*; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male