title: The fornix sign: a potential sign for Alzheimer's disease based on diffusion tensor imaging.
abstract: BACKGROUND
  We investigated a simple imaging sign for Alzheimer's disease (AD), using diffusion tensor imaging (DTI). We hypothesized that a reduction in fractional anisotropy (FA) in the fornix could be utilized as an imaging sign.
  
  
  METHODS
  Twenty-three patients with AD, 24 patients with amnestic mild cognitive impairment (aMCI), and 25 control participants (NC) underwent DTI at baseline and 1 year later. The diagnosis was reevaluated 1 year and 3 years after the initial scan. A color-scaled FA map was used to visually identify the FA reduction ("fornix sign"). We investigated whether the fornix sign could separate AD from NC, and could predict progression from aMCI to AD or NC to aMCI. We also quantified FA of the fornix to validate the fornix sign.
  
  
  RESULTS
  The fornix sign was identical to the lack of any voxels with an FA > .52 within the fornix. The fornix sign differentiated AD from NC with specificity of 1.0 and sensitivity of .56. It predicted conversion from NC to aMCI with specificity of 1.0 and sensitivity of .67, and from aMCI to AD with specificity of .94 and sensitivity of .83.
  
  
  CONCLUSIONS
  The fornix sign is a promising predictive imaging sign of AD.
authors.affiliation: Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA. koishi@mri.jhu.edu
authors.forename: Kenichi
authors.initials: K
authors.lastname: Oishi
authors.forename: Michelle M
authors.initials: MM
authors.lastname: Mielke
authors.forename: Marilyn
authors.initials: M
authors.lastname: Albert
authors.forename: Constantine G
authors.initials: CG
authors.lastname: Lyketsos
authors.forename: Susumu
authors.initials: S
authors.lastname: Mori
mesh_terms: D000368:Aged; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000473:pathology; D016880:Anisotropy; D016022:Case-Control Studies; D056324:Diffusion Tensor Imaging / Q000379:methods*; D018450:Disease Progression; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008297:Male; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity