title: Individual classification of mild cognitive impairment subtypes by support vector machine analysis of white matter DTI.
abstract: OBJECTIVE
  MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI.
  
  
  METHODS
  Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs.
  
  
  RESULTS
  The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI.
  
  
  CONCLUSIONS
  Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.
authors.affiliation: Service neuro-diagnostique et neuro-interventionnel DISIM, Hôpitaux Universitaires de Genève, Rue GabriellePerret-Gentil 4, 1211 Genève 14, Switzerland. sven.haller@hcuge.ch
authors.forename: S
authors.initials: S
authors.lastname: Haller
authors.forename: P
authors.initials: P
authors.lastname: Missonnier
authors.forename: F R
authors.initials: FR
authors.lastname: Herrmann
authors.forename: C
authors.initials: C
authors.lastname: Rodriguez
authors.forename: M-P
authors.initials: MP
authors.lastname: Deiber
authors.forename: D
authors.initials: D
authors.lastname: Nguyen
authors.forename: G
authors.initials: G
authors.lastname: Gold
authors.forename: K-O
authors.initials: KO
authors.lastname: Lovblad
authors.forename: P
authors.initials: P
authors.lastname: Giannakopoulos
mesh_terms: D000368:Aged; D000647:Amnesia / Q000145:classification / Q000175:diagnosis; D016880:Anisotropy; D060825:Cognitive Dysfunction / Q000145:classification* / Q000175:diagnosis*; D003937:Diagnosis, Differential; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D056784:Leukoencephalopathies / Q000145:classification / Q000175:diagnosis; D008297:Male; D008875:Middle Aged; D009413:Nerve Fibers, Myelinated / Q000473:pathology*; D009483:Neuropsychological Tests; D011446:Prospective Studies; D060388:Support Vector Machine