RT Journal Article
SR Electronic
T1 Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI
JF American Journal of Neuroradiology
JO Am. J. Neuroradiol.
FD American Society of Neuroradiology
SP 283
OP 291
DO 10.3174/ajnr.A3223
VO 34
IS 2
A1 S. Haller
A1 P. Missonnier
A1 F.R. Herrmann
A1 C. Rodriguez
A1 M.-P. Deiber
A1 D. Nguyen
A1 G. Gold
A1 K.-O. Lovblad
A1 P. Giannakopoulos
YR 2013
UL http://www.ajnr.org/content/34/2/283.abstract
AB BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND 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. ADAlzheimer diseaseaMCIamnestic MCIFAfractional anisotropyMCImild cognitive impairmentmd-aMCImultiple domains MCIsd-aMCIsingle domain amnestic MCIsd-fMCIsingle domain frontal MCISVMsupport vector machineTBSStract-based spatial statistics