title: The Sub-Classification of Amnestic Mild Cognitive Impairment Using MRI-Based Cortical Thickness Measures.
abstract: BACKGROUND
  Amnestic mild cognitive impairment (aMCI) is considered to be the transitional stage between healthy aging and Alzheimer's disease (AD). Moreover, aMCI individuals with additional impairment in one or more non-memory cognitive domains are at higher risk of conversion to AD. Hence accurate identification of the sub-types of aMCI would enable earlier detection of individuals progressing to AD.
  
  
  METHODS
  We examine the group differences in cortical thickness between single-domain and multiple-domain sub-types of aMCI, and as well as with respect to age-matched controls in a well-balanced cohort from the Sydney Memory and Aging Study. In addition, the diagnostic value of cortical thickness in the sub-classification of aMCI as well as from normal controls using support vector machine (SVM) classifier is evaluated, using a novel cross-validation technique that can handle class-imbalance.
  
  
  RESULTS
  This study revealed an increased, as well as a wider spread, of cortical thinning in multiple-domain aMCI compared to single-domain aMCI. The best performances of the classifier for the pairs (1) single-domain aMCI and normal controls, (2) multiple-domain aMCI and normal controls, and (3) single and multiple-domain aMCI were AUC = 0.52, 0.66, and 0.54, respectively. The accuracy of the classifier for the three pairs was just over 50% exhibiting low specificity (44-60%) and similar sensitivity (53-68%).
  
  
  CONCLUSIONS
  Analysis of group differences added evidence to the hypothesis that multiple-domain aMCI is a later stage of AD compared to single-domain aMCI. The classification results show that discrimination among single, multiple-domain sub-types of aMCI and normal controls is limited using baseline cortical thickness measures.
authors.affiliation: School of Engineering Science, Simon Fraser University , Burnaby, BC , Canada.
authors.forename: Pradeep Reddy
authors.initials: PR
authors.lastname: Raamana
authors.affiliation: Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine, University of New South Wales , Sydney, NSW , Australia ; Neuropsychiatric Institute, Prince of Wales Hospital , Randwick, NSW , Australia.
authors.forename: Wei
authors.initials: W
authors.lastname: Wen
authors.affiliation: Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine, University of New South Wales , Sydney, NSW , Australia ; Neuropsychiatric Institute, Prince of Wales Hospital , Randwick, NSW , Australia.
authors.forename: Nicole A
authors.initials: NA
authors.lastname: Kochan
authors.affiliation: Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine, University of New South Wales , Sydney, NSW , Australia ; Dementia Collaborative Research Centre, School of Psychiatry, UNSW Medicine, University of New South Wales , Sydney, NSW , Australia.
authors.forename: Henry
authors.initials: H
authors.lastname: Brodaty
authors.affiliation: Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine, University of New South Wales , Sydney, NSW , Australia ; Neuropsychiatric Institute, Prince of Wales Hospital , Randwick, NSW , Australia.
authors.forename: Perminder S
authors.initials: PS
authors.lastname: Sachdev
authors.affiliation: Feinberg School of Medicine, Northwestern University , Chicago, IL , USA.
authors.forename: Lei
authors.initials: L
authors.lastname: Wang
authors.affiliation: School of Engineering Science, Simon Fraser University , Burnaby, BC , Canada.
authors.forename: Mirza Faisal
authors.initials: MF
authors.lastname: Beg
keywords: Alzheimer; amnestic; classification; cortical thickness; early detection; mild cognitive impairment; subtype