Amnestic MCI future clinical status prediction using baseline MRI features

Simon Duchesne, Christian Bocti, Kathy De Sousa, Giovanni B. Frisoni, Howard Chertkow, D. Louis Collins

Research output: Contribution to journalArticle

Abstract

Amnestic mild cognitive impairment (aMCI) individuals are known to be at risk for progression to clinically probable Alzheimer's disease (AD). The objective of this work is to measure the accuracy of an automated classification technique based on clinical-quality, single time-point structural magnetic resonance imaging (MRI) scans for the retrospective prediction of future clinical status in aMCI. Thirty-one aMCI research subjects were followed with annual clinical reassessment after baseline MRI. Twenty subjects progressed to probable AD within an average 2.2 (1.4) years [mean age 76.6 (4.7) years, MMSE 27.1 (2.3)], while 11 remained non-demented on average 5.6 (2.6) years after baseline [mean age 73.3 (7.2) years, MMSE 28.2 (1.8)]. Leave-one-out classification was performed within a multidimensional MRI feature space built from intensity and local volume estimate data of a reference group of 75 probable AD and 75 age-matched control subjects. Prediction using aMCI data reached 81% accuracy, 70% sensitivity and 100% specificity. This automated and objective method has potential in helping predict future clinical status in aMCI.

Original languageEnglish
Pages (from-to)1606-1617
Number of pages12
JournalNeurobiology of Aging
Volume31
Issue number9
DOIs
Publication statusPublished - Sep 2010

Keywords

  • Automated computer classification
  • Early detection
  • Magnetic resonance imaging
  • Mild cognitive impairment

ASJC Scopus subject areas

  • Clinical Neurology
  • Neuroscience(all)
  • Ageing
  • Developmental Biology
  • Geriatrics and Gerontology

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