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Prediction of Alzheimer's disease in subjects with mild cognitive impairment using structural patterns of cortical thinning

Research output: Contribution to book/anthology/report/proceedingBook chapterResearchpeer-review

  • Simon Fristed Eskildsen
  • L.R. Østergaard, Aalborg University
  • ,
  • V. Fonov, McGill University
  • ,
  • P. Coupé, McGill University
  • ,
  • D.L. Collins, McGill University
Predicting Alzheimer's disease (AD) in patients exhibiting early symptoms of cognitive decline may have great influence on treatment and drug discovery. Structural magnetic resonance imaging (MRI) has the potential of revealing early signs of neuro-degeneration in the human brain and may thus aid in predicting and diagnosing AD. Surface-based cortical thickness measurements from T1w MRI have demonstrated high sensitivity to cortical gray matter changes. In this study we investigated the possibility for using patterns of cortical thickness measurements for predicting AD in patients with mild cognitive impairment (MCI). We used a novel technique for identifying cortical regions potentially discriminative for separating subjects with MCI, which progress to AD, from subjects with MCI, which do not progress to AD. Cortical thickness measurements from these selected regions were used in a classifier for testing the ability to predict AD. The classification showed an overall accuracy of 72% for predicting AD conversion in MCI patients 12 months in advance, which is better than recently published results on similar data.
Original languageEnglish
Title of host publicationIFMBE Proceedings
Number of pages4
Volume34 IFMBE
Publication year1 Jan 2011
Pages156-159
DOIs
Publication statusPublished - 1 Jan 2011

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