title: Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer's disease.
abstract: Subjects with mild cognitive impairment (MCI) have an increased risk to develop Alzheimer's disease (AD). Voxel-based MRI studies have demonstrated that widely distributed cortical and subcortical brain areas show atrophic changes in MCI, preceding the onset of AD-type dementia. Here we developed a novel data mining framework in combination with three different classifiers including support vector machine (SVM), Bayes statistics, and voting feature intervals (VFI) to derive a quantitative index of pattern matching for the prediction of the conversion from MCI to AD. MRI was collected in 32 AD patients, 24 MCI subjects and 18 healthy controls (HC). Nine out of 24 MCI subjects converted to AD after an average follow-up interval of 2.5 years. Using feature selection algorithms, brain regions showing the highest accuracy for the discrimination between AD and HC were identified, reaching a classification accuracy of up to 92%. The extracted AD clusters were used as a search region to extract those brain areas that are predictive of conversion to AD within MCI subjects. The most predictive brain areas included the anterior cingulate gyrus and orbitofrontal cortex. The best prediction accuracy, which was cross-validated via train-and-test, was 75% for the prediction of the conversion from MCI to AD. The present results suggest that novel multivariate methods of pattern matching reach a clinically relevant accuracy for the a priori prediction of the progression from MCI to AD.
authors: Department of Neuroradiology, Technische Universität München, Munich, Germany.
authors: Claudia
authors: C
authors: Plant
authors: Stefan J
authors: SJ
authors: Teipel
authors: Annahita
authors: A
authors: Oswald
authors: Christian
authors: C
authors: Böhm
authors: Thomas
authors: T
authors: Meindl
authors: Janaina
authors: J
authors: Mourao-Miranda
authors: Arun W
authors: AW
authors: Bokde
authors: Harald
authors: H
authors: Hampel
authors: Michael
authors: M
authors: Ewers
mesh_terms: D000368:Aged; D000465:Algorithms; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000473:pathology; D001284:Atrophy; D001331:Automation; D001499:Bayes Theorem; D001921:Brain / Q000473:pathology*; D016000:Cluster Analysis; D003072:Cognition Disorders / Q000175:diagnosis / Q000473:pathology; D057225:Data Mining; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity