Predicting Clinical Scores from Magnetic Resonance Scans in Alzheimer's Disease
Autor: | Cynthia M. Stonnington, Stefan Klöppel, Richard S.J. Frackowiak, John Ashburner, Clifford R. Jack, Carlton Chu |
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Přispěvatelé: | Alzheimer Disease Neuroimaging Initiative |
Jazyk: | angličtina |
Rok vydání: | 2010 |
Předmět: |
Male
Audiology Neuropsychological Tests 030218 nuclear medicine & medical imaging 0302 clinical medicine Cognition Image Processing Computer-Assisted Likelihood Functions medicine.diagnostic_test relevance vector regression Neuropsychology Alzheimer's disease Middle Aged Verbal Learning Magnetic Resonance Imaging 3. Good health machine learning Neurology Predictive value of tests Data Interpretation Statistical Regression Analysis Female ADAS-Cog Psychology medicine.medical_specialty Cognitive Neuroscience Verbal learning behavioral disciplines and activities MMSE Article 03 medical and health sciences multivariate Neuroimaging Rating scale Alzheimer Disease Predictive Value of Tests mental disorders medicine Humans Psychiatry Aged Alzheimer Disease/pathology Alzheimer Disease/psychology Cognition/physiology Psychomotor Performance/physiology Reproducibility of Results Verbal Learning/physiology Magnetic resonance imaging Voxel-based morphometry medicine.disease AVLT DRS human activities 030217 neurology & neurosurgery Psychomotor Performance |
Zdroj: | NeuroImage NeuroImage, vol. 51, no. 4, pp. 1405-1413 |
ISSN: | 1095-9572 1053-8119 |
Popis: | Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale—Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P |
Databáze: | OpenAIRE |
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