Resting state FDG-PET functional connectivity as an early biomarker of Alzheimer's disease using conjoint univariate and independent component analyses
| Autor: | Marie-Odile Habert, Serge Desarnaud, Paule-Joanne Toussaint, Lucette Lacomblez, Habib Benali, Julien Doyon, Vincent Perlbarg, Pierre Bellec |
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| Rok vydání: | 2012 |
| Předmět: |
Male
Oncology medicine.medical_specialty Pathology Rest Cognitive Neuroscience Population computer.software_genre Alzheimer Disease Fluorodeoxyglucose F18 Voxel Internal medicine Neural Pathways medicine Humans Cognitive decline education Aged Aged 80 and over education.field_of_study medicine.diagnostic_test Resting state fMRI Univariate Brain medicine.disease Early Diagnosis Neurology Positron emission tomography Positron-Emission Tomography Biomarker (medicine) Female Radiopharmaceuticals Alzheimer's disease Psychology computer |
| Zdroj: | NeuroImage. 63:936-946 |
| ISSN: | 1053-8119 |
| DOI: | 10.1016/j.neuroimage.2012.03.091 |
| Popis: | Imaging cerebral glucose metabolism with positron emission tomography (PET) in Alzheimer's disease (AD) has allowed for improved characterisation of this pathology. Such patterns are typically analysed using either univariate or multivariate statistical techniques. In this work we combined voxel-based group analysis and independent component analysis to extract differential characteristic patterns from PET data of glucose metabolism in a large cohort of normal elderly controls and patients with AD. The patterns were used in conjunction with a support vector machine to discriminate between subjects with mild cognitive impairment (MCI) at risk or not of converting to AD. The method was applied to baseline fluoro-deoxyglucose (FDG)-PET images of subjects from the ADNI database. Our approach achieved improved early detection and differentiation of typical versus pathological metabolic patterns in the MCI population, reaching 80% accuracy (85% sensitivity and 75% specificity) when using selected regions. The method has the potential to assist in the advance diagnosis of Alzheimer's disease, and to identify early in the development of the disease those individuals at high risk of rapid cognitive decline who could be candidates for new therapeutic approaches. |
| Databáze: | OpenAIRE |
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