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OBJECTIVES Our aim was to assess cortical thickness in a large multicenter cohort of drug-naive patients with early Parkinson disease (PD), with and without mild cognitive impairment (MCI), and explore the cognitive correlates of regional cortical thinning. METHODS One hundred twenty-three newly diagnosed patients with PD and 56 healthy controls with(More)
Automated structural magnetic resonance imaging (MRI) processing pipelines are gaining popularity for Alzheimer’s disease (AD) research. They generate regional volumes, cortical thickness measures and other measures, which can be used as input for multivariate analysis. It is not clear which combination of measures and normalization approach are most useful(More)
We determined predictors of conversion to Alzheimer's disease (AD) from mild cognitive impairment (MCI) with automated magnetic resonance imaging (MRI) regional cortical volume and thickness measures. One hundred amnestic MCI subjects, 118 AD patients, and 94 age-matched healthy controls were selected from AddNeuroMed study. Twenty-four regional cortical(More)
INTRODUCTION The aim of this study was to determine whether years of schooling influences regional cortical thicknesses and volumes in Alzheimer's disease (AD), mild cognitive impairment (MCI), and healthy age-matched controls. METHODS Using an automated image analysis pipeline, 33 regional cortical thickness and 15 regional volumes measures from MRI(More)
The default mode network (DMN) is particularly relevant to Alzheimer's disease (AD) since its structures are vulnerable to deposition of amyloid. Decreased levels of β-amyloid(1-42) (Aβ42) and increased total tau protein (T-tau) and tau phosphorylated at position threonine 181 (P-tau(181p)) in cerebrospinal fluid (CSF) have been established as valid(More)
In neurodegeneration research, normalization of regional volumes by intracranial volume (ICV) is important to estimate the extent of disease-driven atrophy. There is little agreement as to whether raw volumes, volume-to-ICV fractions or regional volumes from which the ICV factor has been regressed out should be used for volumetric brain imaging studies.(More)
Changes in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve(More)
We propose a novel approach to predicting disease progression in Alzheimer's disease (AD)--multivariate ordinal regression--which inherently models the ordered nature of brain atrophy spanning normal aging (CTL) to mild cognitive impairment (MCI) to AD. Ordinal regression provides probabilistic class predictions as well as a continuous index of disease(More)
The suggested revision of the NINCDS-ADRDA criterion for the diagnosis of Alzheimer's disease (AD) includes at least one abnormal biomarker among magnetic resonance imaging (MRI), positron emission tomography (PET) and cerebrospinal fluid (CSF). We aimed to investigate if the combination of baseline MRI and CSF could enhance the classification of AD(More)
We have used multivariate data analysis, more specifically orthogonal partial least squares to latent structures (OPLS) analysis, to discriminate between Alzheimer's disease (AD), mild cognitive impairment (MCI) and elderly control subjects combining both regional and global magnetic resonance imaging (MRI) volumetric measures. In this study, 117 AD(More)