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      Cortical thickness in relation to clinical symptom onset in preclinical AD

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          Abstract

          Mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia are preceded by a phase of disease, referred to as ‘preclinical AD’, during which cognitively normal individuals have evidence of AD pathology in the absence of clinical impairment. This study examined whether a magnetic resonance imaging (MRI) measure of cortical thickness in brain regions, collectively known as ‘AD vulnerable’ regions, predicted the time to onset of clinical symptoms associated with MCI and whether cortical thickness was similarly predictive of clinical symptom onset within 7 years post baseline versus progression at a later point in time. These analyses included 240 participants from the BIOCARD study, a cohort of longitudinally followed individuals who were cognitively normal at the time of their MRI (mean age = 56 years). Participants have been followed for up to 18 years ( M follow-up = 11.8 years) and 50 participants with MRIs at baseline have developed MCI or dementia over time (mean time to clinical symptom onset = 7 years). Cortical thickness in AD vulnerable regions was based on the mean thickness of eight cortical regions. Using Cox regression models, we found that lower mean cortical thickness was associated with an increased risk of progression from normal cognition to clinical symptom onset within 7 years of baseline ( p = 0.03), but not with progression > 7 years from baseline ( p = 0.30). Lower cortical thickness was also associated with higher levels of phosphorylated tau, measured in cerebrospinal fluid at baseline. These results suggest that cortical thinning in AD vulnerable regions is detectable in cognitively normal individuals several years prior to the onset of clinical symptoms that are a harbinger of a diagnosis of MCI, and that the changes are more likely to be evident in the years proximal to clinical symptom onset, consistent with hypothetical AD biomarker models.

          Highlights

          • Examined cortical thickness in relation to onset of clinical symptoms of MCI.

          • Cortical thickness was associated with clinical symptom onset within 7 years.

          • Cortical thickness was associated with levels of CSF p-tau, but not CSF amyloid.

          • Changes in cortical thickness may be evident during preclinical AD.

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          Most cited references23

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          Development and validation of a geriatric depression screening scale: a preliminary report.

          A new Geriatric Depression Scale (GDS) designed specifically for rating depression in the elderly was tested for reliability and validity and compared with the Hamilton Rating Scale for Depression (HRS-D) and the Zung Self-Rating Depression Scale (SDS). In constructing the GDS a 100-item questionnaire was administered to normal and severely depressed subjects. The 30 questions most highly correlated with the total scores were then selected and readministered to new groups of elderly subjects. These subjects were classified as normal, mildly depressed or severely depressed on the basis of Research Diagnostic Criteria (RDC) for depression. The GDS, HRS-D and SDS were all found to be internally consistent measures, and each of the scales was correlated with the subject's number of RDC symptoms. However, the GDS and the HRS-D were significantly better correlated with RDC symptoms than was the SDS. The authors suggest that the GDS represents a reliable and valid self-rating depression screening scale for elderly populations.
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            A hybrid approach to the skull stripping problem in MRI.

            We present a novel skull-stripping algorithm based on a hybrid approach that combines watershed algorithms and deformable surface models. Our method takes advantage of the robustness of the former as well as the surface information available to the latter. The algorithm first localizes a single white matter voxel in a T1-weighted MRI image, and uses it to create a global minimum in the white matter before applying a watershed algorithm with a preflooding height. The watershed algorithm builds an initial estimate of the brain volume based on the three-dimensional connectivity of the white matter. This first step is robust, and performs well in the presence of intensity nonuniformities and noise, but may erode parts of the cortex that abut bright nonbrain structures such as the eye sockets, or may remove parts of the cerebellum. To correct these inaccuracies, a surface deformation process fits a smooth surface to the masked volume, allowing the incorporation of geometric constraints into the skull-stripping procedure. A statistical atlas, generated from a set of accurately segmented brains, is used to validate and potentially correct the segmentation, and the MRI intensity values are locally re-estimated at the boundary of the brain. Finally, a high-resolution surface deformation is performed that accurately matches the outer boundary of the brain, resulting in a robust and automated procedure. Studies by our group and others outperform other publicly available skull-stripping tools. Copyright 2004 Elsevier Inc.
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              Improved Localizadon of Cortical Activity by Combining EEG and MEG with MRI Cortical Surface Reconstruction: A Linear Approach.

              Abstract We describe a comprehensive linear approach to the problem of imaging brain activity with high temporal as well as spatial resolution based on combining EEG and MEG data with anatomical constraints derived from MRI images. The "inverse problem" of estimating the distribution of dipole strengths over the cortical surface is highly underdetermined, even given closely spaced EEG and MEG recordings. We have obtained much better solutions to this problem by explicitly incorporating both local cortical orientation as well as spatial covariance of sources and sensors into our formulation. An explicit polygonal model of the cortical manifold is first constructed as follows: (1) slice data in three orthogonal planes of section (needle-shaped voxels) are combined with a linear deblurring technique to make a single high-resolution 3-D image (cubic voxels), (2) the image is recursively flood-filled to determine the topology of the gray-white matter border, and (3) the resulting continuous surface is refined by relaxing it against the original 3-D gray-scale image using a deformable template method, which is also used to computationally flatten the cortex for easier viewing. The explicit solution to an error minimization formulation of an optimal inverse linear operator (for a particular cortical manifold, sensor placement, noise and prior source covariance) gives rise to a compact expression that is practically computable for hundreds of sensors and thousands of sources. The inverse solution can then be weighted for a particular (averaged) event using the sensor covariance for that event. Model studies suggest that we may be able to localize multiple cortical sources with spatial resolution as good as PET with this technique, while retaining a much finer grained picture of activity over time.
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                Author and article information

                Contributors
                Journal
                Neuroimage Clin
                Neuroimage Clin
                NeuroImage : Clinical
                Elsevier
                2213-1582
                15 June 2016
                2016
                15 June 2016
                : 12
                : 116-122
                Affiliations
                [a ]Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21224, USA
                [b ]Department of Biostatistics, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD 21205, USA
                [c ]Center for Imaging Science, Johns Hopkins University, Baltimore, MD 21218, USA
                [d ]Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA
                [e ]Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
                Author notes
                [* ]Corresponding author at: Division of Cognitive Neuroscience, 1620 McElderry Street, Reed Hall 1-West, Baltimore, MD 21205, USA.Division of Cognitive Neuroscience1620 McElderry Street, Reed Hall 1-WestBaltimoreMD21205USA cpettigrew@ 123456jhmi.edu
                Article
                S2213-1582(16)30108-5
                10.1016/j.nicl.2016.06.010
                4932610
                27408796
                a4b46ae1-c421-4008-ba40-212d3150e50f
                © 2016 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 19 February 2016
                : 20 May 2016
                : 11 June 2016
                Categories
                Regular Article

                alzheimer's disease,preclinical ad,cortical thickness,magnetic resonance imaging,cerebrospinal fluid,phosphorylated tau

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