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      Baseline MRI Predictors of Conversion from MCI to Probable AD in the ADNI Cohort

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          Abstract

          The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a multi-center study assessing neuroimaging in diagnosis and longitudinal monitoring. Amnestic Mild Cognitive Impairment (MCI) often represents a prodromal form of dementia, conferring a 10-15% annual risk of converting to probable AD. We analyzed baseline 1.5T MRI scans in 693 participants from the ADNI cohort divided into four groups by baseline diagnosis and one year MCI to probable AD conversion status to identify neuroimaging phenotypes associated with MCI and AD and potential predictive markers of imminent conversion. MP-RAGE scans were analyzed using publicly available voxel-based morphometry (VBM) and automated parcellation methods. Measures included global and hippocampal grey matter (GM) density, hippocampal and amygdalar volumes, and cortical thickness values from entorhinal cortex and other temporal and parietal lobe regions. The overall pattern of structural MRI changes in MCI (n=339) and AD (n=148) compared to healthy controls (HC, n=206) was similar to prior findings in smaller samples. MCI-Converters (n=62) demonstrated a very similar pattern of atrophic changes to the AD group up to a year before meeting clinical criteria for AD. Finally, a comparison of effect sizes for contrasts between the MCI-Converters and MCI-Stable (n=277) groups on MRI metrics indicated that degree of neurodegeneration of medial temporal structures was the best antecedent MRI marker of imminent conversion, with decreased hippocampal volume (left > right) being the most robust. Validation of imaging biomarkers is important as they can help enrich clinical trials of disease modifying agents by identifying individuals at highest risk for progression to AD.

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          Vitamin E and donepezil for the treatment of mild cognitive impairment.

          Mild cognitive impairment is a transitional state between the cognitive changes of normal aging and early Alzheimer's disease. In a double-blind study, we evaluated subjects with the amnestic subtype of mild cognitive impairment. Subjects were randomly assigned to receive 2000 IU of vitamin E daily, 10 mg of donepezil daily, or placebo for three years. The primary outcome was clinically possible or probable Alzheimer's disease; secondary outcomes were cognition and function. A total of 769 subjects were enrolled, and possible or probable Alzheimer's disease developed in 212. The overall rate of progression from mild cognitive impairment to Alzheimer's disease was 16 percent per year. As compared with the placebo group, there were no significant differences in the probability of progression to Alzheimer's disease in the vitamin E group (hazard ratio, 1.02; 95 percent confidence interval, 0.74 to 1.41; P=0.91) or the donepezil group (hazard ratio, 0.80; 95 percent confidence interval, 0.57 to 1.13; P=0.42) during the three years of treatment. Prespecified analyses of the treatment effects at 6-month intervals showed that as compared with the placebo group, the donepezil group had a reduced likelihood of progression to Alzheimer's disease during the first 12 months of the study (P=0.04), a finding supported by the secondary outcome measures. Among carriers of one or more apolipoprotein E epsilon4 alleles, the benefit of donepezil was evident throughout the three-year follow-up. There were no significant differences in the rate of progression to Alzheimer's disease between the vitamin E and placebo groups at any point, either among all patients or among apolipoprotein E epsilon4 carriers. Vitamin E had no benefit in patients with mild cognitive impairment. Although donepezil therapy was associated with a lower rate of progression to Alzheimer's disease during the first 12 months of treatment, the rate of progression to Alzheimer's disease after three years was not lower among patients treated with donepezil than among those given placebo. Copyright 2005 Massachusetts Medical Society.
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            Ways toward an early diagnosis in Alzheimer's disease: the Alzheimer's Disease Neuroimaging Initiative (ADNI).

            With the increasing life expectancy in developed countries, the incidence of Alzheimer's disease (AD) and thus its socioeconomic impact are growing. Increasing knowledge over the last years about the pathomechanisms involved in AD allow for the development of specific treatment strategies aimed at slowing down or even preventing neuronal death in AD. However, this requires also that (1) AD can be diagnosed with high accuracy, because non-AD dementias would not benefit from an AD-specific treatment; (2) AD can be diagnosed in very early stages when any intervention would be most effective; and (3) treatment efficacy can be reliably and meaningfully monitored. Although there currently is no ideal biomarker that would fulfill all these requirements, there is increasing evidence that a combination of currently existing neuroimaging and cerebrospinal fluid (CSF) and blood biomarkers can provide important complementary information and thus contribute to a more accurate and earlier diagnosis of AD. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is exploring which combinations of these biomarkers are the most powerful for diagnosis of AD and monitoring of treatment effects.
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              Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI.

              High-dimensional pattern classification was applied to baseline and multiple follow-up MRI scans of the Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with mild cognitive impairment (MCI), in order to investigate the potential of predicting short-term conversion to Alzheimer's Disease (AD) on an individual basis. MCI participants that converted to AD (average follow-up 15 months) displayed significantly lower volumes in a number of grey matter (GM) regions, as well as in the white matter (WM). They also displayed more pronounced periventricular small-vessel pathology, as well as an increased rate of increase of such pathology. Individual person analysis was performed using a pattern classifier previously constructed from AD patients and cognitively normal (CN) individuals to yield an abnormality score that is positive for AD-like brains and negative otherwise. The abnormality scores measured from MCI non-converters (MCI-NC) followed a bimodal distribution, reflecting the heterogeneity of this group, whereas they were positive in almost all MCI converters (MCI-C), indicating extensive patterns of AD-like brain atrophy in almost all MCI-C. Both MCI subgroups had similar MMSE scores at baseline. A more specialized classifier constructed to differentiate converters from non-converters based on their baseline scans provided good classification accuracy reaching 81.5%, evaluated via cross-validation. These pattern classification schemes, which distill spatial patterns of atrophy to a single abnormality score, offer promise as biomarkers of AD and as predictors of subsequent clinical progression, on an individual patient basis.
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                Author and article information

                Journal
                Curr Alzheimer Res
                CAR
                Current Alzheimer Research
                Bentham Science Publishers Ltd.
                1567-2050
                1875-5828
                August 2009
                : 6
                : 4
                : 347-361
                Affiliations
                [1 ]IU Center for Neuroimaging, Division of Imaging Sciences, Department of Radiology, Indiana University School of Medicine, 950 W Walnut St, R2 E124, Indianapolis, IN 46202, USA
                [2 ]Medical Neuroscience Program, Stark Neurosciences Research Institute, Indiana University School of Medicine, 950 W Walnut St, R2 Building, Room 402, Indianapolis, IN 46202, USA
                [3 ]Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA
                [4 ]Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, 410 West 10th Street, Suite 5000, Indianapolis, IN 46202, USA
                Author notes
                [* ]Address correspondence to this author at the IU Center for Neuroimaging, Department of Radiology, Indiana University School of Medicine, 950 W Walnut St, R2 E124, Indianapolis, Indiana 46202, USA; Tel: 317-278-6947; Fax: 317-274-1067; Email: asaykin@ 123456iupui.edu
                Article
                CAR-6-347
                10.2174/156720509788929273
                2764863
                19689234
                dbee4d14-5b34-4fba-be3c-bce1ed66a166
                ©2009 Bentham Science Publishers Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.5/), which permits unrestrictive use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 22 December 2008
                : 22 December 2008
                : 23 December 2008
                Categories
                Article

                Neurology
                hippocampus,alzheimer’s disease neuroimaging initiative (adni),magnetic resonance imaging (mri),cognition.,mild cognitive impairment (mci)

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