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Open AccessJournal ArticleDOI

Predicting MCI outcome with clinically available MRI and CSF biomarkers

TLDR
In this paper, the ability of clinically available volumetric MRI (vMRI) and CSF biomarkers, alone or in combination with a quantitative learning measure, to predict conversion to Alzheimer disease (AD) in patients with mild cognitive impairment (MCI).
Abstract
Objective: To determine the ability of clinically available volumetric MRI (vMRI) and CSF biomarkers, alone or in combination with a quantitative learning measure, to predict conversion to Alzheimer disease (AD) in patients with mild cognitive impairment (MCI). Methods: We stratified 192 MCI participants into positive and negative risk groups on the basis of 1) degree of learning impairment on the Rey Auditory Verbal Learning Test; 2) medial temporal atrophy, quantified from Food and Drug Administration–approved software for automated vMRI analysis; and 3) CSF biomarker levels. We also stratified participants based on combinations of risk factors. We computed Cox proportional hazards models, controlling for age, to assess 3-year risk of converting to AD as a function of risk group and used Kaplan-Meier analyses to determine median survival times. Results: When risk factors were examined separately, individuals testing positive showed significantly higher risk of converting to AD than individuals testing negative (hazard ratios [HR] 1.8– 4.1). The joint presence of any 2 risk factors substantially increased risk, with the combination of greater learning impairment and increased atrophy associated with highest risk (HR 29.0): 85% of patients with both risk factors converted to AD within 3 years, vs 5% of those with neither. The presence of medial temporal atrophy was associated with shortest median dementia-free survival (15 months). Conclusions: Incorporating quantitative assessment of learning ability along with vMRI or CSF biomarkers in the clinical workup of MCI can provide critical information on risk of imminent conversion to AD. Neurology ® 2011;77:1619–1628

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Journal ArticleDOI

Hippocampal atrophy in Alzheimer’s disease

TL;DR: The findings in structural MRI studies, especially in those studies utilizing the most recent methods, and the accuracies of those new methods in differentiating AD from healthy controls and stable MCI from progressive MCI are reviewed.
Journal ArticleDOI

The Effect of Baseline Patient and Caregiver Mindfulness on Dementia Outcomes.

TL;DR: In this paper, a cross-sectional study examined patient and caregiver mindfulness with patient and caregivers rating scales and patient cognitive performance and determined whether dyadic pairing of mindfulness influences patient outcomes.
Book ChapterDOI

Genetic and degenerative disorders primarily causing dementia

TL;DR: Tau and inflammation imaging, still in their infancy, combined with genomics, should provide powerful insights into these disorders and facilitate their treatment.
Journal ArticleDOI

Prediction of Amyloid Positivity in Mild Cognitive Impairment Using Fully Automated Brain Segmentation Software

TL;DR: In this article, the predictive ability of volumetric results provided by automated brain segmentation software for cerebral amyloid positivity in mild cognitive impairment (MCI) was evaluated using binary logistic regression and receiver operating characteristic curve analysis.
References
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Journal ArticleDOI

Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade

TL;DR: This work proposes a model that relates disease stage to AD biomarkers in which Abeta biomarkers become abnormal first, before neurodegenerative biomarkers and cognitive symptoms, and neurodegnerative biomarker become abnormal later, and correlate with clinical symptom severity.
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