Recently major efforts in Alzheimer's disease (AD) research have concentrated on the search for disease-associated biomarkers that can identify people at risk for developing AD, help with early diagnosis, prognosis or therapeutic decision-making, and allow for an expedited evaluation of novel disease-modifying therapies. The current project will use an advanced automated hippocampal segmentation approach based on an adaptive machine-learning algorithm paired with the hippocampal radial atrophy mapping technique to establish the dynamic pattern of hippocampal changes that occur in Alzheimer's disease in 3D. AdaBoost is a widely recognized breakthrough computer vision approach that shows great promise as an objective, reproducible and reliable automated hippocampal segmentation technique. While implementing cutting edge mathematical and statistical concepts, the combined technique provides high throughput and sensitivity to disease-associated hippocampal changes. The main goal of this project is to test the performance, variability, robustness and reproducibility of the approach in very large 1.5T and 3T epidemiological and 1.5T clinical trial datasets and to ultimately establish the AdaBoost/radial atrophy methodology as a potential secondary/surrogate outcome measure for clinical trials in AD and MCI that will overcome many of the limitations imposed by the widely used cognitive batteries such as ceiling and floor effects, fluctuations and learning and practice effects. In addition we will identify the hippocampal morphological changes associated with imminent conversion from MCI to AD and investigate potential cognitive and laboratory biomarker correlations with hippocampal atrophy thus investigating potential disease biosignatures.

Public Health Relevance

If no cure is found, AD will affect as many as 10-16 million Americans by year 2050. Recently major efforts in AD research have concentrated on the search for biomarkers that can identify people at risk as early as possible and assess promising disease-modifying therapies presently being evaluated. The proposed research will further validate and establish a state-of-the-art high throughput automated imaging biomarker for use in epidemiological and clinical trial research.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Specialized Center (P50)
Project #
5P50AG016570-14
Application #
8450829
Study Section
Special Emphasis Panel (ZAG1-ZIJ-4)
Project Start
Project End
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
14
Fiscal Year
2013
Total Cost
$153,207
Indirect Cost
$31,613
Name
University of California Los Angeles
Department
Type
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Teng, Edmond; Chow, Nicole; Hwang, Kristy S et al. (2015) Low plasma ApoE levels are associated with smaller hippocampal size in the Alzheimer's disease neuroimaging initiative cohort. Dement Geriatr Cogn Disord 39:154-66
Hsiao, Julia J; Lu, Po H; Grill, Joshua D et al. (2015) Longitudinal declines in instrumental activities of daily living in stable and progressive mild cognitive impairment. Dement Geriatr Cogn Disord 39:24-Dec
Deutsch, Mariel B; Mendez, Mario F; Teng, Edmond (2015) Interactions between traumatic brain injury and frontotemporal degeneration. Dement Geriatr Cogn Disord 39:143-53
Sanchez-Juan, Pascual; Ghosh, Pia M; Hagen, Jayne et al. (2014) Practical utility of amyloid and FDG-PET in an academic dementia center. Neurology 82:230-8
Burggren, Alison; Brown, Jesse (2014) Imaging markers of structural and functional brain changes that precede cognitive symptoms in risk for Alzheimer's disease. Brain Imaging Behav 8:251-61
Ringman, John M; Goate, Alison; Masters, Colin L et al. (2014) Genetic heterogeneity in Alzheimer disease and implications for treatment strategies. Curr Neurol Neurosci Rep 14:499
Ringman, John M; Sachs, Michael C; Zhou, Yan et al. (2014) Clinical predictors of severe cerebral amyloid angiopathy and influence of APOE genotype in persons with pathologically verified Alzheimer disease. JAMA Neurol 71:878-83
Grill, Joshua D; Zhou, Yan; Karlawish, Jason et al. (2014) Does study partner type impact the rate of Alzheimer's disease progression? J Alzheimers Dis 38:507-14
Ma, Qiu-Lan; Zuo, Xiaohong; Yang, Fusheng et al. (2014) Loss of MAP function leads to hippocampal synapse loss and deficits in the Morris Water Maze with aging. J Neurosci 34:7124-36
Apostolova, Liana G; Di, Li Jie; Duffy, Erin L et al. (2014) Risk factors for behavioral abnormalities in mild cognitive impairment and mild Alzheimer's disease. Dement Geriatr Cogn Disord 37:315-26

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