Abstract Details

Title The Power of Multimodal Neuroimaging Biomarkers for Clinical Trial Screening

Topic Aging and Dementia

Presentation(s) P06 - (-)

Poster/Presentation
Number 034

Objective

Background BACKGROUND: As disease-modifying agents emerge for clinical trials it is critical to establish robust and powerful biomarkers for predicting AD or FTLD pathology in individual patients. The identification of statistically powerful biomarkers can achieve substantial cost-savings and increase feasibility of clinical trials involving rare disorders. Recent work suggests that both MRI and DTI can reliably predict AD or FTLD pathology, however the MMS required using these methods has not been evaluated.

Design/Methods DESIGN/METHODS: 139 patients clinically-diagnosed with AD or FTD underwent lumbar puncture, MRI, and DTI scans. Pathology was defined using an autopsy-validated CSF surrogate of total-tau to beta-amyloid ratio: AD (N=50) and FTLD (N=89). MRI and DTI images were processed using Eigenanatomy, a statistically robust dimensionality reduction tool that identifies volumes of interest (VOIs) that account for the greatest variance in a dataset. The imaging cohort was randomly divided into train and test datasets. Within the training dataset we used linear regression and cross-validation with 1000 permutations to identify VOIs that reliably achieve accurate prediction. We then applied these VOIs to the test cohort to evaluate prediction accuracy to determine MSS estimates to achieve beta=0.8.

Results RESULTS: We observed that multimodal neuroimaging achieved higher prediction accuracy (88%) relative to MRI (72%) and DTI (81%) alone. Power analyses suggested MTI and DTI together require the smallest MMS (N=29) to predict pathology in comparison to DTI (N=58) or MRI (N=48) alone.

Conclusions CONCLUSIONS: Multimodal neuroimaging biomarkers that integrate measures of WM and GM provide a statistically powerful method for predicting underlying pathology in order to screen patients for clinical trials.

Authors/Disclosures
Corey McMillan, PhD (University of Pennsylvania) PRESENTER	Dr. McMillan has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Elsevier. The institution of Dr. McMillan has received research support from Biogen. The institution of Dr. McMillan has received research support from NIH.
	No disclosure on file
	No disclosure on file
John Q. Trojanowski, MD, PhD (University of PA School of Med)	Dr. Trojanowski has nothing to disclose.
Murray Grossman, MD, FAAN (University of Pennsylvania)	Dr. Grossman has received personal compensation in the range of $5,000-$9,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Neurology. The institution of Dr. Grossman has received research support from NIH.
	No disclosure on file

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