# Core F: Neuroimaging Core

> **NIH NIH P30** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $494,007

## Abstract

ABSTRACT
The Imaging Core of the UCSF Alzheimer’s Disease Research Center (ADRC) actively supports the Center by
managing acquisition, archiving, and processing of high quality structural and functional MRI and PET datasets
and providing these data to ADRC and other investigators. In previous cycles of our P50 center, the Imaging
Core has been a leader in applying cutting-edge structural, functional, and molecular imaging techniques to the
heterogeneous cohorts followed in the Clinical Core. In this new P30 application, the Imaging Core will pursue
the following aims: Aim 1: Collection and archiving of images and maintenance of an image database. We
will supervise management of the following MRI and PET sequences from ADRC enrollees: MP-RAGE, FLAIR,
T2-weighted, DTI, ASL perfusion, ICN-fMRI, and amyloid and tau PET scans. We will archive de-identified
images on a server accessible to the rest of the ADRC investigators and provide tools for locating and
downloading images for analysis. We will also upload MRI and PET imaging datasets to the NACC to facilitate
sharing, and we will be available to answer questions for investigators interested in using these images. Aim 2:
Image quality control and preprocessing: We will employ QC and pre-processing frameworks for MPRAGE,
DTI, ASL-MRI, ICN-fMRI, and amyloid and tau PET images, facilitating their use by AD researchers and their
integration into multi-modality analyses. Aim 3: Development and dissemination of standard and innovative
analytic tools: We will maintain and refine an array of tools to characterize disease related changes in brain
volume, white matter microstructure, white matter signal hyperintensity, fMRI-based connectivity, cerebral
perfusion, and PET ligand binding, including optimizing pipelines for cross-sectional and longitudinal analyses.
We will further develop sophisticated classification engines capable of utilizing multiple forms of data and multiple
types of relationships within our data, such as machine-learning based tools and voxel-wise implementation of
mixed linear models. Aim 4: Support research training: We will work with the Research Education
Component to integrate basic principles of image acquisition and analysis into the research training program
and support additional training of individuals who wish to incorporate image analysis into their set of research
skills. In pursuing these aims, the Imaging Core will interact extensively with all other ADRC cores, working
towards the common goals of improving diagnostic accuracy, forwarding our understanding of disease
mechanisms, and enabling drug discovery by improving clinical trial design.

## Key facts

- **NIH application ID:** 10431785
- **Project number:** 5P30AG062422-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** HOWARD J ROSEN
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $494,007
- **Award type:** 5
- **Project period:** 2019-05-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10431785

## Citation

> US National Institutes of Health, RePORTER application 10431785, Core F: Neuroimaging Core (5P30AG062422-04). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10431785. Licensed CC0.

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