# Developing advanced diffusion MRI for early detection of Alzheimer's disease

> **NIH NIH K99** · STANFORD UNIVERSITY · 2023 · $110,092

## Abstract

Project Summary / Abstract
Alzheimer’s disease (AD) and related dementia are one of the most prevalent neurodegenerative disorders in
the aging population, affecting more than 1 in 10 people aged 65 and older each year in the United States alone.
Since AD is a slow and complex progressive brain disease, early identification of brain changes before the onset
of clinical symptoms is critical for minimizing brain tissue damage and improving the effectiveness of clinical
interventions.
 Diffusion magnetic resonance imaging (MRI) is a promising tool for the early detection of AD because of its
non-invasiveness, wide availability, and sensitivity to subtle brain microstructural changes. Unfortunately, current
diffusion MRI techniques can be inadequate for several reasons, including (1) insufficient spatial resolution to
accurately delineate important but fine-scale white matter pathways in the medial temporal lobe (MTL), a critical
region in the early propagation of AD; and (2) a lack of specificity to reveal the underpinning brain microstructural
changes from early neuronal injury and dysfunction. The innovation of this proposal mainly lies in the joint use
of SNR-efficient high-resolution diffusion acquisition and advanced diffusion encoding strategies to effectively
address the accuracy and specificity limitations of current diffusion MRI methods. Specifically, this project will (1)
develop a high-resolution MRI protocol for more accurate segmentation of white and gray matter regions that
are first affected by and play critical roles in AD propagation; (2) develop advanced diffusion encoding waveforms
for more sensitive and specific characterization of subtle brain microstructural changes at the early stage of AD;
and (3) use existing AD molecular biomarkers to rigorously evaluate the efficacy of the new diffusion biomarkers
for early AD detection.
 The outcomes of this proposal will lay the foundation for studying the longitudinal AD progression,
elucidating the underlying AD pathogenesis, and evaluating new intervention strategies to prevent and/or slow
down AD onset and/or progression. The candidate has a strong background and extensive training in MRI
physics, engineering, image processing, and brain imaging. With the additional training in cognitive neuroscience,
biostatistics, and multimodal neuroimaging provided by this program, he will be well equipped as an independent
researcher focusing on (1) developing advanced neuroimaging techniques with a strong focus on MRI; and (2)
employing a multimodal toolset to address fundamental questions in basic neuroscience research and
neurodegenerative disease studies.

## Key facts

- **NIH application ID:** 10740034
- **Project number:** 1K99AG080076-01A1
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Erpeng Dai
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $110,092
- **Award type:** 1
- **Project period:** 2023-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10740034

## Citation

> US National Institutes of Health, RePORTER application 10740034, Developing advanced diffusion MRI for early detection of Alzheimer's disease (1K99AG080076-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10740034. Licensed CC0.

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