# Quantitative Magnetization Transfer Imaging for Early Detection of Alzheimer's Disease > **NIH NIH F30** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2022 · $51,752 ## Abstract Project Summary Alzheimer's disease (AD) is the most common cause of dementia and, at present, an irreversible neurode- generative disease with an ever-increasing disease burden in the United States. Clinical management and de- velopment of novel therapeutics for AD will benefit from reproducible, robust and non-invasive markers of early in vivo AD pathology, but no such tools are well-established in routine clinical practice. Quantitative magnetization transfer (qMT) is an MRI based technique for detecting microstructural tissue changes such as demyelination and the presence of macromolecules, including amyloid beta protein. This sensitivity to multiple aspects of the amy- loid/tau/neurodegeneration framework offers a promising diagnostic alternative to amyloid PET in a single, rapid and high-resolution imaging exam. My preliminary findings suggest that, using the theory of hybrid state free precession developed in my research group, qMT images can be acquired in vivo in 12 minutes at 1mm isotropic resolution with good SNR. Additionally, by direct comparison to PET in a cognitively normal but amyloid positive subject, qMT appears to be sensitive to the early accumulation of amyloid beta and confirms previous literature reports of increased qMT exchange rates in AD. My proposal aims to solve the remaining technical challenges surrounding qMT by optimizing the acquisition for improved sensitivity to amyloid beta (Aim 1) and developing a neural network based reconstruction pipeline to substantially reduce the post-processing time and improve its robustness to magnetic field inhomogeneities (Aim 2), which create biases in the quantitative parameters. These biases are particularly important to curtail in the deep brain, where the accumulation of amyloid beta is purported to begin in AD. In Aim 3, I will perform a pilot study to compare the proposed qMT method's sensitivity for in vivo amyloid beta in a cognitively normal population directly to amyloid PET. Together, this will establish qMT as a surrogate marker for in vivo amyloid and motivate further clinical studies on its utility in monitoring AD progression and response to therapy. ## Key facts - **NIH application ID:** 10464315 - **Project number:** 1F30AG077794-01 - **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE - **Principal Investigator:** Andrew Mao - **Activity code:** F30 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $51,752 - **Award type:** 1 - **Project period:** 2022-08-01 → 2026-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10464315 ## Citation > US National Institutes of Health, RePORTER application 10464315, Quantitative Magnetization Transfer Imaging for Early Detection of Alzheimer's Disease (1F30AG077794-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10464315. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*