# Validation of a Novel Magnetic Resonance Imaging (MRI) Technology for both Diagnostic Screening and Quantification of Brain Vascular Physiology in Alzheimer's-Disease-Related Dementias

> **NIH NIH R43** · IMAGINOSTICS, INC. · 2022 · $915,931

## Abstract

PROJECT SUMMARY
Alzheimer’s disease (AD), a degenerative brain disorder, is responsible for 60-70% of all dementia. Currently no
reliable biomarkers exist for precision-medicine-level, single-patient diagnostics for the early detection of
Alzheimer’s disease and related dementias (AD/ADRD). Imaginostics proposes to clinically valdiate novel
magnetic resonance imaging (MRI)-based proprietary biomarkers for the early detection of vascular pathology
that predisposes individuals to develop dementia in patients with mild cognitive impairment (MCI). Further, we
will validate biomarkers for measuring vascular abnormality in Vascular Dementia (VaD), which accounts for
10% of all dementia. Quantitative Ultra-short Time-to-Echo Contrast-Enhanced (QUTE-CE) MRI is unique in that
it generates a quantitative signal directly representative of physiological information.
The overall objective of Phase I proposal: Obtain clinical validation of the QUTE-CE imaging approach for our
panel of biomarkers for measuring microvascular structure, function and leakage. This first validation is targeted
at two groups: 1) MCI: for evaluating the prospects of detecting abnormality before dementia onset and 2) VaD:
for evaluating the prospect of characterizing vascular related cognitive impairment (VCID) in the most pertinent
dementia population. Their ability to detect dementia will be compared to age-matched individuals and also
compared to state-of-the art neuroimaging biomarker approaches to more fully evaluate the potential of QUTE-
CE MRI.
Specific Aim 1: Establish the merit and feasibility of QUTE-CE MRI vascular imaging biomarkers for
detecting vascular abnormality in vascular dementia. The study will include (n=24; 12M/12F) Vascular
Dementia subjects and (n=24; 12M/12F) age-matched control subjects.
Specific Aim 2: Establish the merit and feasibility of QUTE-CE MRI vascular imaging biomarkers for
detecting vascular abnormality in Mild Cognitive Impairment (MCI). The study will include (n=24; 12M/12F)
MCI subjects and (n=24; 12M/12F) age-matched control subjects.
Primary Endpoints (Specific Aims 1 and 2):
(1) Structure: Cerebral Blood Volume (QC-CBV) & Small Vessel Density (QC-SVD): (Hypothesis 1) We will
 test our hypotheses that QUTE-CE MRI can detect small and large vessel abnormality.
(2) Function: Cerebrovascular reactivity (QC-CVR) & CBV-based Functional MRI (QC-fMRI): (Hypothesis
 2) We will test our hypotheses that QUTE-CE MRI will outperform EPI-fMRI for cerebrovascular reactivity at
 the group level, and that QC-CVR can be mapped in individuals MCI and VaD for precision medicine.
(3) Leakage: Blood-Brain Barrier leakage (QC-BBB): (Hypothesis 3) We will test our hypotheses that QUTE-
 CE MRI will outperform DCE-MRI for detecting BBB leakage at the group level, and that BBB leakage can
 be mapped in individuals MCI and VaD for precision medicine.
Further, we will test our hypothesis (Hypothesis 4) that a multivariate model (CBV, CVR, BBB permeability) of
neurova...

## Key facts

- **NIH application ID:** 10547491
- **Project number:** 1R43AG079732-01
- **Recipient organization:** IMAGINOSTICS, INC.
- **Principal Investigator:** Codi Amir Gharagouzloo
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $915,931
- **Award type:** 1
- **Project period:** 2022-09-15 → 2025-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10547491

## Citation

> US National Institutes of Health, RePORTER application 10547491, Validation of a Novel Magnetic Resonance Imaging (MRI) Technology for both Diagnostic Screening and Quantification of Brain Vascular Physiology in Alzheimer's-Disease-Related Dementias (1R43AG079732-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10547491. Licensed CC0.

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