# Cross-correlation of biomechanical, connectomic, and pathologic markers in Alzheimer's disease at 7T MRI

> **NIH NIH R21** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2020 · $472,501

## Abstract

Early diagnosis of Alzheimer’s disease (AD) is still challenging, because of the subtlety of the
microstructural changes it initially causes in the brain and the difficulty of identifying them with traditional
neuroimaging techniques such as MRI, PET or CT scans.
 Recently, a novel perspective has suggested that the mechanical properties of brain tissue
might serve as an important biomarker carrying information about the tissue’s physiological and
pathological status. Such mechanical properties can be measured by means of magnetic resonance
elastography (MRE), a technique which allows to obtain the stiffness of specific neuroanatomical regions
in vivo and non-invasively with a sub-millimeter resolution. Previous MRE studies have clearly indicated
that AD is characterized by brain tissue softening accompanying neurodegeneration. However, MRE at
conventional field strengths (i.e., 3 Tesla, or 3T) alone is insufficient to characterize how variations in
regional viscoelasticity correlate with tissue microstructure.
 The goal of this proposal is to bring forward a novel platform for the joint analysis of
biomechanical, connectomic and pathologic markers in AD patients, thanks to ultrahigh field (7T)
MR neuroimaging. The development of specialized sequences for 7T MRE and 7T diffusion MRI scans
will enable the comparison of neuromechanic and microstructural data in AD patients at an
unprecedented resolution; this, in turn, will provide a deeper understanding of the in vivo pathophysiology
of AD and allow us to potentially identify a set of viscoelastic and tractographic markers of disease
pathology. Specifically, we expect our integrated approach to help us validate ultrahigh field MRE
as a unique tool to improve AD diagnosis and prognostic measurements. Our central hypothesis is
that ultrahigh field MRE provides a unique and powerful measure of biomechanical changes associated
with AD in the brain, and may be integrated with existing ultrahigh neuroimaging tools to achieve
unprecedented visualization of the consequences of disease pathology.
 In short, the proposed research offers a potential shift in imaging for AD diagnosis by
connecting microstructural changes and tissue-level viscoelasticity of the brain for the first time.
Advanced image analysis of such data may also improve discrimination of AD from other
neurodegenerative conditions displaying similar clinical manifestations. Ultimately, understanding the
patterns of microstructural variations typical of AD might provide a tool for pharmacological and clinical
studies aimed at developing better treatment options.

## Key facts

- **NIH application ID:** 10143367
- **Project number:** 1R21AG071179-01
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Priti Balchandani
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $472,501
- **Award type:** 1
- **Project period:** 2020-09-15 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10143367

## Citation

> US National Institutes of Health, RePORTER application 10143367, Cross-correlation of biomechanical, connectomic, and pathologic markers in Alzheimer's disease at 7T MRI (1R21AG071179-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10143367. Licensed CC0.

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