# Building a pathology-validated neuroimaging tool for Alzheimer's Disease

> **NIH NIH R01** · MASSACHUSETTS GENERAL HOSPITAL · 2022 · $472,526

## Abstract

Entorhinal cortex is ground zero for Alzheimer’s disease. This is where the early cortical neurofibrillary
tangles – hyperphosphorylated tau – appear, which ultimately leads to cell death. Once tau pathology
exceeds healthy neurons in EC, the progression from healthy aging to dementia becomes inevitable.
However, despite the primary role of entorhinal cortex initiating memory impairment, current imaging
biomarkers of entorhinal cortex are large and unidimensional surrogates that fail to account for the
earliest tau pathology within this critical structure. Certain EC subregions (i.e. ELr) are hit hard by
neurofibrillary tangles, even in mild cases and others cave much later. An accurate, histopathologically-
validated imaging biomarker of the entorhinal cortex is an essential step towards identifying key
mechanisms of AD pathogenesis and developing novel clinical interventions to stop AD progression.
The objective of this project is to generate an entorhinal subregions segmentation for FreeSurfer to
serve as such a biomarker. This will be histopathologically-defined at a high resolution by multiple
criteria and applicable to other in vivo datasets. Currently, no parcellation software segments an
entorhinal parcellation and post mortem imaging affords excellent resolution and allows for direct
validation of the pathology. Aim 1 is to develop a novel neuroimaging tool that segments the eight EC
subregions in FreeSurfer. Aim 2 is to validate the EC subregions in histology in same cases and
establish neuronal and pathology profiles. Aim 3 is to apply the EC subregion segmentation tool to in
vivo controls, MCI, and AD subjects in existing structural images at 3T and 7T to test against previously
described biomarkers. Comparing the new segmentation against existing biomarkers will ensure
specificity, sensitivity and reliability in vivo. We will also acquire a novel high resolution 650 µm isotropic
MRI dataset in healthy in vivo subjects to push forward a superior resolution for clinical research. The
aims develop a pathologically validated tool that will provide clinical researchers the ability to relate
quantitative imaging with behavioral and clinical measures. Future application to other in vivo cohorts
will transform the specific characterization of the progression from healthy aging to dementia, providing
both increased accuracy in our ability to detect AD, as well as improved biological understanding of the
pathological effects of the disease that will be critical in developing therapeutic interventions.

## Key facts

- **NIH application ID:** 10390478
- **Project number:** 5R01AG057672-05
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Jean Augustinack
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $472,526
- **Award type:** 5
- **Project period:** 2018-08-15 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10390478

## Citation

> US National Institutes of Health, RePORTER application 10390478, Building a pathology-validated neuroimaging tool for Alzheimer's Disease (5R01AG057672-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10390478. Licensed CC0.

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