# MR Imaging of Bioscaffold-Induced Neural Progenitor Migration

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2022 · $368,424

## Abstract

Abstract
The regeneration of brain tissue has been considered one of the greatest challenges for
regenerative medicine. Implantation of an extracellular matrix (ECM) hydrogel can
produce de novo brain tissue by attracting endogenous neural progenitors into a tissue
cavity. These neural progenitors originate in the subventricular zone (SVZ), one of the few
neurogenic sites in the adult brain. Initially, neural progenitors migrate in the peri-infarct-
damaged tissue before invading the bioscaffold. However, little is known about the route
or time-course of migration of these cells. The objective of this application is to develop a
non-invasive MR imaging paradigm that affords the tracking of neural progenitors from the
SVZ to the bioscaffold. Specifically, we here aim to: 1) develop and optimize contrast agent
to label endogenous neural progenitor cells, 2) to non-invasively track the migration of
neural progenitors and 3) to determine the temporal dynamics of neural progenitors
responding to a hydrogel implant. Achieving an in vivo visualization of neural progenitor
migrations will aid us to understand the contribution of neurogenesis to brain tissue
regeneration, but also to devise novel strategies that can manipulate this process.

## Key facts

- **NIH application ID:** 10428631
- **Project number:** 5R01NS122768-02
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Michel M. Modo
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $368,424
- **Award type:** 5
- **Project period:** 2021-07-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10428631

## Citation

> US National Institutes of Health, RePORTER application 10428631, MR Imaging of Bioscaffold-Induced Neural Progenitor Migration (5R01NS122768-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10428631. Licensed CC0.

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