# MRI Diffusion in Tumors using Oscillating Gradients

> **NIH NIH R01** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2020 · $300,200

## Abstract

Abstract / Summary
 This revised competitive renewal seeks to extend the technical developments of the previous funding
 period to validate and apply a novel diffusion-based MR imaging technique, quantitative temporal diffusion
 spectroscopy (qTDS), that provides unique information on tissue microstructure and in particular can reveal
early changes in tumors after treatment. In the previous cycle we developed this innovative method and
 showed it is a sensitive indicator of changes in cell dimensions and tissue microstructure such as those that
 occur with cell division and during apoptosis, before frank changes occur in cell density or tumor volume. As
 such, qTDS has considerable potential for assessing whether specific treatment regimens are working, and so
 may inform the selection of optimal therapies for patients and the reduction of avoidable side-effects. QTDS is
 based on measurements of water diffusion rates over different time scales corresponding to different spatial
 dimensions. We have previously shown it can detect changes in intracellular structure and cell sizes and
 density, in cell cultures and in animal models, early in the course of a treatment and without some of the
 confounding factors that affect other diffusion techniques, such as changes in cell membrane permeability. We
 have performed theoretical analyses, computer simulations, and cell and in vivo animal studies, to understand
 the factors that affect qTDS measurements, and have implemented the first practical qTDS acquisitions on a
 human 3T scanner. In the current proposal we aim to extend our previous work and use qTDS as an in vivo
imaging technique for non-invasive characterization of specific cellular changes which are currently
 assessable only via invasive biopsy. We propose to validate qTDS in cell and animal models of cancer, and
determine whether qTDS is capable of detecting treatment-induced cell size changes early in specific
therapeutic regimens. We also propose to translate qTDS clinically by demonstrating its performance in
predicting neoadjuvant treatment response in breast cancer. We hypothesize that qTDS is capable of
 characterizing the distinct cellular changes associated with treatment-induced apoptosis, thereby providing an
 innovative and unique means of assessing tumor response at an early stage of therapy. Our specific aims are:
 [i] in a transgenic mouse model of breast cancer, we will quantitatively map tumor cell size and density in vivo,
 and validate the qTDS derived parameters on a voxel by voxel basis using using quantitative, co-registered
 histology: [ii] in mouse models of breast cancer treated by different targeted drugs, we will evaluate qTDS as
an imaging biomarker capable of detecting treatment-induced apoptosis and predicting treatment efficacy
 early during therapy: [iii] In human breast cancer patients, we will evaluate qTDS as an imaging biomarker for
 assessing breast tumor early response to neoadjuvant chemotherapy and pr...

## Key facts

- **NIH application ID:** 9830018
- **Project number:** 5R01CA109106-14
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Junzhong Xu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $300,200
- **Award type:** 5
- **Project period:** 2006-03-15 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9830018

## Citation

> US National Institutes of Health, RePORTER application 9830018, MRI Diffusion in Tumors using Oscillating Gradients (5R01CA109106-14). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9830018. Licensed CC0.

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