# Multicenter Quantitative MRI Assessment of Breast Cancer Therapy Response

> **NIH NIH R01** · OREGON HEALTH & SCIENCE UNIVERSITY · 2021 · $624,828

## Abstract

Project Summary
Quantitative imaging of tumor biological functions have been shown superior to imaging tumor size for
prediction and evaluation of cancer response to therapy. Conventionally used as a noninvasive imaging
method to assess microvascular perfusion and permeability, dynamic contrast-enhanced (DCE) MRI is
increasingly employed in research and early phase clinical trial settings to measure and, importantly, predict
tumor response to treatment. The standard two- or three-parameter Tofts models (TMs) are the most
commonly used for pharmacokinetic (PK) modeling of DCE-MRI data to estimate quantitative imaging
biomarkers such as Ktrans and ve. However, the TM is suboptimal in that it ignores the real physiological
phenomenon of water exchange between tissue compartments when quantifying tissue concentration of
contrast agent from MRI signal intensities. The Shutter-Speed Model (SSM) developed by the Oregon Health
& Science University (OHSU) group is a more comprehensive PK model, taking into account the
intercompartmental water exchange kinetics. Recent single-center OHSU studies have demonstrated superior
ability of SSM DCE-MRI for prediction and evaluation of therapy response in breast cancer compared to the
TM. Furthermore, it was recently discovered that the SSM-exclusive parameter, τi (mean intracellular water
lifetime), is a new imaging biomarker of metabolic activity, and was the only baseline (pre-treatment) marker
predictive of response to neoadjuvant chemotherapy (NAC) in breast cancer and overall survival in head and
neck cancer. τi also has the advantage of being significantly less sensitive to variation in arterial input function
(AIF) than the conventional PK parameters. Using the data acquisition and analysis protocols optimized by the
OHSU group, the overall goal of this project is to validate the robustness of SSM DCE-MRI as a quantitative
imaging tool for assessment of cancer therapy response in a prospective study under a multicenter setting
across three major MRI scanner platforms, using NAC treatment of breast cancer as the testing clinical
application. Specifically, we will (1) implement the optimized SSM DCE-MRI data acquisition and analysis
protocols and perform QA/QC in a multicenter setting; (2) conduct the multicenter prospective study to validate
the utility of SSM DCE-MRI for prediction and evaluation of breast cancer response to NAC; and (3) refine an
OHSU-developed web-based clinical decision support system by developing and incorporating a predictive
model of therapy response that integrates imaging markers with clinical and histopathological data, and
evaluate the system adaptability in clinical workflow.

## Key facts

- **NIH application ID:** 10120157
- **Project number:** 1R01CA248192-01A1
- **Recipient organization:** OREGON HEALTH & SCIENCE UNIVERSITY
- **Principal Investigator:** WEI HUANG
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $624,828
- **Award type:** 1
- **Project period:** 2020-12-01 → 2025-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10120157

## Citation

> US National Institutes of Health, RePORTER application 10120157, Multicenter Quantitative MRI Assessment of Breast Cancer Therapy Response (1R01CA248192-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10120157. Licensed CC0.

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