# Dedicated breast PET and MRI for characterization of breast cancer and its response to therapy

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2021 · $580,052

## Abstract

PROJECT SUMMARY/ABSTRACT
The objective of this academic-industrial partnership (AIP) project is to demonstrate the utility of dedicated
breast positron emission tomography (dbPET) for characterizing primary breast cancers and their response to
neoadjuvant chemotherapy (NAC). While dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)
depicts changes in tumor morphology and vascularity in response to NAC, dbPET provides complementary
information about tumor metabolism that can powerfully predict treatment response earlier in the course of
therapy. We focus this project on MAMMI dbPET by OncoVision because it provides the crucial combination
of high spatial resolution and sensitivity that can enable accurate intratumoral mapping of metabolic changes in
small lesions with only half the radiotracer dose of whole-body PET. Importantly, this new system scales PET
technology to be both economically and clinically feasible in the early (pre-metastatic) breast cancer setting. As
the imaging lead (PI: Nola Hylton) of the I-SPY 2 TRIAL, a clinical trial designed to identify novel therapeutics
for breast cancer, we are in a unique position to integrate and test the performance of FDG-dbPET as an early
marker for treatment response. As academic-industrial partners, UCSF and OncoVision will work together to
develop a user-friendly and cost-effective dbPET technology that can be easily adopted into the clinical
workflow of most breast cancer centers. In Specific Aim 1, we will develop software capabilities to standardize
dbPET image registration and quantification to accurately quantify longitudinal changes with treatment. In
Specific Aim 2, we will acquire pre- and post-treatment FDG-dbPET images of a subset of I-SPY 2 patients
and clinically evaluate whether tumor metabolic metrics (i.e., optimized standardized uptake values, SUV) from
dbPET can act as early predictors of pathologic complete response — in comparison to, and in combination
with, the functional tumor volume (FTV) metric from DCE-MRI. We will test the biomarker performance of
dbPET SUV and combined SUV+FTV using logistic regression predictive models. We will also explore the
association of dbPET and DCE-MRI radiomic features with breast cancer biomarkers in order to identify
imaging features with prognostic value. In addition, our prospective study’s dbPET data will be used to
evaluate the software capabilities developed in Specific Aim 1. We expect the successful completion of this
AIP project to enable the use of MAMMI dbPET in routine breast cancer management and to produce a set of
imaging biomarkers relevant to tumor biology and its change in response to treatment.

## Key facts

- **NIH application ID:** 10092115
- **Project number:** 5R01CA227763-03
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Nola M. Hylton-Watson
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $580,052
- **Award type:** 5
- **Project period:** 2019-02-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10092115

## Citation

> US National Institutes of Health, RePORTER application 10092115, Dedicated breast PET and MRI for characterization of breast cancer and its response to therapy (5R01CA227763-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10092115. Licensed CC0.

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