# B7-H3 Targeted Ultrasound Molecular Imaging System for Early Breast Cancer and Metastatic Detection

> **NIH NIH R01** · STANFORD UNIVERSITY · 2024 · $555,002

## Abstract

ABSTRACT
Breast cancer is the second leading cause of cancer-related deaths in women in the United States, and its
incidence is expected to grow by more than 50% by 2030. If detected early, the survival of women can be
substantially increased compared to late-stage detection. Ultrasound molecular imaging, using molecularly-
targeted contrast microbubbles, is a promising technique for the early detection of breast cancer, particularly in
women with radiographically dense breast. In ultrasound molecular imaging, a molecularly-targeted ligand
attached to a microbubble can bind to proteins expressed on the tumor neovasculature and produce contrast
that can identify cancer early. This approach has large potential for improving the diagnostic accuracy of
ultrasound and noninvasive characterization of focal breast lesions. The keys to successful ultrasound molecular
imaging in this regard are: (1) having a molecular target that is highly specific to breast cancer, and (2) having a
sensitive imaging system that can correctly visualize the microbubbles bound to breast cancer and differentiate
those bubbles from background tissue. In addition, the system must integrate well with existing ultrasound
imaging technology so as to be practically distributable to existing breast imaging clinics.
In this application, we propose to build a real-time ultrasound molecular imaging platform that consisting of a
novel ultrasound contrast imaging technology that is targeted to a newly identified biomarker of breast cancer.
We propose to utilize targeted microbubbles to enhance the contrast signal and improve the sensitivity of the
imaging system and propose to conjugate these microbubbles with a high-affinity affibody targeted to the B7-H3
biomarker, which is a vascular biomarker highly specific to breast cancer, and is not expressed in benign disease
processes. In addition, our preliminary results demonstrate that this biomarker may potentially allow for the
detection of metastatic disease at the time of imaging, potentially enabling the ability to image the extent of
metastatic disease prior to treatment decisions. The real-time imaging technology in this proposal is based on a
neural network design for contrast imaging that requires low computational resources and avoids destruction
of bubbles, and enable real-time imaging of the targeted contrast agent. During this project, we will optimize the
ultrasound parameters of these B7-H3 targeted microbubbles for breast ultrasound imaging frequencies and will
utilize conjugation chemistry for the microbubbles to permit the potential for future clinical translation of the B7-
H3-targeted microbubbles. We will design and construct this ultrasound molecular imaging platform (non-
destructive imaging system plus monodisperse B7-H3-targeted microbubbles) and thoroughly test it in
phantoms, in vitro flow chambers, and several preclinical animal models of primary and metastatic breast cancer.

## Key facts

- **NIH application ID:** 10810672
- **Project number:** 5R01EB031799-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Jeremy Dahl
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $555,002
- **Award type:** 5
- **Project period:** 2023-04-01 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10810672

## Citation

> US National Institutes of Health, RePORTER application 10810672, B7-H3 Targeted Ultrasound Molecular Imaging System for Early Breast Cancer and Metastatic Detection (5R01EB031799-02). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10810672. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*