# Minimizing Uncertainty in Breast Ultrasound Imaging with Real-Time Coherence-Based Beamforming

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2024 · $175,000

## Abstract

Administrative Supplement Application — NIH R01 EB032960 (PI: Bell)
Project Summary
Approximately 280,000 women are expected to be diagnosed with breast cancer in the United
States in 2021 and more than 40,000 will die from the disease. It is well documented that early
detection results in improved morbidity and mortality. Ultrasound imaging is an important
screening and diagnostic breast cancer detection tool, particularly for women with dense breasts
when mammography tends to be suboptimal. While suspicious findings may be clarified with
ultrasound imaging, a subset of ultrasound images yield inconclusive results, necessitating
biopsies or follow-up imaging, which increase patient anxiety and places additional burdens on
the time available for clinical care and the resource allocations of our healthcare system. One
reason for this outstanding challenge is that dense breasts tend to create images with significant
acoustic clutter, which confounds the differentiation of an otherwise anechoic mass (which is
indicative of a benign cyst) from a truly hypoechoic mass (which could be indicative of
malignancy). In addition, it can be difficult to distinguish a complicated cyst (which has internal
echoes due to proteinaceous material and is benign) from either a solid mass or a complex cystic
and solid mass (which could be malignant) using standard ultrasound imaging methods alone.
The objective of this proposal is to develop new, real-time ultrasound imaging technology that will
simplify clinical workflows by distinguishing fluid-filled masses from solid masses and from
complex cystic and solid masses, which each appear hypoechoic in traditional ultrasound B-mode
images. Our novel approach, Robust Short-Lag Spatial Coherence (R-SLSC) imaging, has
demonstrated feasibility to make this distinction by incorporating coherence-based beamforming
to augment existing beamforming methods available in clinical ultrasound scanners. Aim 1 will
focus on development of a real-time system for implementing matched B-mode and R-SLSC
imaging. Aim 2 will evaluate and compare real-time system performance. Aim 3 will assess the
ability of our novel methods to distinguish fluid from solid or complex cystic and solid masses
utilizing a combination of quantitative analyses and task-oriented reader studies.Aim 4 will
investigate advanced methods to retrieve coherence information and diagnostic information
regarding mass contents from ultrasound channel data, including recently discovered options that
rely on coherence lengths and lag-one coherence values without requiring reader input.
Successful completion of these aims will lead to a real-time, ultrasound-based tool to confidently
distinguish solid from fluid hypoechoic breast masses and provide a more simplified clinical
workflow for the most challenging of these cases. In addition, results from the proposed studies
will be applicable to clarifying the content of masses that may appear in multiple organs throughout
the huma...

## Key facts

- **NIH application ID:** 11093157
- **Project number:** 3R01EB032960-03S1
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Muyinatu A. Lediju Bell
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $175,000
- **Award type:** 3
- **Project period:** 2022-08-15 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11093157

## Citation

> US National Institutes of Health, RePORTER application 11093157, Minimizing Uncertainty in Breast Ultrasound Imaging with Real-Time Coherence-Based Beamforming (3R01EB032960-03S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/11093157. Licensed CC0.

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