# ATUSA: World's First Wearable and Automated 3D Breast Ultrasound System with AI

> **NIH NIH R44** · ISONO HEALTH, INC. · 2024 · $1,043,109

## Abstract

PROJECT SUMMARY
Breast cancer (BC) is a formidable global health challenge, affecting millions of women worldwide annually. This
malignancy is a leading cause of death among women, underscoring its profound significance. Detecting BC at
an early stage not only improves treatment outcomes but also significantly enhances survival rates. Currently,
mammography is the standard of care for diagnosis of BC, and it is recommended that screening procedures
commence at the age of 40, particularly due to the rising incidence of BC in women who are under the age of
50. Although mammography decreases BC-associated mortality, there exist distinct challenges with
mammography alone for general population screening. For example, there is often inadequate healthcare
accessibility for certain populations that exist due to socioeconomic disparities. BC mortality is heightened for
Black women relative to White women, which is attributed to lack of access to regular screening, earlier age of
disease incidence, and higher rates of triple-negative breast cancer. Inaccessibility of mammography to rural
populations and a fear of painful mammogram experience also contribute to the lack of timely BC diagnosis in
underrepresented populations. Screening mammography also exhibits inherent sensitivity limitations and often
misses BC at earlier stages, especially for women with dense breasts, who comprise approximately 47% of
women in the U.S. It is thus recommended that women with dense breasts upon mammographic exam undergo
supplemental screening procedures such as ultrasound or MRI. Unfortunately, these imaging procedures are
expensive and/or dependent upon the availability of specially trained breast sonographers and are not widely
available to underserved populations. There is thus an urgent need for the development of innovative screening
methods that facilitate BC detection in nascent stages and that are also deployable to the primary care setting
and can be operated independent of user experience level. To address these problems, iSono Health has
developed the ATUSA imaging platform, which represents a major advancement in supplemental BC screening.
This novel system consists of an adjustable wearable imaging device that can rapidly perform whole breast
scans in ~2 minutes coupled with artificial intelligence (AI)-assisted algorithms that accurately identify and
diagnose BC at an early stage. The goal of this Direct-to-Phase II proposal is to develop and validate Lesion
Classification, Lesion Segmentation, and Density Calculator AI models for 3D ATUSA images. Successful
outcomes of this project will establish baseline measures of the ATUSA diagnostic performance. Validation
results will allow iSono Health to submit a second FDA clearance of AI indications and commercially launch
ATUSA. The ATUSA platform will transform how women access supplemental breast imaging and increase the
number of women receiving adequate breast imaging and timely diagnosis, thus saving lives.

## Key facts

- **NIH application ID:** 10922543
- **Project number:** 1R44CA291498-01
- **Recipient organization:** ISONO HEALTH, INC.
- **Principal Investigator:** Shadi Saberi
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,043,109
- **Award type:** 1
- **Project period:** 2024-09-06 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10922543

## Citation

> US National Institutes of Health, RePORTER application 10922543, ATUSA: World's First Wearable and Automated 3D Breast Ultrasound System with AI (1R44CA291498-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10922543. Licensed CC0.

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