iSono Health today announced the commercial launch of ATUSA, an FDA-cleared, wearable, and automated 3D quantitative breast ultrasound platform.
The device is designed to help eliminate reliance on skilled sonographers and cost-prohibitive equipment.
ATUSA can fundamentally change the economics and accessibility of breast health through a unique fusion of wearable hardware and cloud-based intelligence:
- Automated Scanning: Utilizing a wearable, hands-free accessory, ATUSA captures full 3D volumes in approximately two minutes per breast, roughly 10x faster than manual handheld ultrasound. This ensures consistent and repeatable images are generated, regardless of the operator's skill level.
- Point-of-Care Integration: The system empowers OB/GYNs and primary care providers to offer specialist-level imaging directly in their offices, generating standardized 3D whole-breast visualization directly at the point of care.
- USaaS Business Model: A scalable "Ultrasound-as-a-Service" model that combines the wearable hardware, cloud-based AI, and consumables to create a recurring revenue stream while lowering the barrier to entry for local clinics.
- Advanced "Sentient" AI: iSono Health is working to move beyond simple detection toward a "sentient partner" model, where the system utilizes acoustic biomarkers and machine learning to sense patient-specific needs and provide real-time diagnostic support.
"ATUSA™ is a system-wide upgrade for women’s breast health," said Neda Razavi, CEO of iSono Health. "We are putting the power of a world-class radiology suite into the hands of local clinicians, replacing slow, manual workflows with real-time diagnostic images at the point of care."
The AUDIBLE Study: Validating the Future of Breast Health
A core pillar of the ATUSA launch is the initiation of the AUDIBLE Study, a pivotal multicenter clinical trial supported by a grant from the National Institutes of Health (NIH). This 800-patient study is designed to evaluate the diagnostic performance of the ATUSA platform compared to traditional mammography and MRI.
Key objectives of the AUDIBLE Study include:
- AI Products Validation: Assessing the performance of iSono’s machine-learning algorithms in identifying and classifying abnormal masses.
- Operator Independence: Proving that the automated, wearable hardware provides consistent, high-fidelity 3D volumes regardless of the user's clinical background.
- The study is being conducted at leading medical institutions, including UC Davis, Veda Trials (Axia Women’s Health), and City of Hope, ensuring the technology is vetted by the nation's top oncology and radiology experts.
