From Scan to Treatment Plan, AI Helps Close Breast Cancer’s Deadliest Gaps
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Breast cancer is the most commonly diagnosed cancer among American women, yet the gaps in care are wide.
Key facts
- The system’s AI, trained on thousands of full-breast scans comprising over 1.5 million ultrasound frames, automates image acquisition
- The company has a multicenter clinical study with 3,200 patients underway to further validate the platform’s performance, with lead research sites at UC Davis and Vanderbilt University Medical Center
- The company’s FDA-cleared ATUSA platform, a wearable, automated 3D quantitative ultrasound system, captures a standardized breast volume in approximately two minutes per breast, compared with up
- Another NVIDIA Inception company, SimBioSys, joined NVIDIA on a recent panel marking Breast Cancer Awareness Month
Summary
Companies in the NVIDIA Inception program for startups are building AI applications to support clinicians at each of these friction points, including imaging, risk assessment and treatment planning. About 40 million mammograms are performed in the U.S. each year, but a projected shortfall of tens of thousands of radiologists over the next decade is straining the system’s capacity to read them. At the other end of the care timeline, treatment decisions often hinge on genomic assays sent off to outside labs, assays that take weeks to process, at a moment when speed and certainty matter most. The companies below are addressing both ends of that gap, and everything in between, accelerated by NVIDIA AI infrastructure.