by
Gus Iversen, Editor in Chief | April 20, 2026
Lunit at RSNA 2025 Courtesy: Lunit
Lunit, the Seoul-based developer of AI software for cancer diagnostics, reported expanded clinical use of its breast imaging tools across the U.S. and outlined new regulatory clearance during the Society of Breast Imaging (SBI) Annual Symposium.
The company said its technologies are now deployed at more than 330 screening sites across the Americas, supporting roughly 1 million mammography exams each year. The figure reflects a shift from pilot programs to routine clinical use, as health systems integrate AI into standard workflows.
One example is Lexington Clinic, a Kentucky-based physician-owned multispecialty group with more than 350 providers. The organization has implemented Lunit’s breast imaging platform across multiple functions, including detection, risk assessment, breast density analysis, and workflow management. According to the clinic, consolidating these capabilities into a single system is intended to improve coordination and support earlier clinical decision-making.

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Lunit also pointed to adoption at Radiology Consultants of Iowa, where its digital breast tomosynthesis AI is used in daily reads. “After six months of using AI in our daily workflow, it’s become part of how we read,” said Robert J. Dolan, DO, breast imaging specialist at the practice. “It gives us added confidence, especially in subtle cases, and helps ensure we don’t miss what matters most.”
Separately, the company announced that version 1.2 of its 3D mammography algorithm has received clearance from the U.S. Food and Drug Administration. The updated software includes functionality to compare current exams with up to two prior studies, and allows users to select from multiple operating thresholds that balance sensitivity and specificity. It also incorporates volumetric breast density data alongside AI-generated findings.
The updates reflect ongoing efforts by imaging vendors to adapt AI tools for routine use, with greater emphasis on configurability and integration into existing clinical workflows.