Lunit, a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, announced a landmark achievement at the European Congress of Radiology (ECR) 2025, taking place in Vienna, Austria, from February 26 to March 2. With 15 research abstracts accepted and 13 designated as oral presentations, this year’s participation marks Lunit’s largest and most influential presence at ECR to date. 

The high acceptance rate underscores Lunit’s growing leadership in AI-driven radiology, with its research recognized as highly relevant to the future of cancer screening and detection. Among the featured studies, two highlight groundbreaking findings that further solidify Lunit INSIGHT MMG as a clinically proven tool in mammography interpretation and workflow optimization. 

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Replacing One Radiologist with AI for Independent Double Reading in Mammographic Screening

Presented by Marie Burns Bergan from BreastScreen Norway, this study evaluates the impact of replacing one radiologist with Lunit INSIGHT MMG in a large-scale double-reading mammography screening program. The research analyzed over 1 million mammography screenings, testing various AI thresholds to assess AI’s role in maintaining detection accuracy while reducing radiologists’ workload. 

Key findings include:

  • AI successfully detected up to 79.9% of screen-detected cancers at a 10% positivity threshold.
  • At a 5% threshold, AI maintained 75.5% cancer detection while also identifying 5.7% of interval cancers, which are often missed by traditional screening.
  • AI integration reduced radiologists’ reading workload by 50%, optimizing resources without significantly compromising detection accuracy. 

This study highlights Lunit INSIGHT MMG’s ability to serve as a reliable second reader, supporting AI’s role in improving efficiency and alleviating radiologist shortages in high-volume screening programs. 

Using Artificial Intelligence to Detect Subclinical Breast Cancer

Led by Jonas Gjesvik from BreastScreen Norway, this study investigates whether Lunit INSIGHT MMG can identify subtle cancer risk indicators years before a formal diagnosis. The analysis involved 116,000 women who participated in a long-term mammography screening program, assessing AI’s ability to assign risk scores and track disease progression. 

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Key findings include: 

  • AI assigned higher risk scores to breasts that later developed cancer, even up to six years before diagnosis.
  • AI scores for screen-detected breast cancers increased significantly from 19.2 to 82.7 across consecutive screenings, indicating early disease detection. 
  • For interval cancers, AI identified elevated risk earlier than traditional methods, paving the way for more personalized screening strategies. 

The study underscores AI’s potential to enhance breast cancer risk prediction, shifting screening protocols toward a personalized, risk-based model. This research aligns with ongoing work leveraging Volpara’s breast density analysis, further strengthening the Lunit-Volpara ecosystem in AI-driven breast cancer risk assessment. 

In addition to these highlighted studies, Lunit will present a total of 15 research abstracts, further demonstrating AI’s role in enhancing diagnostic accuracy, optimizing workflow, and supporting radiologists worldwide. 

“This year’s ECR is a landmark moment for Lunit, with our highest-ever number of oral presentations, underscoring our leadership in AI-powered radiology research,” said Brandon Suh, CEO of Lunit. “From replacing a radiologist in double-reading settings to predicting breast cancer years in advance, these findings reinforce AI’s potential to transform breast cancer detection, optimize radiology workflows, and ultimately improve patient outcomes.”

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Source – PR Newswire

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