Employing Lunit INSIGHT MMG, a Turkish study showcases 70% efficiency improvements, advancements in early cancer detection, and interval cancer detection in mammography
SEOUL, South Korea, April 8, 2024 -- Lunit (KRX:328130.KQ), a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, today announced the publication of a new study, highlighting the effectiveness of Lunit INSIGHT MMG in significantly reducing radiologists' workload while enhancing cancer detection rates.
Conducted in collaboration with researchers from Acibadem Mehmet Ali Aydinlar University, Marmara University, Namik Kemal University, and Istanbul University, Türkiye, the study result was recently published in European Radiology, the flagship journal of the European Society of Radiology (ESR).
This comprehensive study encompassed over 22,621 mammograms from 8,825 women over a decade. Utilizing Lunit INSIGHT MMG, Lunit's AI-powered solution for breast cancer detection, the research aimed to assess its proficiency in early cancer detection within a breast cancer screening program.
At a glance
- Company
- Lunit
- Ticker
- KRX: 328130.KQ
- Location
- Seoul, South Korea
Key figures
- Mammograms studied
- over 22,621
- Women included
- 8,825
- Potential workload reduction
- nearly 70%
- Increase in cancer detection accuracy
- 30.5%
- Interval cancers identified
- 51.72%
- Missed cancers identified
- 50%
People
- Brandon SuhCEO of Lunit
Products and programs
A pivotal finding of the study is Lunit INSIGHT MMG's potential to reduce workload by nearly 70% through a hybrid workflow scenario that categorizes mammograms into immediate review, further evaluation, or no action needed based on AI-assessed risk scores, alongside a 30.5% boost in cancer detection accuracy. This indicates a substantial step forward in improving the efficiency of breast cancer screening programs, potentially enabling broader screening coverage and reducing the burden on healthcare systems.
The study further revealed that the AI system identified 51.72% of interval cancers, and 50% of missed cancers. Additionally, the study illustrated that using Lunit INSIGHT MMG as a second reader could potentially expedite the diagnosis by an average of nearly 30 months, compared to traditional screening methods.
"This study not only reaffirms Lunit INSIGHT MMG's efficacy in detecting breast cancer early but also illuminates its impact on operational efficiency and economic value within healthcare systems," said Brandon Suh, CEO of Lunit. "For years, most of the conversation around AI in medical diagnostics has centered on its medical efficacy. However, this research showcases how AI can streamline workflows, reduce the radiological burden, and potentially offer significant cost and time savings. As we move forward, our focus will be on harnessing these dual benefits of AI - enhancing medical outcomes while also driving economic efficiency. We'll expand our research and development efforts to further integrate AI in ways that not only maximize the quality of care but also the sustainability of healthcare systems."
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In brief
Lunit says a study published in European Radiology examined its INSIGHT MMG breast cancer detection system using mammograms from a Turkish screening program. The company reports that an AI-supported workflow could reduce radiologists’ workload by nearly 70%, while cancer detection accuracy increased by 30.5%. The study also found that the system identified 51.72% of interval cancers and half of missed cancers. As a second reader, the AI could potentially bring diagnosis forward by an average of nearly 30 months compared with traditional screening methods, according to the release. The research covered more than 22,621 mammograms from 8,825 women over a decade and involved researchers at universities in Türkiye. Lunit CEO Brandon Suh said the findings address workflow efficiency as well as medical outcomes.
Key takeaways
- Lunit says its AI-supported workflow could lower radiologists’ workload by nearly 70%.
- The company reports a 30.5% increase in cancer detection accuracy in the study.
- The system identified 51.72% of interval cancers and 50% of missed cancers.
- The study examined more than 22,621 mammograms from 8,825 women over a decade.
Earlier from Lunit
- Lunit to Showcase 7 Studies at AACR 2024: Unveiling AI Innovations in HER2 Expression-Mutation Analysis and CNTN4 Biomarker Identification
- Update on Lunit's Acquisition of Volpara: New Zealand High Court Initial Approval Secured
- Lunit Expands AI Medical Imaging Solutions in East & Southeast Asia: Partners with Chung Shan Medical University and Gleneagles Hospital Singapore
- Lunit Presents Seven Study Results at ECR 2024: Showcasing AI's Robust Performance in Diverse Clinical Settings
- New Study Demonstrates Predictive Value of Lunit SCOPE IO to Predict Outcomes of Immune Checkpoint Inhibitor Therapy Across Diverse Tumors - published in the JITC
