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Volpara is now Lunit. Meet us at RSNA 2025 and discover our unified AI-powered breast ecosystem. Book an appointment.

SecondReadAITM is an AI-powered second analysis of mammography images that is proven to provide incredible benefits:

  1. Earlier detection: identifies 15% more cancers over mammography alone. (MMG)
  2. Enhances screening accuracy: detects 1 additional cancer for every 10 found by radiologists. (DBT)
  3. Reliable in dense breasts: Achieves 89% sensitivity in dense breast tissue. (MMG)
  4. More confidence to biopsy: Boosts diagnostic accuracy up to 5% in dense breasts and 12% in fatty breasts. (MMG)
  5. Significantly less false positives to traditional CAD: Reduces false-positive marks by 95%. (MMG)
  6. Accelerates radiologist’s analysis: Reduces reading time by 13%, supporting faster, more efficient workflows. (MMG)

References:

1, 3. Hyo Eun Kim, et al., Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multi reader study, The Lancet Digital Health, 2020

2. Eun Kyung Park, et al., Impact of AI for Digital Breast Tomosynthesis on Breast Cancer Detection and Interpretation Time, Radiology: Artificial Intelligence 2024; 6(3):e230318 • https://doi.org/10.1148/ryai.230318.

4. Lehman CD, Arao RF, Sprague BL, Lee JM, Buist DS, Kerlikowske K, et al. National performance benchmarks for modern screening digital mammography: update from the Breast Cancer Surveillance Consortium. Radiology 2017;283:49-58

4. Kim YS, Jang MJ, Lee SH, Kim SY, Ha SM, Kwon BR, Moon WK, Chang JM. Use of Artificial Intelligence for Reducing Unnecessary Recalls at Screening Mammography: A Simulation Study. Korean J Radiol. 2022 Dec;23(12):1241-1250. doi: 10.3348/kjr.2022.0263. PMID: 36447412; PMCID: PMC9747265.

5. Lee, Si Eun, et al., Comparison of conventional CAD and AI-CAD applied to digital mammography in respect of false-positive marks, Journal of the Korean Society for Breast Screening, 2020

6. Karin Dembrower, et al., Effect of Artificial Intelligence-based Triaging of Breast Cancer Screening Mammograms on Cancer Detection and Radiologist Workload: A Retrospective Simulation Study, The Lancet Digital Health, 2020

This AI software cannot guarantee breast cancer detection with 100% accuracy.