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Aiosyn Mitosis Breast Becomes the First AI-Powered Mitosis Detection Solution to Achieve CE Mark Certification Under IVDR

Aiosyn, a pioneering innovator in AI-powered pathology software for cancer and kidney disease, has announced that its algorithm for mitotic figure counting has achieved CE marking under the In Vitro D...

Business Wire

NIJMEGEN, Netherlands: Aiosyn, a pioneering innovator in AI-powered pathology software for cancer and kidney disease, has announced that its algorithm for mitotic figure counting has achieved CE marking under the In Vitro Diagnostic Regulation (IVDR) for use in diagnostics. This milestone establishes Aiosyn Mitosis Breast as the first IVDR-certified application for mitosis counting in breast cancer diagnostics and accelerates the company’s growth in clinical pathology.

Breast cancer is the most common cancer among women, with 2.3 million new cases diagnosed annually worldwide¹, including 604,900 in the WHO Europe region in 2022². Despite significant advancements that have reduced mortality rates in recent decades, breast cancer remains the leading cause of cancer-related death among women in Europe and globally. This underscores the urgent need for precision diagnostic tools like Aiosyn Mitosis Breast, which enhances grading reproducibility and supports personalized treatment strategies. By improving diagnostic consistency, the solution ensures optimal outcomes for patients and helps address the challenges of modern breast cancer care.

“CE-IVDR certification is setting a new benchmark for quality and safety in medical devices, including those powered by AI,” said Wouter Bulten, Chief Operating and Product Officer at Aiosyn. “The regulation ensures that devices undergo rigorous validation and meet the highest clinical and safety standards, raising the bar for innovation in pathology. Achieving this certification reflects our dedication to delivering trusted tools that enhance consistency, efficiency, and diagnostic confidence in breast cancer care.”

Aiosyn Mitosis Breast uses deep learning to detect cell division in whole slide images, saving pathologists time in this tedious and subjective task required for breast cancer grading. Mitotic count is not only critical for accurate tumor grading but also serves as an important prognostic indicator in breast cancer, helping guide treatment decisions. By standardizing grading assessments, the solution improves diagnostic consistency and aids in selecting appropriate treatments for patients. Supporting diagnoses with efficient tools such as Aiosyn’s is also critical in addressing the global shortage of pathologists in healthcare, which is continuously leading to increased workloads and diagnostic delays.

The algorithm was trained on extensive datasets from multiple pathology laboratories worldwide and validated in a multi-center clinical performance study conducted by Radboud University Medical Center. The study demonstrated that pathologists using the algorithm achieved:

  • Up to 60% time savings per slide;
  • 15% average increase in productivity;
  • And a 32.6% improvement in consistency

With over 90% of surveyed clinical study participants interested in incorporating the algorithm into their daily workflow and several integrations already planned, Aiosyn Mitosis Breast is poised to bring these benefits to pathology practice.

“We look forward to partnering with pathology laboratories and demonstrating its added value for breast cancer grading,” said Patrick de Boer, CEO of Aiosyn.

The application integrates with existing digital pathology software and can be deployed via cloud-based or on-premise installations, offering adaptability to diverse laboratory environments. To learn more about Aiosyn Mitosis Breast and opportunities to join a pilot program, contact Aiosyn at contact@aiosyn.com.

About Aiosyn

Based in the Netherlands, Aiosyn develops precision pathology software for breast cancer and kidney disease, integrating its solutions into standard pathology workflows. Aiosyn has been built upon more than 20 years of research experience in the field of pathology and is rooted in pathology practice.

Sources

  • https://www.who.int/news-room/fact-sheets/detail/breast-cancer
  • https://www.europadonna.org/breast-cancer/#ref
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    Fonte: Business Wire

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