Mitotic figure counting

We provide an AI-powered solution to aid clinical and research labs with the identification of mitotic figures in H&E sections.

The manual process is time-consuming and subject to variability, and there is a need for solutions to increase its efficiency and consistency of results. Aiosyn Mitosis Breast [1] uses deep learning to detect mitosis in whole slide images, saving pathologists time and providing laboratories with a more standard process for assessing tumor growth.

1. Aiosyn Mitosis Breast, for use in clinical diagnostics, is undergoing CE-mark certification under the EU IVDR. In addition to Aiosyn Mitosis Breast, we offer Aiosyn Mitosis Research for Research Use Only.

Analysis of Aiosyn Mitosis Breast

Mitotic figures in an H&E stained slide image are identified and highlighted with Aiosyn Mitosis Breast. The deep learning algorithm detects cells undergoing division (mitosis) in whole slide images before the cases are opened for review.

75% pathologists improved efficiency

The algorithm helps laboratories improve the process of mitosis analysis. In a clinical performance study, 75% of participating pathologists were faster when supported by Aiosyn Mitosis Breast.

32.6% enhancement in consistency

Aiosyn Mitosis Breast has been shown to reduce variability among observers, leading to a 32.6% improvement in consistency between pathologists.

AI integrated in your workflow

Aiosyn Mitosis Research and Aiosyn Mitosis Breast are offered as a modular software solution that can be integrated into existing workflows, removing the need to adopt a different viewer.

Your workflow with Aiosyn Mitosis Breast

Our AI-powered solutions can be integrated with major workflow providers such as Sectra. Slides are prepared as usual, and the algorithm analyzes images once uploaded to the platform.

Over 90% of surveyed pathologists who tried Aiosyn Mitosis Breast would like to use the algorithm in their daily practice.

“I am delighted that we finalized the clinical validation study for Aiosyn Mitosis Breast with Radboudumc. It was an immense project with 28 pathologists from 9 countries participating. Great to see how AI can benefit pathologists in a real clinical setting!”

Wouter Bulten, Chief Innovation Officer of Aiosyn

Aiosyn Mitosis Breast for clinical diagnostics
Aiosyn Mitosis Research for biopharma

Aiosyn Mitosis Breast assists pathologists in detecting mitotic figures in whole slide images of breast biopsies and resections. Mitoses are detected and highlighted by the algorithm before the pathologist opens the WSI, thereby indicating areas with mitotic activity and assisting in the quantification.

In a clinical performance study, 75% of participating pathologists were faster when supported by Aiosyn Mitosis Breast. On average, pathologists showed a 15.5% increase in productivity when reviewing resections. Additionally, the algorithm lead to a 32.6% improvement in consistency between pathologists

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Aiosyn Mitosis Research aids research labs with the identification of mitotic figures in H&E sections. With improved and reproducible detection, new biomarkers can be discovered and researched more accurately.

Automated whole-slide level assessment enables the processing of caseloads that would not be possible with human annotators. By streamlining the process, Aiosyn Mitosis Research can assist laboratories in adopting a more consistent and efficient protocol for the identification of novel pathology-based biomarkers, resulting in improved and standardized results.

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