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 Breast1 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.
75% pathologists improved efficiency
32.6% enhancement in consistency
AI integrated in your workflow
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
Note: Results shown in this page are based on an external clinical performance study performed at Radboud university medical center (Nijmegen, The Netherlands). This study involved 28 certified pathologists from 9 different countries, and it is being prepared for publication.
Improving mitosis counting for clinical diagnostics and biopharma
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.
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.