Aiforia Breast Cancer Suite

Aiforia® Breast Cancer Suite is a comprehensive AI-powered solution designed to support pathologists in breast cancer diagnostics. The suite combines a set of advanced AI models with an optimised interactive user interface, enabling histological grading of breast cancer and objective assessment of key immunohistochemistry (IHC) biomarkers. It is intended for pathology laboratories seeking to enhance precision, speed, and diagnostic consistency across the full breast cancer diagnostic workflow.

All AI models within Aiforia® Breast Cancer Suite are CE-IVD marked for diagnostic use in EU and EEA countries under IVDR, and are available for Research Use Only (RUO) and Performance Studies Only (PSO) in all other market areas.

AI Models Included in the Suite

• Aiforia® Breast Cancer Grading: Automates histological grading from H&E-stained whole-slide images (WSI), accurately identifying invasive carcinoma and ductal carcinoma in situ (DCIS). Objectively scores mitotic count, tubular formation, and nuclear pleomorphism in line with the Nottingham Grading System, reducing grading time by 50%, delivering high correlation with expert assessments, and consistently reducing interobserver variability.
• Aiforia® Breast Cancer ER: Automatically detects invasive carcinoma and quantifies oestrogen receptor (ER)-positive and negative tumour cells from WSI or selected tissue areas. Delivers exceptional diagnostic accuracy, improved consistency, and up to 47% faster ER scoring compared to manual methods.
• Aiforia® Breast Cancer PR: Automatically detects invasive carcinoma and quantifies progesterone receptor (PR)-positive and negative cells from WSI or selected tissue regions. Provides high diagnostic confidence, near-perfect reproducibility, and approximately 12% faster scoring.
• Aiforia® Breast Cancer HER2: Accurately identifies invasive carcinoma and scores HER2 expression in alignment with CAP guidelines. Offers outstanding sensitivity and precision for HER2 classification, enhanced interobserver concordance, and objective support for identifying challenging HER2-low and HER2-ultralow cases.
• Aiforia® Breast Cancer Ki67: Automatically detects invasive carcinoma and quantifies Ki67-positive and negative tumour cells from WSI or targeted image regions. Features automated hotspot detection for accurate proliferation assessment, high correlation to expert visual scoring, and reduces scoring duration by up to 54%.
• Aiforia® Lymph Node Metastasis: Automatically detects and quantifies breast cancer metastases in WSI of lymph node biopsies. Demonstrates excellent correlation with visual diagnosis and delivers up to 40% time savings at the slide level.

Key Platform Capabilities

• Comprehensive AI toolkit: Covers the full spectrum of breast cancer histological grading and biomarker detection, providing a fully digital cockpit for the entire diagnostic workflow.
• Transparent and adjustable results: Delivers pixel-level results at the highest resolution, improving repeatability and traceability while giving pathologists full control over outcomes.
• High lifetime value: AI models are designed to evolve with the laboratory's needs, ensuring consistent accuracy and flexibility throughout their lifecycle.
• Seamless two-way integration: Easily integrates with existing laboratory information and digital pathology systems.

Clinical Performance Highlights Across the Suite

• Up to 54% reduction in scoring time for Ki67, 50% for grading, 47% for ER, and 40% for lymph node metastasis detection
• Consistently high correlation with expert pathologist assessments across all models
• Reduced interobserver variability and improved diagnostic concordance throughout the workflow
• Objective support for emerging diagnostic challenges such as HER2-low and HER2-ultralow classification

Aiforia® Breast Cancer Suite is suitable for clinical pathology laboratories operating within the EU and EEA under IVDR, as well as research and performance study settings globally. The suite supports integration with a range of digital slide scanners and existing laboratory systems, making it adaptable to diverse pathology environments.