AI system improves breast cancer staging
The new AI tech offers a cheap and dependable way to predict disease progression.
Researchers at the Paul Scherrer Institute (PSI) and the Massachusetts Institute of Technology (MIT) have developed an AI system to improve the categorisation of breast cancer. The new technology, led by G.V. Shivashankar from PSI and Caroline Uhler from MIT, aims to provide a reliable and cost-effective method for predicting the progression of ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC).
DCIS, a precursor of breast cancer in the milk ducts, accounts for about 25% of breast cancer diagnoses. It can develop into a threatening invasive form in 30 to 50% of cases. The AI system, trained on tissue samples stained with DAPI dye, analyses chromatin images to identify patterns matching those identified by human pathologists. This approach leverages AI’s potential, as highlighted by research in Lancet Digital Health showing AI outperforming radiologists in breast cancer detection.
The researchers believe this AI-based tumour classification method has significant potential, though further studies are necessary to ensure its reliability and safety. The US Department of Defense (DoD) has been using AI to detect cancer since 2020, showcasing the growing role of AI in medical diagnostics. The new system developed by PSI and MIT could lead to more accurate predictions and better treatment decisions for patients.
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