Morph.ai

Digital pathology platform that uses deep learning to transform the assessment of breast cancer for pathologists.

Problem

We have shown that systemic immune responses in lymph nodes (LN)  convey significant prognostic value for breast cancer patients and we want to improve the current pathological profiling of a patients breast cancer prognosis by extending the current TNM  staging (cancer detection) used by pathologists to include the LN immune response.  To enable an efficient and robust assessment of the LN immune response we have built a deep learning framework (smuLymphNet) to assess alterations of the immune morphometric features in LNs. As researchers at the Guys Breast Cancer Now unit this research has been developed in collaboration with several consultant pathologists both at Guy’s hospital London, Tata Memorial Hospital Mumbai (largest cancer hospital in Asia) and Tianjin University hospital China.

Solution

Our tool is the first to capture immune features (germinal centres and sinuses) in LNs of breast cancer patients and has revealed the prognostic significance of the LN. We have built the tool in collaboration with clinicians at Guys Hospital London, Tata memorial Hospital India and Tianjin University hospital China. Our team has published several papers on the role of LNs in breast cancer.

Team

UN Sustainable Development Goals

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