Google has teamed up with some British researchers to come up with a way of using AI to automatically differentiate between cancerous and healthy tissues on patient scans.
The partnership brings together leading clinicians and researchers at University College London Hospitals NHS Foundation Trust (UCLH) with some of the UK’s top technologists at DeepMind Health, which specialises in using machine learning to solve some of the world’s most difficult problems.
At present, it can take clinicians up to four hours to identify and differentiate between cancerous and healthy tissues on CT and MRI scans of head and neck cancer patients. This process, known as segmentation, is particularly difficult in head and neck cancer patients because their tumours are situated in extremely close proximity to healthy structures such as the eyes and nerves.
Before treatment can begin, clinicians identify the cancerous areas on the scans, and the areas that must be protected from radiation. It is essential that cancerous and healthy tissues are identified accurately so that radiotherapy treatment can be effectively targeted, giving the highest radiation dose possible to the tumour, while preserving healthy, surrounding structures and reducing possible side effects.
The purpose of the research collaboration between UCLH and DeepMind is to develop artificial intelligence technology to assist clinicians in the segmentation process so that it can be done more rapidly but just as accurately. Clinicians will remain responsible for deciding radiotherapy treatment plans but it is hoped that the segmentation process could be reduced from up to four hours to around an hour.
The research involves anonymised radiotherapy images of up to 700 former head and neck cancer patients who have consented to their data being used for research purposes.
Dr Yen-Ching Chang, clinical lead for radiotherapy at UCLH, said: “This is very exciting research which could revolutionise the way in which we plan radiotherapy treatment.
“Developing machine learning which can automatically differentiate between cancerous and healthy tissue on radiotherapy scans will assist clinicians in planning radiotherapy treatment. This has the potential to free up clinicians to spend even more time on patient care, education and research, all of which would be to the benefit of our patients and the populations we serve.
“This collaboration also means our patients continue to benefit from the most cutting-edge developments in healthcare technology.”
Professor Kathy Pritchard-Jones, chief medical officer of London Cancer, the integrated cancer system that serves a population of more than 3.5 million, said: “Head and neck cancer is rare and is one of the most complex tumour sites to treat. Therefore, if we can develop technology to assist in planning radiotherapy treatment for these tumours, we would expect that such a breakthrough would be transferable to other types of cancer. This would not only benefit UCLH patients, but patients across the country.”
DeepMind Co-Founder Mustafa Suleyman said: “This real-world application of artificial intelligence (AI) technology is exactly why we set up DeepMind. We’re incredibly excited to be working with the radiotherapy team at UCLH to explore how AI can help to reduce the time it takes to plan radiotherapy treatment for head and neck cancer patients. We hope this work could lead to real benefits for cancer patients across the country and for the clinicians who treat them.”