DeepMind Q and A 

In August 2016 we announced a medical research partnership with DeepMind Health. Find out more.

Below is a Q and A about the partnership.

  • What does UCLH’s research agreement with DeepMind Health involve?

    Under the agreement, UCLH will provide DeepMind Health secure access to anonymised CT and MRI scans of approximately 700 head and neck cancer patients who have consented to their data being used for research purposes.
  • What is the purpose of the research?

    The purpose of the research is to develop technology which can automatically identify and differentiate between cancerous and healthy tissues on CT and MRI scans of head and neck cancer patients to help target radiotherapy treatment.

    At present, this process, known as segmentation, can take clinicians up to four hours to complete manually, as tumours in head and neck patients are situated in extremely close proximity to healthy structures such as the eyes and nerves.

    The research aims 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.

    Longer term 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.

    In addition, given that head and neck cancer is one of the most complex tumour sites to treat, 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 patients at UCLH, but patients across the country.

  • Will the technology being developed replace the doctor’s role in deciding treatment?

    No. We hope the technology will assist clinicians but they will remain responsible for deciding patients’ treatment plans.
  • Do the images being transferred to DeepMind Health contain patient identifiable information?

    No, all of the images will be anonymised by UCLH before being transferred to DeepMind Health for the research to begin.
  • Does the patient data used in this project relate to former or current patients?

    The research involves anonymised scans dating back to 2008 of head and neck cancer patients who have since completed radiotherapy treatment. At the time, these patients would have consented to their anonymised data being used for research purposes. Scans of patients currently undergoing radiotherapy treatment will not be included in the research.
  • Did the patients give consent for their data to be used for research?

    The data used in this research is not personally identifiable, it is anonymised. In these circumstances, consent from patients for their data to be shared is not required and is covered by our privacy statement.

    When radiotherapy patients begin treatment, however, we do ask them to sign a consent form which allows their anonymised data to be used for research purposes. Only patients who have given consent for their anonymised data to be used for research purposes will be included in this study.

  • How can patients stop their data from being used for research purposes?

    Patients who do not wish their data to be shared for any research purposes can opt out by emailing UCLH’s information governance team on igqueries@uclh.nhs.uk
  • What are the Data Protection measures in place for this project?

    UCLH will rigorously ensure that no personally identifiable data is included in the database of scans provided to DeepMind Health for this project. During the course of the project DeepMind Health must take rigorous measures to protect the security of the data, and may not disclose it to anyone other than the researchers and engineers working on the project. Data contributing to this study can only be used for research that explores the use of machine learning to identify and differentiate between healthy and cancerous cells in radiotherapy images.
  • What processes are in place to ensure that the anonymised data transferred to DeepMind Health is only ever seen by the research team?

    A data custodian has been appointed by DeepMind Health to control access to the data. Only those who require access to conduct the research work will be granted access. All researchers who are involved in the study are required to complete Health and Social Care Information Centre (HSCIC) training and internal DeepMind Health information governance training before beginning research work.
  • What happens to the data at the end of the agreement?

    DeepMind Health must securely destroy all copies of anonymised data received through the agreement. A certificate of destruction will be provided to UCLH.
  • Who owns the data?

    UCLH owns the data at all times – both during and after the agreement has finished.
  • Does the research have ethical approval?

    Yes, the project was granted ethical approval by the national research ethics service and the UCL/UCLH joint research office. A summary of the project is available on the Health Research Authority’s website.
  • How long is the research project with DeepMind Health?

    The research agreement will last five years. Either UCLH or DeepMind Health can end the project early with 30 days’ notice.
  • What will you do with the results of the research?

    DeepMind Health will publish the results through normal academic channels, subject to formal peer review process.
  • Where can I find more detail on the agreement between DeepMind and UCLH?

    The research study protocol is available on the F1000 Research website. You can also request a copy of the research collaboration agreement and the data sharing agreement (with minor redactions for commercial sensitivity) by emailing our communications team. Patients who have further questions can speak to our Patient Advice and Liaison Service (PALS).