Mayo Clinic and Google Health recently announced a joint initiative focused on researching how best to apply AI into radiation therapy planning, a critical aspect of cancer care.
In the first part of the project, Mayo experts from radiation therapy and other specialties will partner with Google Health’s experts to use de-identified data to develop and validate an algorithm to automate contouring of healthy tissue and organs from tumors. The teams also aim to develop adaptive dosage and treatment plans for patients undergoing radiation therapy for cancers in the head and neck area
The initiative’s overall goal is to develop an algorithm that will improve quality of radiation plans and patient outcomes while reducing treatment planning times and improving the efficiency of radiotherapy practice.
"Today, more than half of patients diagnosed with cancer receive radiation therapy, and the number is expected to grow in the future," said Nadia Laack, M.D., chair of the Department of Radiation Oncology at Mayo Clinic in Rochester and one of the principal investigators on the project. She added that contouring is particularly challenging for sensitive areas like the head and neck where many delicate structures are located close together and may take six hours or longer for more complex cases, and she noted that during radiation therapy planning, “physicians identify organs and tumors in a manual or semiautomated manner that is subject to variability.”
According to Chris Beltran, Ph.D., chair of the Division of Medical Physics at Mayo Clinic in Florida and one of the principle investigators on the project, “Radiation Oncology is ripe if not overdue for application of AI-augmented methods, particularly deep-learning-based approaches. We are excited to work with Google Health so we can get closer to developing reliable AI tools to help make sure we get to the best plan possible for each patient."
The partner organizations hope that AI-based tools may eventually help broaden access to specialized expertise across the world and help reduce prolonged wait time for patients.
"Applying AI and machine learning may also help to alleviate radiation oncology workforce shortages throughout the world and decrease the variability in the quality of care patients receive," said Dr. Laack.
The initiative is the first research collaboration in a strategic partnership Mayo Clinic and Google announced last year that aims to improve the delivery of care for serious and complex conditions by harnessing knowledge and data creating useful digital tools.