GE HealthCare Partners with Mass General Brigham to Integrate AI in Radiation Oncology

On September 23, 2026, GE HealthCare announced a collaboration with a research team at Mass General Brigham to investigate the potential of generative artificial intelligence (AI) in facilitating efficient access to cancer treatment information. This initiative seeks to enhance the planning and delivery of radiation therapy, which traditionally involves data fragmented across various systems.

With nearly 60% of cancer patients receiving radiation therapy, the treatment planning process often lacks cohesion. The complexity of treatment schedules and the involvement of multiple care teams necessitate navigation across numerous unconnected systems. Current workflows can be labor-intensive and variable; for instance, importing treatment data may require up to 17 manual steps. A study examining over 500 radiation oncology cases uncovered more than 44 variations in the treatment-planning workflow, highlighting the challenges posed by unstructured clinical information such as notes and reports.

To address these issues, the teams from GE HealthCare and Mass General Brigham plan to develop a generative AI tool. This tool aims to integrate both structured clinical data and unstructured information, allowing radiation oncology teams to swiftly access relevant patient treatment information through targeted inquiries. By providing a consolidated view of complex data, the tool could aid clinicians in making informed care decisions, potentially personalizing treatment plans for patients. Insights gleaned from this research could also enhance future capabilities of Intelligent Radiation Therapy (iRT) systems across various imaging modalities including MR and CT.

This collaboration builds upon a successful history of technological innovation between GE HealthCare and Massachusetts General Hospital, from where foundational technologies transitioned into GE’s iRT solution. Previous research indicated that this technology significantly reduced the time from patient intake to the initiation of treatment, decreasing the wait time from 30 days to just eight days by streamlining fragmented workflows.

John Wolfgang, PhD, principal investigator and clinical physicist at Mass General Brigham's Department of Radiation Oncology, emphasized the importance of utilizing technology to mitigate barriers in care delivery, thereby allowing clinicians to concentrate on patient interactions and expedite treatment timelines. The evolving collaboration aims to further leverage AI to simplify access to and understanding of complex information faced by radiation oncology care teams.

As hospitals globally adopt iRT to improve efficiency in managing radiation therapy and theranostics workflows, this new research aims to explore how enhanced AI capabilities could contribute to more personalized patient care by providing clinicians with essential, tailored information for individualized treatment approaches.

Sam Kandala, General Manager of Therapy Guidance at GE HealthCare, expressed enthusiasm about building on the successful iRT foundation to explore how AI could optimize clinicians' efficiency and the personalization of patient care.