GE HealthCare Expands Research Collaboration to Explore Using Generative AI for More Personalized Radiation Therapy

• New research collaboration builds on a history of innovation between GE HealthCare and Mass General Brigham, where technology developed at Massachusetts General Hospital became a component of GE HealthCare’s Intelligent Radiation Therapy™ (iRT) solution and helped reduce the time from patient intake to the start of treatment from as long as 30 days down to eight days¹.
• The research will explore developing a generative AI tool that could bring together structured clinical data and unstructured information across systems to allow radiation oncology teams to ask questions and easily access relevant information about a patient’s treatment journey.

CHICAGO - September 23, 2026 — GE HealthCare today announced a new collaboration with a research team at Mass General Brigham to explore how generative artificial intelligence (AI) could help radiation oncology teams quickly access and interpret the information involved in planning and delivering cancer treatment that is often spread across various systems. The teams aim to develop a generative AI tool that could be integrated into Intelligent Radiation Therapy (iRT), GE HealthCare’s AI-supported software solution for radiation therapy workflow management designed to connect tools, coordinate workflows, and reduce manual handoffs to help patients progress from diagnosis to treatment more efficiently.

Nearly 60% of people with cancer receive radiation therapy², yet the process of planning and preparing treatment has historically been fragmented. The length and complexity of treatment, combined with the number of care teams typically involved in a patient’s journey mean that radiation oncology teams must work across multiple systems and sources of information that rarely connect. The workflows can also be both highly manual and highly variable. A simple task like importing treatment data can take up to 17 manual steps, while one study of more than 500 radiation oncology cases identified more than 44 variations in the treatment-planning workflow³. This variability is driven in part by the unstructured nature of the information clinicians must work with, such as clinical notes and reports, making it harder for care teams to quickly find and synthesize the information they need, potentially contributing to delays in patient care.

To help address these challenges, teams from Mass General Brigham and GE HealthCare will explore developing a generative AI tool that could bring together structured clinical data and unstructured information—including clinical notes, images, and treatment plans—allowing radiation oncology teams to ask questions in order to surface relevant information quickly about a patient’s treatment journey. The tool could provide a summarized view to help clinicians navigate complex treatment data and inform care decisions to deliver more personalized care. Insights from the research could ultimately inform future iRT workflow capabilities across MR, CT, and theranostics.

The collaboration builds on a history of innovation between GE HealthCare and Massachusetts General Hospital, a founding member of the Mass General Brigham healthcare system, where software technology developed at the hospital became a component of GE HealthCare’s Intelligent Radiation Therapy™ (iRT) solution. Research found the technology helped reduce the time from patient intake to the start of treatment from as long as 30 days down to eight days⁴ by connecting and orchestrating fragmented workflows.

“Our original work demonstrated how technology can remove barriers in care delivery and help clinicians focus more of their time on patients while accelerating time to treatment,” said John Wolfgang, PhD, a principal investigator on the research and clinical physicist in the Department of Radiation Oncology at Mass General Brigham. “We are excited to advance this work to explore how AI could further support radiation oncology care teams by making complex treatment information easier to access, understand, and act on.”

Today, hospitals worldwide are implementing iRT to manage their radiation therapy and theranostics workflows, improving efficiency and helping coordinate care across the treatment pathway. The new research will explore whether new AI capabilities could help expand the solution toward more personalized care by helping clinicians access the patient-specific information needed to inform individualized treatment decisions.

“Our iRT solution began by solving a very real clinical problem, making a complex and fragmented radiation therapy process simpler and more efficient,” said Sam Kandala, General Manager, Therapy Guidance at GE HealthCare. “This new collaboration gives us an opportunity to build on that foundation and explore how AI could help clinicians not only work more efficiently but also make better use of the information available to them as they personalize treatment for each patient.”

1. These data are based on analysis of over 11,000 treatment plans at MGH, following the implementation of a workflow efficiency solution. iRT was developed using the MGH solution as a foundation, with extended connectivity and interoperability capabilities. Any results achieved using iRT may vary based on differences in workflows, patient populations, or other factors.

2. American Society for Radiation Oncology. Radiation Oncology Case Rate (ROCR) Report. June 26, 2023. https://www.astro.org/ASTRO/media/ASTRO/Advocacy/PDFs/ROCRReport.pdf

3. https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000647

4. These data are based on analysis of over 11,000 treatment plans at MGH, following the implementation of a workflow efficiency solution. iRT was developed using the MGH solution as a foundation, with extended connectivity and interoperability capabilities. Any results achieved using iRT may vary based on differences in workflows, patient populations, or other factors.