Major Cancer Center Teams with GE HealthCare to Tackle Radiation Therapy's 17-Step Workflow Problem

Radiation oncology faces a hidden crisis of complexity: importing treatment data for a single cancer patient can require up to 17 manual steps across fragmented systems, and a recent study of over 500 cases revealed more than 44 distinct variations in treatment-planning workflows. Now GE HealthCare and Mass General Brigham are launching a collaboration to deploy generative AI as a potential solution, building on earlier work that already cut patient wait times from 30 days to just 8 days.

Generative AI Meets Fragmented Clinical Data

The partnership will focus on developing a generative AI tool integrated into GE HealthCare's Intelligent Radiation Therapy (iRT) platform. According to the announcement, the technology is designed to consolidate both structured clinical data and unstructured information—including clinical notes, images, and treatment plans—into a single queryable interface for radiation oncology teams.

"Radiation therapy is a critical component of cancer care, yet the workflows supporting it are often fragmented and time-consuming," said Sam Kandala, General Manager of Therapy Guidance at GE HealthCare. The collaboration aims to address these inefficiencies by enabling clinicians to access comprehensive patient information without navigating multiple disconnected systems.

John Wolfgang, PhD, Principal Investigator and Clinical Physicist in the Department of Radiation Oncology at Mass General Brigham, emphasized the potential clinical impact: the tool could support more personalized treatment approaches while reducing administrative burden on multidisciplinary care teams.

Building on Proven Time Savings

This initiative extends an earlier collaboration between GE HealthCare and Massachusetts General Hospital that demonstrated significant workflow improvements. That previous project reduced the time from patient intake to treatment start from 30 days to 8 days—a reduction that could prove critical for cancer patients where treatment delays may affect outcomes.

The current partnership will leverage Mass General Brigham's clinical expertise to refine the generative AI capabilities within the iRT platform, which GE HealthCare describes as AI-supported software for radiation therapy workflow management. Future development plans include expanding iRT capabilities across multiple imaging modalities, including MR, CT, and theranostics.

Addressing a Widespread Challenge

The stakes are substantial: nearly 60% of cancer patients receive radiation therapy as part of their treatment, according to the announcement. The workflow variations identified in the 500-case study suggest that current approaches to radiation therapy planning lack standardization, potentially contributing to inefficiencies, scheduling errors, and delays in care coordination.

By creating a unified interface that can interpret and retrieve information from diverse data sources, the generative AI tool could help clinicians spend less time on data gathering and more time on treatment decision-making. The collaboration represents GE HealthCare's strategy of embedding large language model capabilities into established clinical platforms rather than offering standalone AI tools—an approach that may accelerate adoption by integrating directly into existing oncology workflows.

The partnership underscores how academic medical centers and health technology companies are increasingly turning to generative AI not for diagnostic breakthroughs, but for solving persistent operational bottlenecks that affect patient experience and clinical efficiency.

Sources

1. GE HealthCare and Mass General Brigham Collaborate to Explore Generative AI for Personalized Radiation Therapy - News Center — g-medtech.com