New Research Uses AI to Guide Radiation Treatment Protocols

“Radiation exposure to the heart during lung cancer treatment can have very serious and immediate effects on a patient’s cardiovascular health,” Raymond Mak, MD, director of clinical innovation for the Department of Radiation Oncology at Brigham and Women’s and corresponding author for the study, said in a press release. “We are hoping to inform not only oncologists and cardiologists, but also patients receiving radiation treatment, about the risks to the heart when treating lung cancer tumors with radiation.”

The study is just the latest effort by health systems and hospitals to apply AI to clinical care pathways.

The Brigham and Women’s team used AI to gain a more focused understanding of how the heart is affected by that radiation treatment. Researchers analyzed data from 748 patients who had been treated with radiation for locally advanced NSCLC to identify different types of arrhythmia that can occur. They found that 1 in 6 patients experience at least one grade 3 arrhythmia within roughly two years of treatment, and 1 of every 3 of those patients experienced “major adverse cardiac events.”

“An interesting part of what we did was leverage artificial intelligence algorithms to segment structures like the pulmonary vein and parts of the conduction system to measure the radiation dose exposure in over 700 patients,” Mak said in the press release. “This saved us many months of manual work. So, not only does this work have potential clinical impact, but it also opens the door for using AI in radiation oncology research to streamline discovery and create larger datasets.”

Mak and his team concluded that radiation oncologists should collaborate with cardiology specialists when developing radiation treatment plans, including embracing strategies that “actively sculpt radiation exposure” away from the areas of the heart that are susceptible to arrhythmias.