Researchers at Brigham and Women’s Hospital used AI to help understand when radiation treatments can cause dangerous heart arrhythmias.
Healthcare researchers are now using AI to gain a better understanding of when patients should and should not receive radiation as part of their treatment.
In a study published in JACC: CardioOncology, a team from Brigham and Woman’s Hospital used an AI tool to better understand the risk of cardiac arrhythmia for patients undergoing radiation treatment for lung cancer. The results not only could lead to better treatment plans but also improve care for the estimated 1 in 6 patients who experience severe side effects, including death.
“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.
This research targets patients receiving radiation therapy to treat non-small cell lung cancer (NSCLC), for which arrhythmias can be a common side effect. Because NSCLC tumors and the treatment to eradicate them occur close to the heart, the heart can be affected by those doses of radiation.
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.
Eric Wicklund is the associate content manager and senior editor for Innovation at HealthLeaders.
KEY TAKEAWAYS
Healthcare researchers are using AI to process sophisticated sets of data on clinical care.
In one case, researchers from Brigham and Women’s Hospital were able to identify the effects of radiation treatment for lung cancer on the heart.
With that data, care teams can adjust and improve radiation treatment protocols and potentially save the lives of patients at higher risk of arrhythmia.