Cancer patients are often expected to wait before starting radiation therapy so that a full treatment plan can be developed. AI could help make such delays a thing of the past, according to new research out of UT Southwestern Medical Center in Dallas, Texas.
“Some of these patients need radiation therapy immediately, but doctors often have to tell them to go home and wait,” Steve Jiang, PhD, director of UT Southwestern’s Medical Artificial Intelligence and Automation (MAIA) Lab, said in a prepared statement. “Achieving optimal treatment plans in near real time is important and part of our broader mission to use AI to improve all aspects of cancer care.”
Jiang contributed to two new studies published in Medical Physics, the official journal of the American Association of Physicists in Medicine. In one study, the authors found that AI could “produce optimal treatment plans within five-hundredths of a second after receiving clinical data for patients.” Jiang and colleagues explored data from 70 prostate cancer patients, training AI to assess each patient’s entire situation and predict the treatment plan ultimately chosen by healthcare providers.
“The real‐time prediction capabilities allow for a physician to quickly navigate the tradeoff space for a patient, and produce a dose distribution as a tangible endpoint for the dosimetrist to use for planning,” the authors wrote. “This is expected to considerably reduce the treatment planning time, allowing for clinicians to focus their efforts on the difficult and demanding cases.”
In addition, another study published in Medical Physics focused on AI’s ability to recalculate dosages before each radiation session. This represents another significant step in reducing the time it takes for cancer patients to receive the care they need.
Michael has more than 16 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.