Artificial Intelligence Could Speed Up Radiotherapy

"Intensity-modulated radiation therapy (IMRT) has exploded in popularity, but the technique can require hours of manual tuning to determine an effective radiation treatment for a given patient,” said Dr. Richard Radke, assistant professor of electrical, computer, and systems engineering at Rensselaer.

A subfield of artificial intelligence, machine learning is based on the development of algorithms that allow computers to learn relationships in large datasets from examples. Dr. Radke and his coworkers have evaluated their algorithm on 10 prostate cancer patients at MSKCC. They discovered that for 70% of the cases, the algorithm automatically determined an appropriate radiation therapy plan in approximately 10 minutes.

IMRT adds subtle distinctions and flexibility to radiation therapy, increasing the likelihood of treating a tumor without endangering surrounding healthy tissue. Each IMRT beam is composed of thousands of tiny "beamlets” that can be individually modulated to deliver the right level of radiation precisely where it is needed. However, the semi-automatic process of developing a treatment plan can be very time-consuming--up to about four hours for prostate cancer and up to an entire day for more complicated cancers in the head and neck, according to Dr. Radke.

The procedure was assessed by developing radiation plans for 10 patients with prostate cancer. In all 10 cases, the process took between five and 10 minutes, according to Dr. Radke. Four cases would have been immediately acceptable in the clinic; three needed only minor adjusting by an expert to achieve an acceptable radiation plan; and three would have demanded more attention from a radiation planner.


Related Links:
Rensselaer Polytechnic Institute
Memorial Sloan-Kettering Cancer Center