PHILADELPHIA--A new mathematical model to better pinpoint tumor location and thereby reduce radiation exposure uses data on how tumor motion has changed during a course of radiation treatment, along with real-time tumor images to calculate the confidence physicists can have about an instantaneous tumor position estimate. The research was presented July 21 at the annual meeting of the American Association of Physicists in Medicine (AAPM).
The goal of the work is to reduce the number of times intrafraction x-ray needs to be triggered as tumor localization measurement, said the study's lead author Dan Ruan, PhD, an instructor in radiation oncology at Stanford University in Stanford, Calif.
With a typical image-guided radiotherapy protocol, x-rays are used at a fixed frequency to validate the location of the tumor target. This rate may be increased to improve the localization accuracy.
Ruan's model, however, which she calls adaptive, aims to accurately localize tumors in real time by imaging smarter, rather than more frequently. It makes online decisions as to whether or not it is necessary to take a new x-ray image during treatment.
Researchers tested their model on 159 patient-derived 3D abdominal and thoracic tumor traces. They found that the model consistently reduced the required total number of images.
Quantitatively, the average imaging frequency was reduced by 40 to 50 percent without sacrificing tumor localization accuracy, meaning that the x-ray dosage to the patient was essentially halved or close to halved, she said.
Reducing imaging radiation is an important goal for oncologists because radiation is associated with secondary malignancies, especially in pediatric patients who typically live for a long time after surviving their cancer, Ruan said. "This model should be helpful in these cases, and particularly for tumors that because of their location—lung, thorax and abdomen—are difficult to locate because of the body movement that occurs as patients breathe."