Researchers at the University of Waterloo have identified a new method of planning radiation therapy that can be up to 22% more effective at killing cancer cells than current standard radiation therapy regimens.
While many mathematical studies have looked at how to optimize the timing of radiation therapy for maximum efficacy against cancer, most of these studies assume “intratumor homogeneity,” meaning that all cancer cells are identical. In recent years, however, scientists have realized that tumors are made up of many different types of cells. More importantly, they include cancer stem cells, which are more resistant to radiation than other cell types.
“The problem with any calculation involving cancer is that it’s very difficult to get exact values because things vary from cancer type to cancer type, patient to patient, even within the tumor,” said Cameron Meaney, Ph.D. in applied mathematics at Waterloo and principal investigator of the study.
This new algorithm can generalize the different radiation resistances of stem and non-stem cells, allowing doctors to predict how a tumor will respond to treatment before gathering exact data on an individual’s cancer.
The model has limitations, Meaney explained, because tumors contain far more than just two types of cells. What it does, however, is provide clinical researchers with a better starting point for therapeutic research.
“The results from the algorithm are important because they illuminate the idea that tumor heterogeneity is important to treatment planning,” Meaney said.
The next step the researchers hope to see is an application of their algorithm to clinical trials: Will their suggested treatment schedule outperform existing planning practices in a laboratory trial?
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