Detecting spatial susceptibility to cardiac toxicity of radiation therapy for lung cancer.

Radiation therapy (RT) is a commonly used approach for treating lung cancer. Because the lungs are close to the heart, radiation dose may inevitably spill to the heart, causing heart damage and diminishing treatment outcomes. There is an urgent need to better understand how treatment outcomes are affected by radiation dose spilled to the heart in order to optimize RT planning. However, despite the fact that dose distribution on the heart is 3-D, most existing research collapses the 3-D dose map into a 1-D histogram to be linked with outcomes. This ignores the spatial information. We propose a novel method that automatically searches for subregions of the heart that are susceptible to radiation toxicity, called Toxicity-Susceptible Subregions (TSSs), based on the 3-D dose distribution. We apply the proposed method to a real-world dataset and find TSSs that harbor the sinoatrial node of the electronic conduction system of the heart. Damage of the sinoatrial node by radiation toxicity disrupts the crucial function of the heart, leading to shortening of the overall survival. Our finding suggests that protective strategies may be developed to spare the TSSs, and thus helping RT planning achieve optimal results in treating lung cancer patients.