A Population-Based Tumor-Volume Model for Head and Neck Cancer During Radiation Therapy With a Dynamic Oxygenated Compartment.

Purpose: With the coming era of digital medicine and healthcare technology, mathematical modeling of tumors has become a key step to optimize and realize precision radiation therapy. The purpose of this study was to develop a mathematical model for simulating the change of head and neck (HN) tumor volume during radiation therapy.

Methods And Materials: A formula was developed to describe the dynamic change of oxygenated compartment within a tumor, which was combined with the lethal lesions model to describe various cell processes during radiation therapy, including potentially lethal lesion repair and misrepair, cell proliferation/loss, and tumor reoxygenation. Parameter sensitivity analysis was performed to evaluate the impacts of lesion- and repair-related biological factors on radiation therapy outcomes.

Results: We tested our model on 14 available patients with HN cancer and compared the performance with 3 other models. The mean error of our model for the 12 good fit cases was 12.2%, which is considerably smaller than that of the linear quadratic model (19.7%), the generalized linear quadratic model (19.1%), and a 4-level cell population model (16.6%). Correlation analysis results revealed that for small tumors, there was a positive correlation (correlation coefficient r=0.9416) between hypoxic fraction (hf) and tumor volume, whereas the correlation became negative and not significant (r=-0.4365) for large tumors. It is demonstrated from sensitivity analysis that the production rate of lethal lesions (η) has a far greater impact on tumor volume than other parameters. The hf had an insignificant impact on tumor volume but had a notable influence on the volume of surviving cells. The final volume of surviving cells athf=0.5 was almost 8 ×10 times that of hf=0.01. The potentially lethal lesion-related parameters (the production rate of potentially lethal lessions per unit dose η, the rate of correct repair per unit time ε, and the rate of binary misrepair per unit time ε) had rather small impacts (<1%) on both tumor volume and the volume of surviving cells, which indicates that the repaired and misrepaired sublethal cells only take up a small portion of the total cancer cell population.

Conclusions: A population-based tumor-volume model for HN cancer during radiation therapy with a dynamic oxygenated compartment was developed in this study. Comprehensively considering the damage process of tumor cells caused by radiation therapy, the accurate prediction of the volume change of HN tumors during treatment was revealed. Meanwhile, various cell activities and their principles in the process of antitumor treatment were reflected, which has positive clinical reference significance for radiobiology.