A Population-Based Tumor-Volume Model for Head-and-Neck Cancer During Radiotherapy with a Dynamic Oxygenated Compartment

Purpose With the coming era of digital wisdom medical technology, mathematical modelling of tumor becomes a key step to optimize and realize precision radiotherapy. The purpose of this study is to develop a mathematical model for simulating the change of head-and-neck tumor (HN) volume during radiotherapy. Methods and Materials A formula is developed to describe the dynamic change of oxygenated compartment within a tumor, which is combined with the LPL model to describe various cell processes during radiotherapy, including potentially lethal lesion repair and misrepair, cell proliferation/loss, and tumor reoxygenation. Parameter sensitivity analysis is performed to evaluate the impacts of the lesion-related and repair-related biological factors on radiotherapy outcome. Results We tested our model on 14 available HN cancer patients and compared the performance with three other models. The mean error of our model for the twelve good fit cases is 12.2%, which is considerable smaller than that of the LQ model (19.7%), GLQ model (19.1%) and FLCP model (16.6%). Correlation analysis results reveal that for small tumors, there is a positive correlation (correlation coefficient r=0.9416) between hypoxic fraction and tumor volume, whereas the correlation becomes negative and not significant (r=−0.4365) for large tumors. It is demonstrated from sensitivity analysis that the production rate of lethal lesions (ηl) has a far greater impact on tumor volume than other parameters. The hypoxic fraction has insignificant impact on tumor volume, but it has notable influence on the volume of surviving cells. The final volume of surviving cells athf=0.5 is almost 8 ×102 times that of hf=0.01. The potentially lethal lesion-related parameters (ηpl,εpl, ε2pl) have 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 radiotherapy 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 head-and-neck tumors during treatment has been revealed. Meanwhile, various cell activities and their principles in the process of anti-tumor treatment were reflected, and it has positive clinical reference significance for radiobiology.