Monte Carlo radiotherapy simulations of accelerated repopulation and reoxygenation for hypoxic head and neck cancer

Abstract

Objective: A temporal Monte Carlo tumour growth and radiotherapy effect model (HYP-RT) simulating hypoxia in head and neck cancer has been developed and used to analyse parameters influencing cell kill during conventionally fractionated radiotherapy. The model was designed to simulate individual cell division up to 10 8 cells, while incorporating radiobiological effects, including accelerated repopulation and reoxygenation during treatment. Method: Reoxygenation of hypoxic tumours has been modelled using randomised increments of oxygen to tumour cells after each treatment fraction. The process of accelerated repopulation has been modelled by increasing the symmetrical stem cell division probability. Both phenomena were onset immediately or after a number of weeks of simulated treatment. Results: The extra dose required to control (total cell kill) hypoxic vs oxic tumours was 15-25% (8-20 Gy for 562 Gy per week) depending on the timing of accelerated repopulation onset. Reoxygenation of hypoxic tumours resulted in resensitisation and reduction in total dose required by approximately 10%, depending on the time of onset. When modelled simultaneously, accelerated repopulation and reoxygenation affected cell kill in hypoxic tumours in a similar manner to when the phenomena were modelled individually; however, the degree was altered, with non-additive results. Simulation results were in good agreement with standard linear quadratic theory; however, differed for more complex comparisons where hypoxia, reoxygenation as well as accelerated repopulation effects were considered. Conclusion: Simulations have quantitatively confirmed the need for patient individualisation in radiotherapy for hypoxic head and neck tumours, and have shown the benefits of modelling complex and dynamic processes using Monte Carlo methods.

Altered fractionation outcomes for hypoxic head and neck cancer using theHYP-RTMonte Carlo model

“…The validity of the HYP-RT model compared with the standard LQ model (for oxic and hypoxic tumours) and the known limitations and assumptions of the cell growth and radiotherapy algorithms have been previously reported [3][4][5]. Statistical uncertainty in the model results arising from the use of different random number seeds continued to be in the range of 4-6 Gy in the current work [3].…”

“…The model incorporates a realistic epithelial cell hierarchy, tumour hypoxia and mimics the effects of AR and ROx during radiotherapy-induced tumour shrinkage [3][4][5].…”

“…The methods used to implement AR through loss of asymmetrical stem cell division as well as the gradual daily increase of oxygenation levels to cells to simulate ROx have been outlined in detail previously [3]. Two different AR and ROx onset times are simulated for each schedule (0 weeks and 2 weeks) as well as no AR or ROx effects, with model outcomes averaged over nine different simulations using unique random number seeds (three radiotherapy runs on three virtual tumours).…”

“…Statistical uncertainty in the model results arising from the use of different random number seeds continued to be in the range of 4-6 Gy in the current work [3]. For figures referenced in the following Results section, error margins (1 standard deviation) of this dose level apply; however, they have been purposely removed from some figures owing to the large amount of data displayed to allow for clearer visualisation of the results.…”

“…Model outcomes that compare the doses required for 100% tumour control (for "moderately hypoxic" tumours [3,4]) are presented in Figure 3a,b for seven AR and ROx onset time combinations, illustrating the full range of dose outcomes arising owing to the onset time variations, for each of the 11 schedules. Figure 3a shows that the ranges in results caused by altering AR Figure 3.…”