Modelling the interplay between hypoxia and proliferation in radiotherapy tumour response

Area of Science:

• Radiotherapy
• Computational modeling
• Tumor biology

Background:

• Fractionated radiotherapy efficacy depends on tumor microenvironment factors like hypoxia and proliferation.
• Understanding the interplay of these factors is crucial for optimizing treatment outcomes.

Purpose of the Study:

• To develop a computational model simulating tumor control probability during fractionated radiotherapy.
• To incorporate hypoxia, proliferation, and reoxygenation dynamics.
• To evaluate the impact of varying growth fraction (GF) and volume doubling time (TD) on treatment outcomes.

Main Methods:

• A three-compartment model was developed: proliferating, intermediate (metabolically-active), and hypoxic.
• Initial cell distribution was determined by local GF and TD.
• Tumor response simulations were performed for head and neck squamous cell carcinoma.

Main Results:

• Conventional fraction sizes (2-2.4 Gy) predicted smaller tumor control dose 50% (TCD50) values than larger fractions (4-5 Gy) due to reoxygenation.
• Increased initial proliferation (high GF) surprisingly led to moderately higher local control.
• Tumor hypoxia was predicted to increase the required dose for local control by approximately 30%.

Conclusions:

• The model uniquely determines initial cell distribution from GF and TD.
• It demonstrates how local resource competition impacts local control rates under varying fractionation.
• Predicted tumor regression patterns align with clinical observations.