Combining radiation with hyperthermia: a multiscale model informed by in vitro experiments.

Area of Science:

• Computational oncology
• Mathematical modeling in cancer research
• Multiscale systems biology

Background:

• Combined radiotherapy and hyperthermia show promise for radio-resistant tumors via thermo-radiosensitization.
• Tumor response heterogeneity complicates traditional treatment planning.
• Systems oncology simulations offer a powerful approach for treatment optimization.

Purpose of the Study:

• To develop and validate a multiscale hybrid cellular automaton framework for simulating combined radiotherapy and hyperthermia treatments.
• To model individual cell-cycle progression and treatment response at a cellular level.
• To assess the framework's accuracy against experimental data for HCT116 cells.

Main Methods:

• A multiscale hybrid cellular automaton simulating up to 10^7 cells in vitro.
• Modeling of radiation-induced mitotic cell death and heat-induced immediate cell kill.
• Calibration using experimental data on cell growth, cell cycle, and survival.

Main Results:

• Model predictions showed excellent agreement (R^2 > 0.95) with experimental data for HCT116 cells.
• The framework accurately simulated tumor response within tested radiation (0-5 Gy) and thermal doses (0-40 CEM43).
• Demonstrated flexibility in modeling multimodality treatment combinations.

Conclusions:

• The developed framework provides a robust tool for simulating combined radio-hyperthermia treatments.
• This approach can help account for tumor response heterogeneity in treatment planning.
• It represents a significant step towards personalized cancer therapy modeling using virtual patient tumors.