Lung Cancer Radiotherapy: Simulation and Analysis Based on a Multicomponent Mathematical Model.

Area of Science:

• Biomedical Engineering
• Computational Biology
• Oncology

Background:

• Lung cancer remains a leading global cause of mortality.
• Radiotherapy is a key treatment modality for lung cancer.
• Mathematical models are increasingly used in biomedical fields for analysis and prediction.

Purpose of the Study:

• To develop and validate a multicomponent mathematical model for simulating lung cancer growth.
• To simulate and analyze the efficacy of different radiotherapy treatment plans.

Main Methods:

• A multicomponent mathematical model was developed for lung cancer growth and radiotherapy simulation.
• The model was digitalized, coded for computer simulation, and parameters were fitted with in vitro data.
• Various radiotherapy plans, including stereotactic body radiotherapy and conventional fractional radiotherapy, were simulated.

Main Results:

• The mathematical model successfully simulated lung cancer growth and radiotherapy.
• Analysis of typical radiotherapy plans demonstrated the model's capability for evaluation.
• The model provided results consistent with in vitro lung cancer cell growth.

Conclusions:

• The developed mathematical model serves as a foundational tool for analyzing and evaluating radiotherapy plans.
• Mathematical modeling is poised to become invaluable for optimizing personalized lung cancer treatment in the future.