A parameter computation and optimization method in multi-directional exciting tumor treating fields

Area of Science:

• Biophysics
• Medical Physics
• Oncology

Background:

• Tumor Treating Fields (TTFs) offer a non-invasive cancer therapy but operate as a 'black box' due to unknown electric parameters.
• Current TTFs utilize limited excitation directions and fixed times, potentially limiting treatment efficacy.

Purpose of the Study:

• To develop a multi-directional TTFs (m-TTFs) system and a computational model to elucidate key electric parameters.
• To optimize m-TTFs excitation strategies for improved energy focusing on lung lesions.

Main Methods:

• Developed an m-TTFs system and analytically derived a computation model for electric parameters (potential, field intensity, energy distribution).
• Employed perturbation analysis to compute parameters for arbitrary dielectric properties and optimize excitation times.
• Validated the model through simulations and experiments, including models simulating respiratory phases.

Main Results:

• High consistency was observed between computed and actual electric parameters, with low Mean Absolute Error (MAE < 0.6571).
• The model accurately predicted parameters for various tissues and dynamic respiratory processes.
• Optimized excitation strategies significantly enhanced electric potential within the tumor.

Conclusions:

• The proposed model effectively addresses the 'black box' problem in TTFs and m-TTFs.
• The developed m-TTFs system and optimized excitation methods provide a foundation for enhanced TTFs protocols and treatment outcome evaluation.