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

Tumor Treating Fields (TTFs) in a quasi-electrostatic field represent an emerging and effective cancer therapy owing to their non-invasive, safe, portable, and low-cost advantages. However, the key electric parameters in TTFs remain unknown and TTFs are in a "black box" state. Essentially, the existing TTFs use only two alternating directions as excitations with fixed excitation times, but the multidirectional and targeted one can have a better treatment effect.

We develop a multi-directional excitation TTFs (m-TTFs) system, and analytically derive a computation model for electric parameters such as potential, electric field intensity, and energy distribution within the m-TTFs system. According to the perturbation analysis, we further compute these parameters for any individual in whom all tissues have arbitrary dielectric properties, and optimize excitation times in the m-TTFs to approximately focus the electic energy on these lung lesions.

Both simulations and experiments demonstrate high consistency between the computed parameters and actual values. The mean absolute error (MAE) for the computed electric parameters is low relative to the actual values. For the conductivity and permittivity of general tissues as well as those during dynamic respiratory processes, all three computed electric parameters exhibit low error compared to actual values. Optimizing the excitation strategy in the m-TTFs system significantly enhances the electric potential within the tumor. In actual experiments, we constructed three models under different respiratory phases. No significant discrepancies were observed between the measured and computed electric field intensities for a set of randomly selected points, the overall MAE was less than 0.6571.

Consequently, the proposed model to compute the key electric parameters can effectively solve the "black box" problem in both current TTFs and m-TTFs, and the designed m-TTFs system and optimized excitation methods provide a solid basis for improving TTFs protocols, enhancing applicability, and evaluating treatment outcomes.