A New Method for Optimal Placement of Tumor Treating Fields Electrodes

Area of Science:

• Neuro-oncology
• Medical Physics
• Computational Biology

Background:

• Tumor Treating Fields (TTFields) are a non-invasive therapy for glioblastoma.
• Current TTFields planning uses proprietary software (NovoTAL®) lacking clinical validation.
• Optimizing electrode placement is crucial for enhancing TTFields efficacy.

Purpose of the Study:

• To develop and evaluate a novel computational approach for optimizing TTFields electrode placement.
• To compare the performance of the new method against the current clinical standard (NovoTAL®).
• To assess the impact of tumor characteristics on optimization outcomes.

Main Methods:

• A computational pipeline integrating patient-specific anatomical data was developed.
• Two optimization strategies were used: maximizing tumor intensity and enhancing adjacent brain coverage.
• Results were compared to NovoTAL® placements and validated with simulations on artificial tumors.

Main Results:

• Optimized placements increased tumor electric field intensity by 18%-34% over the clinical standard.
• Coverage-weighted optimizations improved field distribution without compromising tumor intensity.
• Smaller and surface-adjacent tumors showed the most significant benefits from optimized placement.

Conclusions:

• Personalized TTFields electrode placement optimization enhances tumor targeting and brain coverage.
• The computational approach surpasses current clinical planning software.
• This work supports the development of adaptive, individualized TTFields therapy for glioblastoma.