Tumor Treating Fields: A Review of Computational Strategies for Thermal Safety and Personalization Treatment.

Abstract

Tumor Treating Fields (TTFields) therapy, a clinically established modality that disrupts cancer cell mitosis through biophysical mechanisms, presents a unique paradigm in oncology. Despite its proven efficacy, its broad application is hindered by significant challenges in optimizing treatment delivery for individual patients. This review synthesizes the landscape of advanced computational strategies designed to overcome these barriers. We argue that personalizing TTFields therapy requires tackling three interdependent obstacles: achieving accurate electric field dosimetry, ensuring thermal safety, and enabling adaptive treatment planning. this review systematically analyzes the state-of-the-art computational solutions corresponding to each challenge. We first examine patient-specific electric field modeling, emphasizing the critical roles of high-fidelity segmentation and quantitative dosimetric criteria. We then delve into thermal safety analysis, focusing on coupled electro-thermal simulations for predicting and mitigating thermal risks. Finally, we explore the multifaceted approaches to personalization, reviewing the convergence of algorithmic array layout optimization, real-time monitoring systems, and synergistic surgical interventions. By structuring the current body of research within this "problem-solution" framework, this review provides a clear and cohesive synthesis of how computational engineering is paving the way for a new era of precise, safe, and adaptive TTFields therapy.