Computational Analysis of Tumor Treating Fields for Non-Small Cell Lung Cancer in Full Thoracic Models

Abstract

Purpose: Tumor Treating Fields (TTFields) are alternating electric fields at 150 to 200 kHz that exert their anticancer effect by destroying tumor cells when they undergo mitosis. TTFields are currently being tested in patients with non-small cell lung cancer with advanced disease (NCT02973789) and those with brain metastasis (NCT02831959). However, the distribution of these fields within the thoracic compartment remains poorly understood. Methods and Materials: Using positron emission tomography–computed tomography image data sets obtained from a series of 4 patients with poorly differentiated adenocarcinoma, the positron emission tomography–positive gross tumor volume (GTV), clinical target volume (CTV), and structures from the chest surface to the intrathoracic compartment were manually segmented, followed by 3-dimensional physics simulation and computational modeling using finite element analysis. Electric field-volume histograms, specific absorption rate-volume histograms, and current density-volume histograms were generated to produce plan quality metrics (95%, 50%, and 5% volumes) for quantitative comparisons between models. Results: Unlike other organs in the body, the lungs have a large volume of air, which has a very low electric conductivity value. Our comprehensive and individualized models demonstrated heterogeneity in electric field penetration to the GTVs with differences upwards of 200% and yielded a diverse range of TTFields distributions. Target contact with the conductive pleura intensified TTFields at the GTV and CTV. Furthermore, in a sensitivity analysis, varying electric conductivity and mass density of the CTV altered TTFields coverage to both the CTV and GTV. Conclusions: Personalized modeling is important to accurately estimate target coverage at the tumor volumes and surrounding normal tissue structures in the thorax.