RESUMEN
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.
RESUMEN
Purpose: Cerebral edema is an important component of brain metastasis, and its presence may alter the distribution of tumor-treating fields (TTFields). We therefore performed a computational study to model the extent of this alteration according to various edema conditions associated with the metastasis. Methods and Materials: Postacquisition magnetic resonance imaging data sets were obtained from 2 patients with solitary brain metastases from non-small cell lung cancer. After delineation of various anatomies, a 3-dimensional finite element mesh model was generated and then solved for the distribution of applied electric fields, rate of energy deposition, and current density at the gross tumor volume (GTV), edema, and other cranial structures. Electric field-volume histograms, specific absorption rate-volume histograms, and current density-volume histograms were generated, by which plan quality metrics were derived from and used to evaluate relative differences in field coverage between models under various conditions. Results: Changes in the conductivity of cerebral edema altered the electric fields, rate of energy deposition, and current density at the GTV region. At the cerebral edema region, increasing electric conductivity of the edema only decreased the electric fields and rate of energy deposition while the current density increased. The ratio of edema-to-tumor is also important because the plan quality metrics increased linearly when the edema-to-GTV ratio decreased, and increased vice versa. Furthermore, a conductive necrotic core additionally altered the distribution of TTFields according to the plan quality metrics. Conclusions: Our modeling study demonstrated that cerebral edema alters the distribution of applied TTFields in patients. Personalized treatment planning will need to take into account the modulating effects of cerebral edema on TTFields as well as additional effects from a necrotic core inside the GTV.