Abstract PO-076: First steps towards a framework for Tumor Treating Fields dosimetry and treatment planning
Authors: Zeev Bomzon, Noa Urman, Shay Levi, Ariel Naveh
Journal: Clinical Cancer Research (2021)

Abstract Introduction: In 2019 a study establishing the connection between Tumor Treating Fields (dose) at the tumor bed and overall survival in newly diagnosed Glioblastoma patients was published [1]. The investigators created realistic computational models of 340 newly diagnosed Glioblastoma patients that received TTFields as part of the EF-14 clinical trial. Computational models of the patients were created, and finite element simulations used to evaluate TTFields dose at the tumor bed comprising the region of enhancing tumor as well as a 3mm boundary zone surrounding the tumor and resection cavity. Their analysis showed a connection between the average field power of the field delivered to this region and patient survival. This study provide rationale for TTFields treatment planning, in which computational models are used in order to determine how best to place TTFields transducer arrays on the body to enhance patient outcome. Here we discuss a workflow we have developed for performing TTFields treatment planning a practical manner. Methods: TTFields treatment planning involves several steps including: (a) importing of patient imaging data into the treatment planning system (b) creation of an accurate patient model (c) defining a target region-the region in which TTFields dose should be optimized (d) optimization phase in which numerical simulations and optimization algorithms are used to optimal placement of the arrays (referred to as a treatment plan) (d) evaluation of the treatment plan and sign off. Here we present a practical framework for this procedure. Results: To framework utilizes a combination of T1c MRI and CT images in order to create a patient model. The images are first fused and the patient model created by semi-automatic segmentation of the images. Electric properties are assigned to each tissue type according to empirical values reported in the literature. The user selects the target region in which to optimize TTFields dose. Standard practice is to define a target region consistent with that used by Ballo et. al. [1]. Model quality is evaluated by the user, and if sufficient, optimization is initiated. During optimization, an iterative algorithm incorporating finite element simulations is used to identify optimal array layouts. The algorithm attempts to identify a layout that maximizes TTFields dose in the target region. Finally, the user is presented with a small set of (up to 5) layouts including the optimal layout. A set of color maps and dose Volume Histograms enable the user to select a treatment plan for the patient. Summary: We have developed a practical framework for TTFields treatment planning that in the future may be integrated into standard clinical practice when treating patients with TTFields. Citation Format: Zeev Bomzon, Noa Urman, Shay Levi, Ariel Naveh. First steps towards a framework for Tumor Treating Fields dosimetry and treatment planning [abstract]. In: Proceedings of the AACR Virtual Special Conference on Radiation Science and Medicine; 2021 Mar 2-3. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(8_Suppl):Abstract nr PO-076.