A Working TTFields Therapy Framework for Patient-Specific Segmentation-Based Treatment Planning and Dosimetry

Abstract

Previously reported data support the notion that patient-specific treatment planning in patients with newly diagnosed glioblastoma (GBM) could positively impact patient outcomes like overall survival and progression free survival and predictably affect imaging progression patterns (Ballo et al 2019; Glas et al 2021). These findings provide the grounds for a TTFields dosimetry and patient-specific segmentation-based treatment planning (SBTP) paradigm. This paradigm allows optimized delivery of TTFields to target regions of interest (ROIs) and ability to adjust the treatment during therapy. In this study, we describe a working framework for TTFields SBTP. The working framework consists of the following process: First, a patient's high-resolution imaging data (MRI with or without a CT) is imported from the institution's PACS. The image is segmented to identify tissue types using a combination of automatic and semi-automatic algorithms. During this stage, the user indicates the target ROI subject to optimization. Then, a computational model of the patient is created in which typical electrical properties are allocated to each tissue type based on empirical measurements and/or literature. At this point, the user can mark avoidance zones on the skin identifying areas where the transducer arrays (TAs) should not be placed. Next, dedicated algorithms identify optimal arrangements of TAs to produce several options of TA layouts. Further, quantitative and qualitative evaluation tools such as color maps, iso-surfaces, and dose volume histogram (DVH) curves, are applied to choose the layouts that achieve the optimal distribution of TTFields therapy for each patient. Finally, each patient receives two SBTP to allow switching between the layouts in order to mitigate the risk of skin irritation. Over 60 image sets from GBM patients were used to test the SBTP system. Our experience demonstrates a viable working framework that has the potential to boost TTFields delivery to target ROIs. This working framework offers qualitative and quantitative tools for SBTP and streamlines the process of personalized treatment, allowing physicians to optimize treatment with TTFields therapy. Additionally, this system provides tools for developing an adaptive patient-specific SBTP in response to any clinical need (e.g., disease progression).