Impact of Peritumoral Edema during Tumor Treatment Field Therapy: A Computational Modelling Study

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Abstract

Background: Tumor treatment fields (TTFie-lds) are an approved adjuvant therapy for glioblastoma (GBM). The magnitude of applied electrical field has been shown to be related to the anti-tumoral response. However, peritumoral edema may result in shunting of electrical current around the tumor, thereby reducing the intra-tumoral electric field. In this study, we systematically address this issue with computational simulations. Methods: Finite element models are created of a human head with varying amounts of peritumoral edema surrounding a virtual tumor. The electric field distribution was simulated using the standard TTFields electrode montage. Electric field magnitude was extracted from the tumor and related to edema thickness. Two patient specific models were created to confirm these results. Results: The inclusion of peritumoral edema decreased the average magnitude of the electric field within the tumor. In the model considering a frontal tumor and an anterior-posterior electrode configuration, ≥6 mm of peritumoral edema decreased the electric field by 52%. In the patient specific models, peritumoral edema decreased the electric field magnitude within the tumor by an average of 26%. The effect of peritumoral edema on the electric field distribution was spatially heterogenous, being most significant at the tissue interface between edema and tumor. Conclusions: The inclusion of peritumoral edema during TTFields modelling may have a dramatic effect on the predicted electric field magnitude within the tumor. Given the importance of electric field magnitude for the anti-tumoral effects of TTFields, the presence of edema should be considered both in future modelling studies and when planning TTField therapy.

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Lang, S. T., Gan, L. S., McLennan, C., Monchi, O., & Kelly, J. J. P. (2020). Impact of Peritumoral Edema during Tumor Treatment Field Therapy: A Computational Modelling Study. IEEE Transactions on Biomedical Engineering, 67(12), 3327–3338. https://doi.org/10.1109/TBME.2020.2983653

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