Impact of glioma peritumoral edema, tumor size, and tumor location on alternating electric fields (AEF) therapy in realistic 3D rat glioma models: a computational study.

Objective.Alternating electric fields (AEF) therapy is a treatment modality for patients with glioblastoma. Tumor characteristics such as size, location, and extent of peritumoral edema may affect the AEF strength and distribution. We evaluated the sensitivity of the AEFs in a realistic 3D rat glioma model with respect to these properties.Approach.The electric properties of the peritumoral edema were varied based on calculated and literature-reported values. Models with different tumor composition, size, and location were created. The resulting AEFs were evaluated in 3D rat glioma models.Main results.In all cases, a pair of 5 mm diameter electrodes induced an average field strength >1 V cm-1. The simulation results showed that a negative relationship between edema conductivity and field strength was found. As the tumor core size was increased, the average field strength increased while the fraction of the shell achieving >1.5 V cm-1decreased. Increasing peritumoral edema thickness decreased the shell's mean field strength. Compared to rostrally/caudally, shifting the tumor location laterally/medially and ventrally (with respect to the electrodes) caused higher deviation in field strength.Significance.This study identifies tumor properties that are key drivers influencing AEF strength and distribution. The findings might be potential preclinical implications.

Tumor treating fields increases blood-brain barrier permeability and relative cerebral blood volume in patients with glioblastoma.

BACKGROUND AND OBJECTIVE: 200 kHz tumor treating fields (TTFields) is clinically approved for newly-diagnosed glioblastoma (nGBM). Because its effects on conventional surveillance MRI brain scans are equivocal, we investigated its effects on perfusion MRI (pMRI) brain scans. METHODS: Each patient underwent institutional standard pMRI: dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) pMRI at three time points: baseline, 2-, and 6-months on-adjuvant therapy. At each timepoint, the difference between T1 pre- versus post-contrast tumor volume (ΔT1) and these pMRI metrics were evaluated: normalized and standardized relative cerebral blood volume (nRCBV, sRCBV); fractional plasma volume (Vp), volume of extravascular extracellular space (EES) per volume of tissue (Ve), blood-brain barrier (BBB) permeability (Ktrans), and time constant for gadolinium reflux from EES back into the vascular system (Kep). Between-group comparisons were performed using rank-sum analysis, and bootstrapping evaluated likely reproducibility of the results. RESULTS: Among 13 pMRI datasets (11 nGBM, 2 recurrent GBM), therapies included temozolomide-only (n = 9) and temozolomide + TTFields (n = 4). No significant differences were found in patient or tumor characteristics. Compared to temozolomide-only, temozolomide + TTFields did not significantly affect the percent-change in pMRI metrics from baseline to 2 months. But during the 2- to 6-month period, temozolomide + TTFields significantly increased the percent-change in nRCBV (+26.9% [interquartile range 55.1%] vs -39.1% [37.0%], p = 0.049), sRCBV (+9.5% [39.7%] vs -30.5% [39.4%], p = 0.049), Ktrans (+54.6% [1768.4%] vs -26.9% [61.2%], p = 0.024), Ve (+111.0% [518.1%] vs -13.0% [22.5%], p = 0.048), and Vp (+98.8% [2172.4%] vs -24.6% [53.3%], p = 0.024) compared to temozolomide-only. CONCLUSION: Using pMRI, we provide initial in-human validation of pre-clinical studies regarding the effects of TTFields on tumor blood volume and BBB permeability in GBM.

Electric field distributions in realistic 3D rat head models during alternating electric field (AEF) therapy: a computational study.

Objective.Application of alternating electrical fields (AEFs) in the kHz range is an established treatment modality for primary and recurrent glioblastoma. Preclinical studies would enable innovations in treatment monitoring and efficacy, which could then be translated to benefit patients. We present a practical translational process converting image-based data into 3D rat head models for AEF simulations and study its sensitivity to parameter choices.Approach.Five rat head models composed of up to 7 different tissue types were created, and relative permittivity and conductivity of individual tissues obtained from the literature were assigned. Finite element analysis was used to model the AEF strength and distribution in the models with different combinations of head tissues, a virtual tumor, and an electrode pair.Main results.The simulations allowed for a sensitivity analysis of the AEF distribution with respect to different tissue combinations and tissue parameter values.Significance.For a single pair of 5 mm diameter electrodes, an average AEF strength inside the tumor exceeded 1.5 V cm-1, expected to be sufficient for a relevant therapeutic outcome. This study illustrates a robust and flexible approach for simulating AEF in different tissue types, suitable for preclinical studies in rodents and translatable to clinical use.