Body Fluids Modulate Propagation of Tumor Treating Fields

Effects of craniectomy defect on tumor-treating fields

Background

Tumor-treating fields (TTFields) are alternating electric fields approved for the treatment of glioblastoma. They must penetrate through the skull to reach the gross tumor volume (GTV) in the brain. Since the skull is an attenuator of electric fields, removal of a section of cortical bone by craniectomy may facilitate the delivery of TTFields into the GTV.

Methods

We identified a glioblastoma patient who underwent craniectomy for evacuation of a subdural empyema. The patient subsequently received standard adjuvant treatment with TTFields plus temozolomide without replacement of the skull defect. Post-acquisition magnetic resonance imaging datasets were obtained from this index patient and 2 others for virtual craniectomy analysis. After anatomic delineation, a 3-dimensional finite element mesh was generated and then solved for the distribution of applied electric fields, rate of energy deposition, and current density at the GTV.

Results

The geometry of craniectomy defect alone, with or without burr holes, did not alter TTFields delivery to GTV. Biomaterials filling the defect could significantly influence electric field penetration, particularly when they are highly conductive at 10 S/m or 7.76 × 106 S/m as in tantalum. The ratio of GTV relative to defect size also enhanced or attenuated TTFields coverage when the GTV was expanded or eroded, respectively.

Conclusions

Craniectomy, biomaterials filling the defect, and the ratio of GTV relative to defect size may interact in a combinatorial fashion in modulating TTFields penetration into the brain. These findings are clinically relevant for personalized TTFields treatment.

Prediction of intracranial electric field strength and analysis of treatment protocols in tumor electric field therapy targeting gliomas of the brain

BACKGROUND AND OBJECTIVE

Tumor Electric Field Therapy (TEFT) is a new treatment for glioblastoma cells with significant effect and few side effects. However, it is difficult to directly measure the intracranial electric field generated by TEFT, and the inability to control the electric field intensity distribution in the tumor target area also limits the clinical therapeutic effect of TEFT. It is a safe and effective way to construct an efficient and accurate prediction model of intracranial electric field intensity of TEFT by numerical simulation.

METHODS

Different from the traditional methods, in this study, the brain tissue was segmented based on the MRI data of patients with retained spatial location information, and the spatial position of the brain tissue was given the corresponding electrical parameters after segmentation. Then, a single geometric model of the head profile with the transducer array is constructed, which is assembled with an electrical parameter matrix containing tissue position information. After applying boundary conditions on the transducer, the intracranial electric field intensity could be solved in the frequency domain. The effects of transducer array mode, load voltage and voltage frequency on the intracranial electric field strength were further analyzed. Finally, planning system software was developed for optimizing TEFT treatment regimens for patients.

RESULTS

Experimental validation and comparison with existing results demonstrate the proposed method has a more efficient and pervasive modeling approach with higher computational accuracy while preserving the details of MRI brain tissue structure completely. In the optimization analysis of treatment protocols, it was found that increasing the load voltage could effectively increase the electric field intensity in the target area, while the effect of voltage frequency on the electric field intensity was very limited.

CONCLUSIONS

The results showed that adjusting the transducer array mode was the key method for making targeted treatment plans. The proposed method is capable prediction of intracranial electric field strength with high accuracy and provide guidance for the design of the TEFT therapy process. This study provides a valuable reference for the application of TEFT in clinical practice.

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.