End-to-end workflow for finite element analysis of tumor treating fields in glioblastomas

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.

Body Fluids Modulate Propagation of Tumor Treating Fields

Tumor treating fields (TTFields) are nonionizing alternating electric fields that have anticancer properties. After the initial approval for use in patients with recurrent glioblastoma in 2011 and newly diagnosed glioblastomas in 2015, they are now being tested in those with advanced lung cancer, ovarian carcinoma, and pancreatic cancer. Unlike ionizing radiation therapy, TTFields have nonlinear propagation characteristics; therefore, it is difficult for clinicians to recognize intuitively the location where these fields have the most impact. However, finite element analysis offers a means of delineating TTFields in the human body. Our analyses in the brain, pelvis, and thorax revealed that cerebrospinal fluid, edema, urine, ascites, pleural fluid, and necrotic core within a tumor greatly influence their distribution within these body cavities. Our observations thus provided a unified framework on the role of these compartmentalized fluids in influencing the propagation of TTFields.

Skull defect increases the tumor treating fields strength without detrimental thermogenic effect: A computational simulating research

BACKGROUND

Tumor treating fields (TTFields) is an FDA-approved adjuvant therapy for glioblastoma. The distribution of an applied electric field has been shown to be governed by distinct tissue structures and electrical conductivity. Of all the tissues the skull plays a significant role in modifying the distribution of the electric field due to its large impedance. In this study, we studied how remodeling of the skull would affect the therapeutic outcome of TTFields, using a computational approach.

METHODS

Head models were created from the head template ICBM152 and five realistic head models. The electric field distribution was simulated using the default TTFields array layout. To study the impact of the skull on the electric field, we compared three cases, namely, intact skull, defective skull, and insulating process, wherein a thin electrical insulating layer was added between the transducer and the hydrogel. The electric field strength and heating power were calculated using the FEM (finite element method).

RESULTS

Removing the skull flap increased the average field strength at the tumor site, without increasing the field strength of "brain". The ATVs of the supratentorial tumors were enhanced significantly. Meanwhile, the heating power of the gels increased, especially those overlapping the skull defect site. Insulation lightly decreased the electric field strength and significantly decreased the heating power in deep tumor models.

CONCLUSION

Our simulation results showed that a skull defect was beneficial for superficial tumors but had an adverse effect on deep tumors. Skull removal should be considered as an optional approach in future TTFields therapy to enhance its efficacy. An insulation process could be used as a joint option to reduce the thermogenic effect of skull defect. If excessive increase in heating power is observed in certain patients, insulating material could be used to mitigate overheating without sacrificing the therapeutic effect of TTFields.

Guidelines for Burr Hole Surgery in Combination With Tumor Treating Fields for Glioblastoma: A Computational Study on Dose Optimization and Array Layout Planning

Tumor treating fields (TTFields) is an anti-cancer technology increasingly used for the treatment of glioblastoma. Recently, cranial burr holes have been used experimentally to enhance the intensity (dose) of TTFields in the underlying tumor region. In the present study, we used computational finite element methods to systematically characterize the impact of the burr hole position and the TTFields transducer array layout on the TTFields distribution calculated in a realistic human head model. We investigated a multitude of burr hole positions and layouts to illustrate the basic principles of optimal treatment planning. The goal of the paper was to provide simple rules of thumb for physicians to use when planning the TTFields in combination with skull remodeling surgery. Our study suggests a number of key findings, namely that (1) burr holes should be placed directly above the region of interest, (2) field enhancement occurs mainly underneath the holes, (3) the ipsilateral array should directly overlap the holes and the contralateral array should be placed directly opposite, (4) arrays in a pair should be placed at far distance and not close to each other to avoid current shunting, and finally (5) rotation arrays around their central normal axis can be done without diminishing the enhancing effect of the burr holes. Minor deviations and adjustments (<3 cm) of arrays reduces the enhancement to some extent although the procedure is still effective in these settings. In conclusion, our study provides simple guiding principles for implementation of dose-enhanced TTFields in combination with burr-holes. Future studies are required to validate our findings in additional models at the patient specific level.

Finite element analysis of Tumor Treating Fields in a patient with posterior fossa glioblastoma

INTRODUCTION

Tumor Treating Fields (TTFields) are alternating electric fields at 200 kHz that disrupt tumor cells as they undergo mitosis. Patient survival benefit has been demonstrated in randomized clinical trials but much of the data are available only for supratentorial glioblastomas. We investigated a series of alternative array configurations for the posterior fossa to determine the electric field coverage of a cerebellar glioblastoma.

METHODS

Semi-automated segmentation of neuro-anatomical structures was performed while the gross tumor volume (GTV) was manually delineated. A three-dimensional finite-element mesh was generated and then solved for field distribution.

RESULTS

Compared to the supratentorial array configuration, the alternative array configurations consist of posterior displacement the 2 lateral opposing arrays and inferior displacement of the posteroanterior array, resulting in an average increase of 46.6% electric field coverage of the GTV as measured by the area under the curve of the electric field-volume histogram (EAUC). Hotspots, or regions of interest with the highest 5% of TTFields intensity (E5%), had an average increase of 95.6%. Of the 6 posterior fossa configurations modeled, the PAHorizontal arrangement provided the greatest field coverage at the GTV when the posteroanterior array was placed centrally along the patient's posterior neck and horizontally parallel, along the longer axis, to the coronal plane of the patient's head. Varying the arrays also produced hotspots proportional to TTFields coverage.

CONCLUSIONS

Our finite element modeling showed that the alternative array configurations offer an improved TTFields coverage to the cerebellar tumor compared to the conventional supratentorial configuration.