Spatiotemporally dynamic electric fields for brain cancer treatment: anin vitroinvestigation.

Objective. The treatment of glioblastoma (GBM) using low intensity electric fields (∼1 V cm-1) is being investigated using multiple implanted bioelectrodes, which was termed intratumoral modulation therapy (IMT). Previous IMT studies theoretically optimized treatment parameters to maximize coverage with rotating fields, which required experimental investigation. In this study, we employed computer simulations to generate spatiotemporally dynamic electric fields, designed and purpose-built an IMT device forin vitroexperiments, and evaluated the human GBM cellular responses to these fields.Approach. After measuring the electrical conductivity of thein vitroculturing medium, we designed experiments to evaluate the efficacy of various spatiotemporally dynamic fields: (a) different rotating field magnitudes, (b) rotating versus non-rotating fields, (c) 200 kHz versus 10 kHz stimulation, and (d) constructive versus destructive interference. A custom printed circuit board (PCB) was fabricated to enable four-electrode IMT in a 24-well plate. Patient derived GBM cells were treated and analyzed for viability using bioluminescence imaging.Main results. The optimal PCB design had electrodes placed 6.3 mm from the center. Spatiotemporally dynamic IMT fields at magnitudes of 1, 1.5, and 2 V cm-1reduced GBM cell viability to 58%, 37% and 2% of sham controls respectively. Rotating versus non-rotating, and 200 kHz versus 10 kHz fields showed no statistical difference. The rotating configuration yielded a significant reduction (p< 0.01) in cell viability (47 ± 4%) compared to the voltage matched (99 ± 2%) and power matched (66 ± 3%) destructive interference cases.Significance. We found the most important factors in GBM cell susceptibility to IMT are electric field strength and homogeneity. Spatiotemporally dynamic electric fields have been evaluated in this study, where improvements to electric field coverage with lower power consumption and minimal field cancellations has been demonstrated. The impact of this optimized paradigm on cell susceptibility justifies its future use in preclinical and clinical trial investigations.

Planning system for the optimization of electric field delivery using implanted electrodes for brain tumor control.

BACKGROUND: The use of non-ionizing electric fields from low-intensity voltage sources (< 10 V) to control malignant tumor growth is showing increasing potential as a cancer treatment modality. A method of applying these low-intensity electric fields using multiple implanted electrodes within or adjacent to tumor volumes has been termed as intratumoral modulation therapy (IMT). PURPOSE: This study explores advancements in the previously established IMT optimization algorithm, and the development of a custom treatment planning system for patient-specific IMT. The practicality of the treatment planning system is demonstrated by implementing the full optimization pipeline on a brain phantom with robotic electrode implantation, postoperative imaging, and treatment stimulation. METHODS: The integrated planning pipeline in 3D Slicer begins with importing and segmenting patient magnetic resonance images (MRI) or computed tomography (CT) images. The segmentation process is manual, followed by a semi-automatic smoothing step that allows the segmented brain and tumor mesh volumes to be smoothed and simplified by applying selected filters. Electrode trajectories are planned manually on the patient MRI or CT by selecting insertion and tip coordinates for a chosen number of electrodes. The electrode tip positions and stimulation parameters (phase shift and voltage) can then be optimized with the custom semi-automatic IMT optimization algorithm where users can select the prescription electric field, voltage amplitude limit, tissue electrical properties, nearby organs at risk, optimization parameters (electrode tip location, individual contact phase shift and voltage), desired field coverage percent, and field conformity optimization. Tables of optimization results are displayed, and the resulting electric field is visualized as a field-map superimposed on the MR or CT image, with 3D renderings of the brain, tumor, and electrodes. Optimized electrode coordinates are transferred to robotic electrode implantation software to enable planning and subsequent implantation of the electrodes at the desired trajectories. RESULTS: An IMT treatment planning system was developed that incorporates patient-specific MRI or CT, segmentation, volume smoothing, electrode trajectory planning, electrode tip location and stimulation parameter optimization, and results visualization. All previous manual pipeline steps operating on diverse software platforms were coalesced into a single semi-automated 3D Slicer-based user interface. Brain phantom validation of the full system implementation was successful in preoperative planning, robotic electrode implantation, and postoperative treatment planning to adjust stimulation parameters based on actual implant locations. Voltage measurements were obtained in the brain phantom to determine the electrical parameters of the phantom and validate the simulated electric field distribution. CONCLUSIONS: A custom treatment planning and implantation system for IMT has been developed in this study and validated on a phantom brain model, providing an essential step in advancing IMT technology toward future clinical safety and efficacy investigations.

Optimization of multi-electrode implant configurations and programming for the delivery of non-ablative electric fields in intratumoral modulation therapy.

PURPOSE: Application of low intensity electric fields to interfere with tumor growth is being increasingly recognized as a promising new cancer treatment modality. Intratumoral modulation therapy (IMT) is a developing technology that uses multiple electrodes implanted within or adjacent tumor regions to deliver electric fields to treat cancer. In this study, the determination of optimal IMT parameters was cast as a mathematical optimization problem, and electrode configurations, programming, optimization, and maximum treatable tumor size were evaluated in the simplest and easiest to understand spherical tumor model. The establishment of electrode placement and programming rules to maximize electric field tumor coverage designed specifically for IMT is the first step in developing an effective IMT treatment planning system. METHODS: Finite element method electric field computer simulations for tumor models with 2 to 7 implanted electrodes were performed to quantify the electric field over time with various parameters, including number of electrodes (2 to 7), number of contacts per electrode (1 to 3), location within tumor volume, and input waveform with relative phase shift between 0 and 2π radians. Homogeneous tissue specific conductivity and dielectric values were assigned to the spherical tumor and surrounding tissue volume. In order to achieve the goal of covering the tumor volume with a uniform threshold of 1 V/cm electric field, a custom least square objective function was used to maximize the tumor volume covered by 1 V/cm time averaged field, while maximizing the electric field in voxels receiving less than this threshold. An additional term in the objective function was investigated with a weighted tissue sparing term, to minimize the field to surrounding tissues. The positions of the electrodes were also optimized to maximize target coverage with the fewest number of electrodes. The complexity of this optimization problem including its non-convexity, the presence of many local minima, and the computational load associated with these stochastic based optimizations led to the use of a custom pattern search algorithm. Optimization parameters were bounded between 0 and 2π radians for phase shift, and anywhere within the tumor volume for location. The robustness of the pattern search method was then evaluated with 50 random initial parameter values. RESULTS: The optimization algorithm was successfully implemented, and for 2 to 4 electrodes, equally spaced relative phase shifts and electrodes placed equidistant from each other was optimal. For 5 electrodes, up to 2.5 cm diameter tumors with 2.0 V, and 4.1 cm with 4.0 V could be treated with the optimal configuration of a centrally placed electrode and 4 surrounding electrodes. The use of 7 electrodes allow for 3.4 cm diameter coverage at 2.0 V and 5.5 cm at 4.0 V. The evaluation of the optimization method using 50 random initial parameter values found the method to be robust in finding the optimal solution. CONCLUSIONS: This study has established a robust optimization method for temporally optimizing electric field tumor coverage for IMT, with the adaptability to optimize a variety of parameters including geometrical and relative phase shift configurations.

Diffuse intrinsic pontine glioma cells are vulnerable to low intensity electric fields delivered by intratumoral modulation therapy.

INTRODUCTION: Diffuse intrinsic pontine glioma (DIPG) is a high fatality pediatric brain cancer without effective treatment. The field of electrotherapeutics offers new potential for other forms of glioma but the efficacy of this strategy has not been reported for DIPG. This pilot study evaluated the susceptibility of patient-derived DIPG cells to low intensity electric fields delivered using a developing technology called intratumoral modulation therapy (IMT). METHODS: DIPG cells from autopsy specimens were treated with a custom-designed, in vitro IMT system. Computer-generated electric field simulation was performed to quantify IMT amplitude and distribution using continuous, low intensity, intermediate frequency stimulation parameters. Treatment groups included sham, IMT, temozolomide (TMZ) chemotherapy and radiation therapy (RT). The impact of single and multi-modality therapy was compared using spectrophotometric and flow cytometry viability analyses. RESULTS: DIPG cells exhibited robust, consistent susceptibility to IMT fields that significantly reduced cell viability compared to untreated control levels. The ratio of viable:non-viable DIPG cells transformed from ~ 6:1 in sham-treated to ~ 1.5:1 in IMT-treated conditions. The impact of IMT was similar to that of dual modality TMZ-RT therapy and the addition of IMT to this treatment combination dramatically reduced DIPG cell viability to ~ 20% of control values. CONCLUSIONS: This proof-of-concept study provides a novel demonstration of marked DIPG cell susceptibility to low intensity electric fields delivered using IMT. The potent impact as a monotherapy and when integrated into multi-modality treatment platforms justifies further investigations into the potential of IMT as a critically needed biomedical innovation for DIPG.

Preclinical outcomes of Intratumoral Modulation Therapy for glioblastoma.

Glioblastoma (GBM) is the leading cause of high fatality cancer arising within the adult brain. Electrotherapeutic approaches offer new promise for GBM treatment by exploiting innate vulnerabilities of cancer cells to low intensity electric fields. This report describes the preclinical outcomes of a novel electrotherapeutic strategy called Intratumoral Modulation Therapy (IMT) that uses an implanted stimulation system to deliver sustained, titratable, low intensity electric fields directly across GBM-affected brain regions. This pilot technology was applied to in vitro and animal models demonstrating significant and marked reduction in tumor cell viability and a cumulative impact of concurrent IMT and chemotherapy in GBM. No off target neurological effects were observed in treated subjects. Computational modeling predicted IMT field optimization as a means to further bolster treatment efficacy. This sentinel study provides new support for defining the potential of IMT strategies as part of a more effective multimodality treatment platform for GBM.

In Vitro Validation of Intratumoral Modulation Therapy for Glioblastoma.

BACKGROUND/AIM: This proof-of-concept study evaluated the antitumor impact of a direct electrical stimulation technique, termed intratumoral modulation therapy (IMT) on glioblastoma (GBM) cells. MATERIALS AND METHODS: An in vitro IMT model comprised of a calibrated electrode to deliver continuous, low-intensity stimulation within GBM preparations. Viability and apoptosis assays were performed in treated immortalized and patient-derived GBM cells, and post-mitotic neurons. IMT was delivered alone and with temozolomide, or gene silencing of the tumor-promoting chaperone, heat-shock protein 27 (HSP27). RESULTS: GBM cells, but not neurons, exhibited >40% loss of viability, caspase-3 activation and apoptosis with IMT. Cell death was modest with temozolomide alone (30%) but increased significantly with concomitant IMT (70%). HSP27 silencing alone produced 30% viability loss, with significant enhancement of target knockdown and GBM cell death (65%), when combined with IMT. CONCLUSION: These findings warrant further evaluation of IMT as a potential novel therapeutic strategy for GBM.

Impaired percent alpha variability on continuous electroencephalography is associated with thalamic injury and predicts poor long-term outcome after human traumatic brain injury.

Continuous electroencephalography (cEEG) is potentially useful in determining prognosis in patients with traumatic brain injuries (TBI). The objective of this prospective, observational cohort study was to determine if the percent alpha variability (PAV) on cEEG was predictive of outcome following TBI. Injury characteristics were indexed to assess whether lesions in specific cerebral loci were correlated with PAV and patient recovery. Fifty-three TBI patients were studied using cEEG recording and serial neuroimaging. Clinical recovery was assessed at regular intervals in hospital and following discharge. The principal outcome measures included the mean 3-day PAV score, the 7-day PAV pattern, delineation of the anatomical sites of brain injury, and the 6-month clinical outcome, as measured by the Glasgow Outcome Scale (GOS). Significant univariate (p = 0.030) and multivariate (p = 0.008) relations were identified between PAV and GOS scores. PAV offered good discrimination between favorable and unfavorable 6-month outcomes (AUC 0.76) and, with a cutpoint of 0.20, had a sensitivity of 87% and negative predictive value of 82%. Multivariate modeling revealed that injuries of the thalamus (p = 0.009) and basal ganglia (p = 0.016), and the presence of diffuse edema (p = 0.009), were the key anatomical predictors of PAV. Brainstem injuries (p = 0.020) and indicators of diffuse cerebral trauma, such as deep white matter shearing (p = 0.036) and multiple subcortical lesions (p = 0.033), were the principal determinants of 6-month recovery. Inclusion of PAV enhanced the accuracy of prediction models that encompassed a selective combination of clinical and anatomical variables (adjusted R(2) = 0.458, p < 0.001). The two main results of this study are (1) PAV is a sensitive predictor of 6-month clinical outcomes following TBI, and (2) injury to the thalamus is related to impaired PAV. PAV appears best utilized as a functional adjunct to traditional clinical and anatomical predictors.