Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma

The Synergy of Thermal and Non-Thermal Effects in Hyperthermic Oncology

BACKGROUND

Modulated electro-hyperthermia (mEHT) is unique due to its combination of thermal and non-thermal effects.

METHOD

This report summarizes the literature on the effects of mEHT observed in vitro and in vivo.

RESULTS

The thermal and electrical heterogeneity of tissues allows the radiofrequency signal to selectively target malignant tissue. The applied modulation appears to activate various apoptotic pathways, predominantly leading to immunogenic cell death (ICD). ICD promotes the release of damage-associated molecular patterns, potentially producing tumour-specific antigen-presenting cells. This abscopal-type effect may target distant metastases while treating the primary tumour locally. This immune memory effect is like vaccination mechanisms.

CONCLUSIONS

The application of mEHT has the potential to expand from local to systemic disease, enabling the simultaneous treatment of micro- and macro-metastases.

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.

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.

Tumor-treating fields dosimetry in glioblastoma: Insights into treatment planning, optimization, and dose-response relationships

Tumor-treating fields (TTFields) are currently a Category 1A treatment recommendation by the US National Comprehensive Cancer Center for patients with newly diagnosed glioblastoma. Although the mechanism of action of TTFields has been partly elucidated, tangible and standardized metrics are lacking to assess antitumor dose and effects of the treatment. This paper outlines and evaluates the current standards and methodologies in the estimation of the TTFields distribution and dose measurement in the brain and highlights the most important principles governing TTFields dosimetry. The focus is on clinical utility to facilitate a practical understanding of these principles and how they can be used to guide treatment. The current evidence for a correlation between TTFields dose, tumor growth, and clinical outcome will be presented and discussed. Furthermore, we will provide perspectives and updated insights into the planning and optimization of TTFields therapy for glioblastoma by reviewing how the dose and thermal effects of TTFields are affected by factors such as tumor location and morphology, peritumoral edema, electrode array position, treatment duration (compliance), array "edge effect," electrical duty cycle, and skull-remodeling surgery. Finally, perspectives are provided on how to optimize the efficacy of future TTFields therapy.

Evaluation of Interfraction Setup Uncertainty of Patients With Glioblastoma Wearing TTFields (Tumor Treating Fields) During Radiation Therapy

PURPOSE

Tumor treating fields (TTFields) with concurrent radiation therapy (RT) might improve the outcome of patients with newly diagnosed glioblastoma. Several trials, including that conducted in our center, have allowed patients to wear TTFields during RT. We aimed to evaluate the setup uncertainty introduced by TTFields and calculate the planning target volume (PTV) margin for clinical reference.

METHODS AND MATERIALS

We collected and analyzed 201 cone beam computed tomography images of 22 patients in our center. Patients with or without TTFields were divided into the control and TTFields groups. We evaluated the setup errors in 6 degrees of freedom and 3 degrees of freedom and the magnitudes in the 3-dimensional vectors. An estimated PTV margin for patients requiring nonimaging-guided RT was recommended.

RESULTS

A significant difference was observed in the longitudinal axis between the TTFields and control groups (P < .05). These results were consistent with that of the intragroup comparison of the TTFields group. The position error of the longitudinal axis (from head to feet) was -0.51 ± 2.05 mm in the TTFields group.

CONCLUSIONS

Wearing TTFields during RT increased the uncertainty, especially in the longitudinal axis, with a system error of 1.40 mm and a random error of 1.28 mm. Daily image guided RT for TTFields patients seems necessary. However, the recommended expansion margin of the PTV is 5 mm for patients requiring nonimage-guided RT to enhance the safety and efficacy of treatment.

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.

Modeling of intracranial tumor treating fields for the treatment of complex high-grade gliomas

Increasing the intensity of tumor treating fields (TTF) within a tumor bed improves clinical efficacy, but reaching sufficiently high field intensities to achieve growth arrest remains challenging due in part to the insulating nature of the cranium. Using MRI-derived finite element models (FEMs) and simulations, we optimized an exhaustive set of intracranial electrode locations to obtain maximum TTF intensities in three clinically challenging high-grade glioma (HGG) cases (i.e., thalamic, left temporal, brainstem). Electric field strengths were converted into therapeutic enhancement ratios (TER) to evaluate the predicted impact of stimulation on tumor growth. Concurrently, conventional transcranial configurations were simulated/optimized for comparison. Optimized intracranial TTF were able to achieve field strengths that have previously been shown capable of inducing complete growth arrest, in 98-100% of the tumor volumes using only 0.54-0.64 A current. The reconceptualization of TTF as a targeted, intracranial therapy has the potential to provide a meaningful survival benefit to patients with HGG and other brain tumors, including those in surgically challenging, deep, or anatomically eloquent locations which may preclude surgical resection. Accordingly, such an approach may ultimately represent a paradigm shift in the use of TTFs for the treatment of brain cancer.

Design of a novel integrated microfluidic chip for continuous separation of circulating tumor cells from peripheral blood cells

Cancer is one of the foremost causes of death globally. Late-stage presentation, inaccessible diagnosis, and treatment are common challenges in developed countries. Detection, enumeration of Circulating Tumor Cells (CTC) as early as possible can reportedly lead to more effective treatment. The isolation of CTC at an early stage is challenging due to the low probability of its presence in peripheral blood. In this study, we propose a novel two-stage, label-free, rapid, and continuous CTC separation device based on hydrodynamic inertial focusing and dielectrophoretic separation. The dominance and differential of wall-induced inertial lift force and Dean drag force inside a curved microfluidic channel results in size-based separation of Red Blood Cells (RBC) and platelets (size between 2-4 µm) from CTC and leukocytes (9-12.2 µm). A numerical model was used to investigate the mechanism of hydrodynamic inertial focusing in a curvilinear microchannel. Simulations were done with the RBCs, platelets, CTCs, and leukocytes (four major subtypes) to select the optimized value of the parameters in the proposed design. In first stage, the focusing behavior of microscale cells was studied to sort leukocytes and CTCs from RBCs, and platelets while viable CTCs were separated from leukocytes based on their inherent electrical properties using dielectrophoresis in the second stage. The proposed design of the device was evaluated for CTC separation efficiency using numerical simulations. This study considered the influence of critical factors like aspect ratio, dielectrophoretic force, channel size, flow rate, separation efficiency, and shape on cell separation. Results show that the proposed device yields viable CTC with 99.5% isolation efficiency with a throughput of 12.2 ml/h.

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.

Elucidating the Innate Immunological Effects of Mild Magnetic Hyperthermia on U87 Human Glioblastoma Cells: An In Vitro Study

Cancer immunotherapies have been approved as standard second-line or in some cases even as first-line treatment for a wide range of cancers. However, immunotherapy has not shown clinically relevant success in glioblastoma (GBM). This is principally due to the brain's "immune-privileged" status and the peculiar tumor microenvironment (TME) of GBM characterized by a lack of tumor-infiltrating lymphocytes and the establishment of immunosuppressive mechanisms. Herein, we explore a local mild thermal treatment, generated via cubic-shaped iron oxide magnetic nanoparticles (size ~17 nm) when exposed to an external alternating magnetic field (AMF), to induce immunogenic cell death (ICD) in U87 glioblastoma cells. In accordance with what has been observed with other tumor types, we found that mild magnetic hyperthermia (MHT) modulates the immunological profile of U87 glioblastoma cells by inducing stress-associated signals leading to enhanced phagocytosis and killing of U87 cells by macrophages. At the same time, we demonstrated that mild magnetic hyperthermia on U87 cells has a modulatory effect on the expression of inhibitory and activating NK cell ligands. Interestingly, this alteration in the expression of NK ligands in U87 cells upon MHT treatment increased their susceptibility to NK cell killing and enhanced NK cell functionality. The overall findings demonstrate that mild MHT stimulates ICD and sensitizes GBM cells to NK-mediated killing by inducing the upregulation of specific stress ligands, providing a novel immunotherapeutic approach for GBM treatment, with potential to synergize with existing NK cell-based therapies thus improving their therapeutic outcomes.

Tumor Treating Fields for Ovarian Carcinoma: A Modeling Study

Purpose

Since the inception of tumor treating fields (TTFields) therapy as a Food and Drug Administration–approved treatment with known clinical efficacy against recurrent and newly diagnosed glioblastoma, various in silico modeling studies have been performed in an effort to better understand the distribution of applied electric fields throughout the human body for various malignancies or metastases.

Methods and Materials

Postacquisition attenuation-corrected positron emission tomography–computed tomography image data sets from 2 patients with ovarian carcinoma were used to fully segment various intrapelvic and intra-abdominal gross anatomic structures. A 3-dimensional finite element mesh model was generated and then solved for the distribution of applied electric fields, rate of energy deposition, and current density at the clinical target volumes (CTVs) and other intrapelvic and intra-abdominal structures. Electric field-volume histograms, specific absorption rate–volume histograms, and current density-volume histograms were generated, by which plan quality metrics were derived from and used to evaluate relative differences in field coverage between models under various conditions.

Results

TTFields therapy distribution throughout the pelvis and abdomen was largely heterogeneous, where specifically the field intensity at the CTV was heavily influenced by surrounding anatomic structures as well as its shape and location. The electric conductivity of the CTV had a direct effect on the field strength within itself, as did the position of the arrays on the surface of the pelvis and/or abdomen.

Conclusion

The combined use of electric field-volume histograms, specific absorption rate-volume histograms, current density-volume histograms, and plan quality metrics enables a personalized method to dosimetrically evaluate patients receiving TTFields therapy for ovarian carcinoma when certain patient- and tumor-specific factors are integrated with the treatment plan.

Non-thermal membrane effects of electromagnetic fields and therapeutic applications in oncology

The temperature-independent effects of electromagnetic fields (EMF) have been controversial for decades. Here, we critically analyze the available literature on non-thermal effects of radiofrequency (RF) and microwave EMF. We present a literature review of preclinical and clinical data on non-thermal antiproliferative effects of various EMF applications, including conventional RF hyperthermia (HT, cRF-HT). Further, we suggest and evaluate plausible biophysical and electrophysiological models to decipher non-thermal antiproliferative membrane effects. Available preclinical and clinical data provide sufficient evidence for the existence of non-thermal antiproliferative effects of exposure to cRF-HT, and in particular, amplitude modulated (AM)-RF-HT. In our model, transmembrane ion channels function like RF rectifiers and low-pass filters. cRF-HT induces ion fluxes and AM-RF-HT additionally promotes membrane vibrations at specific resonance frequencies, which explains the non-thermal antiproliferative membrane effects via ion disequilibrium (especially of Ca²⁺) and/or resonances causing membrane depolarization, the opening of certain (especially Ca²⁺) channels, or even hole formation. AM-RF-HT may be tumor-specific owing to cancer-specific ion channels and because, with increasing malignancy, membrane elasticity parameters may differ from that in normal tissues. Published literature suggests that non-thermal antiproliferative effects of cRF-HT are likely to exist and could present a high potential to improve future treatments in oncology.

Dosimetric impact of the positioning variation of tumor treating field electrodes in the PriCoTTF-phase I/II trial

Purpose

The aim of the present study based on the PriCoTTF‐phase I/II trial is the quantification of skin‐normal tissue complication probabilities of patients with newly diagnosed glioblastoma multiforme treated with Tumor Treating Field (TTField) electrodes, concurrent radiotherapy, and temozolomide. Furthermore, the skin‐sparing effect by the clinically applied strategy of repetitive transducer array fixation around their center position shall be examined.

Material and Methods

Low‐dose cone‐beam computed tomography (CBCT) scans of all fractions of the first seven patients of the PriCoTTF‐phase I/II trial, used for image guidance, were applied for the dosimetric analysis, for precise TTField transducer array positioning and contour delineation. Within this trial, array positioning was varied from fixation‐to‐fixation period with a standard deviation of 1.1 cm in the direction of the largest variation of positioning and 0.7 cm in the perpendicular direction. Physical TTField electrode composition was examined and a respective Hounsfield Unit attributed to the TTField electrodes. Dose distributions in the planning CT with TTField electrodes in place, as derived from prefraction CBCTs, were calculated and accumulated with the algorithm Acuros XB. Dose‐volume histograms were obtained for the first and second 2 mm scalp layer with and without migrating electrodes and compared with those with fixed electrodes in an average position. Skin toxicity was quantified according to Lyman's model. Minimum doses in hot‐spots of 0.05 cm² and 25 cm² (ΔD_0.05cm², ΔD_25cm²) size in the superficial skin layers were analyzed.

Results

Normal tissue complication probabilities (NTCPs) for skin necrosis ranged from 0.005% to 1.474% (median 0.111%) for the different patients without electrodes. NTCP logarithms were significantly dependent on patient (P < 0.0001) and scenario (P < 0.0001) as classification variables. Fixed positioning of TTField arrays increased skin‐NTCP by a factor of 5.50 (95%, CI: 3.66–8.27). The variation of array positioning increased skin‐NTCP by a factor of only 3.54 (95%, CI: 2.36–5.32) (P < 0.0001, comparison to irradiation without electrodes; P = 0.036, comparison to irradiation with fixed electrodes). NTCP showed a significant rank correlation with D25cm² over all patients and scenarios (r_s = 0.76; P < 0.0001).

Conclusion

Skin‐NTCP calculation uncovers significant interpatient heterogeneity and may be used to stratify patients into high‐ and low‐risk groups of skin toxicity. Array position variation may mitigate about one‐third of the increase in surface dose and skin‐NTCP by the TTField electrodes.

A Radio Frequency Magnetoelectric Antenna Prototyping Platform for Neural Activity Monitoring Devices with Sensing and Energy Harvesting Capabilities

This article describes the development of a radio frequency (RF) platform for electromagnetically modulated signals that makes use of a software-defined radio (SDR) to receive information from a novel magnetoelectric (ME) antenna capable of sensing low-frequency magnetic fields with ultra-low magnitudes. The platform is employed as part of research and development to utilize miniaturized ME antennas and integrated circuits for neural recording with wireless implantable devices. To prototype the reception of electromagnetically modulated signals from a sensor, a versatile Universal Software Radio Peripheral (USRP) and the GNU Radio toolkit are utilized to enable real-time signal processing under varying operating conditions. Furthermore, it is demonstrated how a radio frequency signal transmitted from the SDR can be captured by the ME antenna for wireless energy harvesting.

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.

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.

OptimalTTF-1: Enhancing tumor treating fields therapy with skull remodeling surgery. A clinical phase I trial in adult recurrent glioblastoma

BACKGROUND

Preclinical studies suggest that skull remodeling surgery (SR-surgery) increases the dose of tumor treating fields (TTFields) in glioblastoma (GBM) and prevents wasteful current shunting through the skin. SR-surgery introduces minor skull defects to focus the cancer-inhibiting currents toward the tumor and increase the treatment dose. This study aimed to test the safety and feasibility of this concept in a phase I setting.

METHODS

Fifteen adult patients with the first recurrence of GBM were treated with personalized SR-surgery, TTFields, and physician's choice oncological therapy. The primary endpoint was toxicity and secondary endpoints included standard efficacy outcomes.

RESULTS

SR-surgery resulted in a mean skull defect area of 10.6 cm2 producing a median TTFields enhancement of 32% (range 25-59%). The median TTFields treatment duration was 6.8 months and the median compliance rate 90%. Patients received either bevacizumab, bevacizumab/irinotecan, or temozolomide rechallenge. We observed 71 adverse events (AEs) of grades 1 (52%), 2 (35%), and 3 (13%). There were no grade 4 or 5 AEs or intervention-related serious AEs. Six patients experienced minor TTFields-induced skin rash. The median progression-free survival (PFS) was 4.6 months and the PFS rate at 6 months was 36%. The median overall survival (OS) was 15.5 months and the OS rate at 12 months was 55%.

CONCLUSIONS

TTFields therapy combined with SR-surgery and medical oncological treatment is safe and nontoxic and holds the potential to improve the outcome for GBM patients through focal dose enhancement in the tumor.

Estimating the Intensity and Anisotropy of Tumor Treating Fields Jsing Singular Value Decomposition. Towards a More Comprehensive Estimation of Anti-tumor Efficacy

Tumor treating fields (TTFields) is an anticancer treatment that inhibits tumor growth with alternating electrical fields. Finite element (FE) methods have been used to estimate the TTFields intensity as a measure of treatment "dose". However, TTFields efficacy also depends on field direction and exposure time. Here we propose a new FE based approach, which uses all these parameters to quantify the average field intensity and the amount of unwanted directional field correlation (fractional anisotropy, FA). The method is based on principal component decomposition of the sequential TTFields over one duty cycle. Using a realistic head model of a glioblastoma patient, we observed significant unwanted FA in many regions of the brain, which may potentially affect therapeutic efficacy. FA varied between different array layouts and indicated a different order of array performance than predicted from the field intensity. Tumor resection nullified differences in field distributions between layouts and increased FA considerably. Our results question the rationale for the use of macroscopically orthogonal array layouts to reduce field correlation and rather indicate that arrays should be placed to maximize pathology coverage and field intensity. The proposed calculation framework has several potential applications, incl. improved treatment planning, technology development, and accurate prognostication models. Future studies are required to validate the method.

Fluorescence intensity modulation of CdSe/ZnS quantum dots assesses reactive oxygen species during chemotherapy and radiotherapy for cancer cells

Quantum dots (QDs) are semiconductor nanoparticles ranging in size from 2 to 10 nm. QDs are increasingly being developed for biomedical imaging, targeted drug delivery and green energy technology. These have led to much research on QD interactions with various physical, chemical and biological systems. For biological systems, research has focused on the biocompatibility/cytotoxicity of QDs in the context of imaging/therapy. However, there is a paucity of work on how biological systems and bioactive molecules might be used to alter the optoelectronic properties of QDs. Here, it is shown that these properties can be altered by reactive oxygen species (ROS) from chemotherapeutic media and biological cells following controlled changes in cellular activities. Using CdSe/ZnS core-shell QDs, spectroscopic analysis of optically excited QDs with HL60, K562 and T98G cancer cell lines is performed. Our results show statistically significant (P < 0.0001) modulation of the fluorescence emission spectra of the QDs due to the ROS produced by common chemotherapeutic drugs, daunorubicin and doxorubicin and by cells following chemotherapy/radiotherapy. This optical modulation, in addition to assessing ROS generation, will possibly enhance applications of QDs in simultaneous diagnostic imaging and nanoparticle-mediated drug delivery as well as simultaneous ROS assessment and radiosensitization for improved outcomes in cancer treatments. Reactive molecular species produced by biological cells and chemotherapeutic drugs can create electric fields that alter the photophysical properties of QDs, and this can be used for concurrent monitoring of cellular activities, while inducing changes in those cellular activities.

Importance of electrode position for the distribution of tumor treating fields (TTFields) in a human brain. Identification of effective layouts through systematic analysis of array positions for multiple tumor locations

Tumor treating fields (TTFields) is a new modality used for the treatment of glioblastoma. It is based on antineoplastic low-intensity electric fields induced by two pairs of electrode arrays placed on the patient’s scalp. The layout of the arrays greatly impacts the intensity (dose) of TTFields in the pathology. The present study systematically characterizes the impact of array position on the TTFields distribution calculated in a realistic human head model using finite element methods. We investigate systematic rotations of arrays around a central craniocaudal axis of the head and identify optimal layouts for a large range of (nineteen) different frontoparietal tumor positions. In addition, we present comprehensive graphical representations and animations to support the users’ understanding of TTFields. For most tumors, we identified two optimal array positions. These positions varied with the translation of the tumor in the anterior-posterior direction but not in the left-right direction. The two optimal directions were oriented approximately orthogonally and when combining two pairs of orthogonal arrays, equivalent to clinical TTFields therapy, we correspondingly found a single optimum position. In most cases, an oblique layout with the fields oriented at forty-five degrees to the sagittal plane was superior to the commonly used anterior-posterior and left-right combinations of arrays. The oblique configuration may be used as an effective and viable configuration for most frontoparietal tumors. Our results may be applied to assist clinical decision-making in various challenging situations associated with TTFields. This includes situations in which circumstances, such as therapy-induced skin rash, scar tissue or shunt therapy, etc., require layouts alternative to the prescribed. More accurate distributions should, however, be based on patient-specific models. Future work is needed to assess the robustness of the presented results towards variations in conductivity.

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

Tumor Treating Fields (TTFields) therapy is an approved modality of treatment for glioblastoma. Patient anatomy-based finite element analysis (FEA) has the potential to reveal not only how these fields affect tumor control but also how to improve efficacy. While the automated tools for segmentation speed up the generation of FEA models, multi-step manual corrections are required, including removal of disconnected voxels, incorporation of unsegmented structures and the addition of 36 electrodes plus gel layers matching the TTFields transducers. Existing approaches are also not scalable for the high throughput analysis of large patient volumes. A semi-automated workflow was developed to prepare FEA models for TTFields mapping in the human brain. Magnetic resonance imaging (MRI) pre-processing, segmentation, electrode and gel placement, and post-processing were all automated. The material properties of each tissue were applied to their corresponding mask in silico using COMSOL Multiphysics (COMSOL, Burlington, MA, USA). The fidelity of the segmentations with and without post-processing was compared against the full semi-automated segmentation workflow approach using Dice coefficient analysis. The average relative differences for the electric fields generated by COMSOL were calculated in addition to observed differences in electric field-volume histograms. Furthermore, the mesh file formats in MPHTXT and NASTRAN were also compared using the differences in the electric field-volume histogram. The Dice coefficient was less for auto-segmentation without versus auto-segmentation with post-processing, indicating convergence on a manually corrected model. An existent but marginal relative difference of electric field maps from models with manual correction versus those without was identified, and a clear advantage of using the NASTRAN mesh file format was found. The software and workflow outlined in this article may be used to accelerate the investigation of TTFields in glioblastoma patients by facilitating the creation of FEA models derived from patient MRI datasets.

Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma

Tumor Treating Fields (TTFields) therapy is an approved treatment that has known clinical efficacy against recurrent and newly diagnosed glioblastoma. However, the distribution of the electric fields and the corresponding pattern of energy deposition in the brain are poorly understood. To evaluate the physical parameters that may influence TTFields, postacquisition MP-RAGE, T1 and T2 MRI sequences from a responder with a right parietal glioblastoma were anatomically segmented and then solved using finite-element method to determine the distribution of the electric fields and rate of energy deposition at the gross tumor volume (GTV) and other intracranial structures. Electric field-volume histograms (EVH) and specific absorption rate-volume histograms (SARVH) were constructed to numerically evaluate the relative and/or absolute magnitude volumetric differences between models. The electric field parameters E_AUC , V_E150 , E_95% , E_50% , and E_20% , as well as the SAR parameters SAR_AUC , V_SAR7.5 , SAR_95% , SAR_50% , and SAR_20% , facilitated comparisons between models derived from various conditions. Specifically, TTFields at the GTV were influenced by the dielectric characteristics of the adjacent tissues as well as the GTV itself, particularly the presence or absence of a necrotic core. The thickness of the cerebrospinal fluid on the convexity of the brain and the geometry of the tumor were also relevant factors. Finally, the position of the arrays also influenced the electric field distribution and rate of energy deposition in the GTV. Using EVH and SARVH, a personalized approach for TTFields treatment can be developed when various patient-related and tumor-related factors are incorporated into the planning procedure.