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.

Validating Patient-Specific Finite Element Models of Direct Electrocortical Stimulation.

Direct electrocortical stimulation (DECS) with electrocorticography electrodes is an established therapy for epilepsy and an emerging application for stroke rehabilitation and brain-computer interfaces. However, the electrophysiological mechanisms that result in a therapeutic effect remain unclear. Patient-specific computational models are promising tools to predict the voltages in the brain and better understand the neural and clinical response to DECS, but the accuracy of such models has not been directly validated in humans. A key hurdle to modeling DECS is accurately locating the electrodes on the cortical surface due to brain shift after electrode implantation. Despite the inherent uncertainty introduced by brain shift, the effects of electrode localization parameters have not been investigated. The goal of this study was to validate patient-specific computational models of DECS against in vivo voltage recordings obtained during DECS and quantify the effects of electrode localization parameters on simulated voltages on the cortical surface. We measured intracranial voltages in six epilepsy patients during DECS and investigated the following electrode localization parameters: principal axis, Hermes, and Dykstra electrode projection methods combined with 0, 1, and 2 mm of cerebral spinal fluid (CSF) below the electrodes. Greater CSF depth between the electrode and cortical surface increased model errors and decreased predicted voltage accuracy. The electrode localization parameters that best estimated the recorded voltages across six patients with varying amounts of brain shift were the Hermes projection method and a CSF depth of 0 mm (r = 0.92 and linear regression slope = 1.21). These results are the first to quantify the effects of electrode localization parameters with in vivo intracranial recordings and may serve as the basis for future studies investigating the neuronal and clinical effects of DECS for epilepsy, stroke, and other emerging closed-loop applications.

Simulating transcranial direct current stimulation with a detailed anisotropic human head model.

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique able to induce long-lasting changes in cortical excitability that can benefit cognitive functioning and clinical treatment. In order to both better understand the mechanisms behind tDCS and possibly improve the technique, finite element models are used to simulate tDCS of the human brain. With the detailed anisotropic head model presented in this study, we provide accurate predictions of tDCS in the human brain for six of the practically most-used setups in clinical and cognitive research, targeting the primary motor cortex, dorsolateral prefrontal cortex, inferior frontal gyrus, occipital cortex, and cerebellum. We present the resulting electric field strengths in the complete brain and introduce new methods to evaluate the effectivity in the target area specifically, where we have analyzed both the strength and direction of the field. For all cerebral targets studied, the currently accepted configurations produced sub-optimal field strengths. The configuration for cerebellum stimulation produced relatively high field strengths in its target area, but it needs higher input currents than cerebral stimulation does. This study suggests that improvements in the effects of transcranial direct current stimulation are achievable.

Single-layer skull approximations perform well in transcranial direct current stimulation modeling.

In modeling the effect of transcranial direct current stimulation, the representation of the skull is an important factor. In a spherical model, we compared a realistic skull modeling approach, in which the skull consisted of three isotropic layers, to anisotropic and isotropic single-layer approximations. We simulated direct current stimulation for a range of conductivity values and investigated differences in the resulting current densities. Our results demonstrate that both approximation methods perform well, provided that the optimal conductivity values are used. We found that for both the anisotropic and the isotropic approximations the optimal conductivity values are largely dictated by the equivalent radial conductivity of the three-layered skull.

Binocular onset rivalry at the time of saccades and stimulus jumps.

Recent studies suggest that binocular rivalry at stimulus onset, so called onset rivalry, differs from rivalry during sustained viewing. These observations raise the interesting question whether there is a relation between onset rivalry and rivalry in the presence of eye movements. We therefore studied binocular rivalry when stimuli jumped from one visual hemifield to the other, either through a saccade or through a passive stimulus displacement, and we compared rivalry after such displacements with onset and sustained rivalry. We presented opponent motion, orthogonal gratings and face/house stimuli through a stereoscope. For all three stimulus types we found that subjects showed a strong preference for stimuli in one eye or one hemifield (Experiment 1), and that these subject-specific biases did not persist during sustained viewing (Experiment 2). These results confirm and extend previous findings obtained with gratings. The results from the main experiment (Experiment 3) showed that after a passive stimulus jump, switching probability was low when the preferred eye was dominant before a stimulus jump, but when the non-preferred eye was dominant beforehand, switching probability was comparatively high. The results thus showed that dominance after a stimulus jump was tightly related to eye dominance at stimulus onset. In the saccade condition, however, these subject-specific biases were systematically reduced, indicating that the influence of saccades can be understood from a systematic attenuation of the subjects' onset rivalry biases. Taken together, our findings demonstrate a relation between onset rivalry and rivalry after retinal shifts and involvement of extra-retinal signals in binocular rivalry.

Ligand-induced folding of the guanine-sensing riboswitch is controlled by a combined predetermined induced fit mechanism.

All known guanine-sensing riboswitches regulate gene expression by specifically binding to guanine (G) or related analogs with high affinity to switch off transcription. The aptamers of this class of riboswitches are characterized by three helices (P1-P3), surrounding a central core of phylogenetically conserved nucleotides and a long-range loop-loop interaction. To gain more insight into the switching mechanism, we present here a comparison between the solution-state structures of the G-free and G-bound forms of the guanine aptamer from the xpt-pbuX operon of Bacillus subtilis, as derived from NMR chemical shifts and magnetic-field-induced residual dipolar couplings. The high-resolution NMR analysis shows the G-free aptamer is highly structured with parallel P2 and P3 helices and the long-range loop-loop interaction already present, implying that the structure is largely preformed to bind the ligand. Structural changes upon guanine binding are found to be localized to the central core. In the free state, the G-quadruple interaction and two base pairs of the P1 stem flanking the central core appear to be largely disordered. The ligand thus binds via a combined predetermined-induced fit mechanism, involving a previously unstructured five-residue loop of the J2-3 junction that folds over the ligand. These limited additional interactions within a preorganized setting possibly explain how the aptamer rapidly responds to ligand binding, which is necessary to switch the structural state of the expression platform within a narrow time frame before the RNA polymerase escapes the 5'-UTR.