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We design, develop, and disseminate a 'virtual population' of five realistic computational models of deep brain stimulation (DBS) patients for electromagnetic (EM) analysis. We found five DBS patients in our institution' research patient database who received high quality post-DBS surgery computer tomography (CT) examinations of the head and neck. Three patients have a single implanted pulse generator (IPG) and the two others have two IPGs (one for each lead). Moreover, one patient has two abandoned leads on each side of the head. For each patient, we combined the head and neck volumes into a 'virtual CT', from which we extracted the full-length DBS path including the IPG, extension cables, and leads. We corrected topology errors in this path, such as self-intersections, using a previously published optimization procedure. We segmented the virtual CT volume into bones, internal air, and soft tissue classes and created two-manifold, watertight surface meshes of these distributions. In addition, we added a segmented model of the brain (grey matter, white matter, eyes and cerebrospinal fluid) to one of the model (nickname Freddie) that was derived from a T1-weighted MR image obtained prior to the DBS implantation. We simulated the EM fields and specific absorption rate (SAR) induced at 3 Tesla by a quadrature birdcage body coil in each of the five patient models using a co-simulation strategy. We found that inter-subject peak SAR variability across models was independent of the target averaging mass and equal to ~45%. In our simulations of the full brain segmentation and six simplified versions of the Freddie model, the error associated with incorrect dielectric property assignment around the DBS electrodes was greater than the error associated with modeling the whole model as a single tissue class. Our DBS patient models are freely available on our lab website (Webpage of the Martinos Center Phantom Resource 2018 https://phantoms.martinos.org/Main_Page).

Access to MRI is limited for patients with deep brain stimulation (DBS) implants due to safety hazards, including radiofrequency (RF) heating of tissue surrounding the leads. Computational models provide an exquisite tool to explore the multi-variate problem of RF heating and help better understand the interaction of electromagnetic fields and biological tissues. This paper presents a computational approach to assess RF-induced heating, in terms of specific absorption rate (SAR) in the tissue, around the tip of bilateral DBS leads during MRI at 64MHz/1.5 T and 127 MHz/3T. Patient-specific realistic lead models were constructed from post-operative CT images of nine patients operated for sub-thalamic nucleus DBS. Finite element method was applied to calculate the SAR at the tip of left and right DBS contact electrodes. Both transmit head coils and transmit body coils were analyzed. We found a substantial difference between the SAR and temperature rise at the tip of right and left DBS leads, with the lead contralateral to the implanted pulse generator (IPG) exhibiting up to 7 times higher SAR in simulations, and up to 10 times higher temperature rise during measurements. The orientation of incident electric field with respect to lead trajectories was explored and a metric to predict local SAR amplification was introduced. Modification of the lead trajectory was shown to substantially reduce the heating in phantom experiments using both conductive wires and commercially available DBS leads. Finally, the surgical feasibility of implementing the modified trajectories was demonstrated in a patient operated for bilateral DBS., (Copyright © 2018 Elsevier Inc. All rights reserved.)

We propose a framework for electromagnetic (EM) simulation of deep brain stimulation (DBS) patients in radiofrequency (RF) coils. We generated a model of a DBS patient using post-operative head and neck computed tomography (CT) images stitched together into a 'virtual CT' image covering the entire length of the implant. The body was modeled as homogeneous. The implant path extracted from the CT data contained self-intersections, which we corrected automatically using an optimization procedure. Using the CT-derived DBS path, we built a model of the implant including electrodes, helicoidal internal conductor wires, loops, extension cables, and the implanted pulse generator. We also built four simplified models with straight wires, no extension cables and no loops to assess the impact of these simplifications on safety predictions. We simulated EM fields induced by the RF birdcage body coil in the body model, including at the DBS lead tip at both 1.5 Tesla (64 MHz) and 3 Tesla (123 MHz). We also assessed the robustness of our simulation results by systematically varying the EM properties of the body model and the position and length of the DBS implant (sensitivity analysis). The topology correction algorithm corrected all self-intersection and curvature violations of the initial path while introducing minimal deformations (open-source code available at http://ptx.martinos.org/index.php/Main_Page). The unaveraged lead-tip peak SAR predicted by the five DBS models (0.1 mm resolution grid) ranged from 12.8 kW kg -1 (full model, helicoidal conductors) to 43.6 kW kg -1 (no loops, straight conductors) at 1.5 T (3.4-fold variation) and 18.6 kW kg -1 (full model, straight conductors) to 73.8 kW kg -1 (no loops, straight conductors) at 3 T (4.0-fold variation). At 1.5 T and 3 T, the variability of lead-tip peak SAR with respect to the conductivity ranged between 18% and 30%. Variability with respect to the position and length of the DBS implant ranged between 9.5% and 27.6%.

Purpose: MRI may cause brain tissue around deep brain stimulation (DBS) electrodes to become excessively hot, causing lesions. The presence of extracranial loops in the DBS lead trajectory has been shown to affect the specific absorption rate (SAR) of the radiofrequency energy at the electrode tip, but experimental studies have reported controversial results. The goal of this study was to perform a systematic numerical study to provide a better understanding of the effects of extracranial loops in DBS leads on the local SAR during MRI at 64 and 127 MHz., Methods: A total of 160 numerical simulations were performed on patient-derived data, in which relevant factors including lead length and trajectory, loop location and topology, and frequency of MRI radiofrequency (RF) transmitter were assessed., Results: Overall, the presence of extracranial loops reduced the local SAR in the tissue around the DBS tip compared with straight trajectories with the same length. SAR reduction was significantly larger at 127 MHz compared with 64 MHz. SAR reduction was significantly more sensitive to variable loop parameters (eg, topology and location) at 127 MHz compared with 64 MHz., Conclusion: Lead management strategies could exist that significantly reduce the risks of 3 Tesla (T) MRI for DBS patients. Magn Reson Med 78:1558-1565, 2017. © 2016 International Society for Magnetic Resonance in Medicine., (© 2016 International Society for Magnetic Resonance in Medicine.)

Post-operative MRI of patients with deep brain simulation (DBS) implants is useful to assess complications and diagnose comorbidities, however more than one third of medical centers do not perform MRIs on this patient population due to stringent safety restrictions and liability risks. A new system of reconfigurable magnetic resonance imaging head coil composed of a rotatable linearly-polarized birdcage transmitter and a close-fitting 32-channel receive array is presented for low-SAR imaging of patients with DBS implants. The novel system works by generating a region with low electric field magnitude and steering it to coincide with the DBS lead trajectory. We demonstrate that the new coil system substantially reduces the SAR amplification around DBS electrodes compared to commercially available circularly polarized coils in a cohort of 9 patient-derived realistic DBS lead trajectories. We also show that the optimal coil configuration can be reliably identified from the image artifact on B 1 + field maps. Our preliminary results suggest that such a system may provide a viable solution for high-resolution imaging of DBS patients in the future. More data is needed to quantify safety limits and recommend imaging protocols before the novel coil system can be used on patients with DBS implants., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been shown to reduce some of the symptoms of advanced, levodopa-responsive Parkinson's disease that are not adequately controlled with medication. However, the precise mechanism of the therapeutic action of DBS is still unclear. Stimulation-induced side effects are not uncommon and require electrical "dose" adjustments. Quantitative methods are needed to fully characterize the electric field in the deep brain region that surrounds the electrodes in order to help with adjustments and maximize the efficacy of the device. Herein we report a magnetic resonance imaging (MRI)-based head model proposed for analysis of fields generated by deep brain stimulation (DBS). The model was derived from multimodal image data at 0.5mm isotropic spatial resolution and distinguishes 142 anatomical structures, including the basal ganglia and 38 nuclei of the thalamus. Six bipolar electrode configurations (1-2, 1-3, 1-4, 2-3, 2-4, 3-4) were modeled in order to assess the effects of the inter-electrode distance of the electric field. Increasing the distance between the electrodes results in an attenuated stimulation, with up to 25% reduction in electric field amplitude delivered (2-3 vs. 1-4). The map of the deep brain structures provided a highly precise anatomical detail which is useful for the quantitative assessment of current spread around the electrode and a better evaluation of the stimulation setting for the treatment optimization.

Deep brain stimulation (DBS) is an established procedure for the treatment of movement and affective disorders. Patients with DBS may benefit from magnetic resonance imaging (MRI) to evaluate injuries or comorbidities. However, the MRI radio-frequency (RF) energy may cause excessive tissue heating particularly near the electrode. This paper studies how the accuracy of numerical modeling of the RF field inside a DBS patient varies with spatial resolution and corresponding anatomical detail of the volume surrounding the electrodes. A multiscale model (MS) was created by an atlas-based segmentation using a 1 mm(3) head model (mRes) refined in the basal ganglia by a 200  μ m(2) ex-vivo dataset. Four DBS electrodes targeting the left globus pallidus internus were modeled. Electromagnetic simulations at 128 MHz showed that the peak of the electric field of the MS doubled (18.7 kV/m versus 9.33 kV/m) and shifted 6.4 mm compared to the mRes model. Additionally, the MS had a sixfold increase over the mRes model in peak-specific absorption rate (SAR of 43.9 kW/kg versus 7 kW/kg). The results suggest that submillimetric resolution and improved anatomical detail in the model may increase the accuracy of computed electric field and local SAR around the tip of the implant.

Deep Brain Stimulation (DBS) is an effective therapy for patients disabling motor symptoms from Parkinson's disease, essential tremor, and other motor disorders. Precise, individualized placement of DBS electrodes is a key contributor to clinical outcomes following surgery. Electroencephalography (EEG) is widely used to identify the sources of intracerebral signals from the potential on the scalp. EEG is portable, non-invasive, low-cost, and it could be easily integrated into the intraoperative or ambulatory environment for localization of either the DBS electrode or evoked potentials triggered by stimulation itself. In this work, we studied with numerical simulations the principle of extracting the DBS electrical pulse from the patient's EEG – which normally constitutes an artifact – and localizing the source of the artifact (i.e., the DBS electrodes) using EEG localization methods. A high-resolution electromagnetic head model was used to simulate the EEG potential at the scalp generated by the DBS pulse artifact. The potential distribution on the scalp was then sampled at the 256 electrode locations of a high-density EEG Net. The electric potential was modeled by a dipole source created by a given pair of active DBS electrodes. The dynamic Statistical Parametric Maps (dSPM) algorithm was used to solve the EEG inverse problem, and it allowed localization of the position of the stimulus dipole in three DBS electrode bipolar configurations with a maximum error of 1.5 cm. To assess the accuracy of the computational model, the results of the simulation were compared with the electric artifact amplitudes over 16 EEG electrodes measured in five patients. EEG artifacts measured in patients confirmed that simulated data are commensurate to patients' data (0 ± 6.6 μV). While we acknowledge that further work is necessary to achieve a higher accuracy needed for surgical navigation, the results presented in this study are proposed as the first step toward a validated computational framework that could be used for non-invasive localization not only of the DBS system but also brain rhythms triggered by stimulation at both proximal and distal sites in the human central nervous system. [ABSTRACT FROM AUTHOR]