The 'virtual DBS population': five realistic computational models of deep brain stimulation patients for electromagnetic MR safety studies.

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).

RF-induced heating in tissue near bilateral DBS implants during MRI at 1.5 T and 3T: The role of surgical lead management.

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.

Radio-Frequency Safety Assessment of Stents in Blood Vessels During Magnetic Resonance Imaging.

Purpose: The purpose of this study was to investigate the need for high-resolution detailed anatomical modeling to correctly estimate radio-frequency (RF) safety during magnetic resonance imaging (MRI). RF-induced heating near metallic implanted devices depends on the electric field tangential to the device (Etan ). Etan and specific absorption rate (SAR) were analyzed in blood vessels of an anatomical model to understand if a standard gel phantom accurately represents the potential heating in tissues due to passive vascular implants such as stents. Methods: A numerical model of an RF birdcage body coil and an anatomically realistic virtual patient with a native spatial resolution of 1 mm3 were used to simulate the in vivo electric field at 64 MHz (1.5 T MRI system). Maximum values of SAR inside the blood vessels were calculated and compared with peaks in a numerical model of the ASTM gel phantom to see if the results from the simplified and homogeneous gel phantom were comparable to the results from the anatomical model. Etan values were also calculated in selected stent trajectories inside blood vessels and compared with the ASTM result. Results: Peak SAR values in blood vessels were up to ten times higher than those found in the ASTM standard gel phantom. Peaks were found in clinically significant anatomical locations, where stents are implanted as per intended use. Furthermore, Etan results showed that volume-averaged SAR values might not be sufficient to assess RF safety. Conclusion: Computational modeling with a high-resolution anatomical model indicated higher values of the incident electric field compared to the standard testing approach. Further investigation will help develop a robust safety testing method which reflects clinically realistic conditions.

Biomimetic 3D-printed neurovascular phantoms for near-infrared fluorescence imaging.

Emerging three-dimensional (3D) printing technology enables the fabrication of optically realistic and morphologically complex tissue-simulating phantoms for the development and evaluation of novel optical imaging products. In this study, we assess the potential to print image-defined neurovascular phantoms with patent channels for contrast-enhanced near-infrared fluorescence (NIRF) imaging. An anatomical map defined from clinical magnetic resonance imaging (MRI) was segmented and processed into files suitable for printing a forebrain vessel network in rectangular and curved-surface biomimetic phantoms. Methods for effectively cleaning samples with complex vasculature were determined. A final set of phantoms were imaged with a custom NIRF system at 785 nm excitation using two NIRF contrast agents. In addition to demonstrating the strong potential of 3D printing for creating highly realistic, patient-specific biophotonic phantoms, our work provides insight into optimal methods for accomplishing this goal and elucidates current limitations of this approach.

Retrospective analysis of RF heating measurements of passive medical implants.

PURPOSE: The test reports for the RF-induced heating of metallic devices of hundreds of medical implants have been provided to the U.S. Food and Drug Administration as a part of premarket submissions. The main purpose of this study is to perform a retrospective analysis of the RF-induced heating data provided in the reports to analyze the trends and correlate them with implant geometric characteristics. METHODS: The ASTM-based RF heating test reports from 86 premarket U.S. Food and Drug Administration submissions were reviewed by three U.S. Food and Drug Administration reviewers. From each test report, the dimensions and RF-induced heating values for a given whole-body (WB) specific absorption rate (SAR) and local background (LB) SAR were extracted and analyzed. The data from 56 stents were analyzed as a subset to further understand heating trends and length dependence. RESULTS: For a given WB SAR, the LB/WB SAR ratio varied significantly across the test labs, from 2.3 to 11.3. There was an increasing trend on the temperature change per LB SAR with device length. The maximum heating for stents occurred at lengths of approximately 100 mm at 3 T, and beyond 150 mm at 1.5 T. CONCLUSIONS: Differences in the LB/WB SAR ratios across testing labs and various MRI scanners could lead to inconsistent WB SAR labeling. Magnetic resonance (MR) conditional labeling based on WB SAR should be derived from a conservative estimate of global LB/WB ratios.

Realistic modeling of deep brain stimulation implants for electromagnetic MRI safety studies.

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%.

A Study on the Feasibility of the Deep Brain Stimulation (DBS) Electrode Localization Based on Scalp Electric Potential Recordings.

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.

Construction and modeling of a reconfigurable MRI coil for lowering SAR in patients with deep brain stimulation implants.

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 B1+ 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.

Local SAR near deep brain stimulation (DBS) electrodes at 64 and 127 MHz: A simulation study of the effect of extracranial loops.

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.

Assessing the Electromagnetic Fields Generated By a Radiofrequency MRI Body Coil at 64 MHz: Defeaturing Versus Accuracy.

GOAL: This study aims at a systematic assessment of five computational models of a birdcage coil for magnetic resonance imaging (MRI) with respect to accuracy and computational cost. METHODS: The models were implemented using the same geometrical model and numerical algorithm, but different driving methods (i.e., coil "defeaturing"). The defeatured models were labeled as: specific (S2), generic (G32, G16), and hybrid (H16, [Formula: see text]). The accuracy of the models was evaluated using the "symmetric mean absolute percentage error" ("SMAPE"), by comparison with measurements in terms of frequency response, as well as electric ( ||→E||) and magnetic ( || →B ||) field magnitude. RESULTS: All the models computed the || →B || within 35% of the measurements, only the S2, G32, and H16 were able to accurately model the ||→E|| inside the phantom with a maximum SMAPE of 16%. Outside the phantom, only the S2 showed a SMAPE lower than 11%. CONCLUSIONS: Results showed that assessing the accuracy of || →B || based only on comparison along the central longitudinal line of the coil can be misleading. Generic or hybrid coils - when properly modeling the currents along the rings/rungs - were sufficient to accurately reproduce the fields inside a phantom while a specific model was needed to accurately model ||→E|| in the space between coil and phantom. SIGNIFICANCE: Computational modeling of birdcage body coils is extensively used in the evaluation of radiofrequency-induced heating during MRI. Experimental validation of numerical models is needed to determine if a model is an accurate representation of a physical coil.

MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck.

Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1-2 mm and with 10-50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named "MIDA". The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community.

MRI-based multiscale model for electromagnetic analysis in the human head with implanted DBS.

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.

A multi-tissue mass-spring model for computer assisted breast surgery.

The aim of this work was to develop and validate a 3D female breast deformation model for computer assisted breast surgery. Magnetic resonance (MR) image data of a patient undergoing breast biopsy, were acquired using two different protocols with the patient in prone position: (i) uncompressed breast and (ii) compressed breast, with lateral single breast compression, realized with a movable slab. The acquired images were then segmented using a semi-automatic procedure and from the extracted volumes of interest tetrahedral meshes representing skin, fat and mammary glands were generated. Tissue deformation was ruled by a mass-spring model: first, an iterative approximation algorithm was implemented to estimate the spring's rest length and stiffness, accounting for gravity force; then the resulting parameters were used to deform the uncompressed breast model in order to reach the real compressed one (ground truth). Results showed that gravity force applied to the mesh was properly compensated by the internal elastic forces, leading to a distance between the deformed mesh and the reference data of 0.036±0.092 mm (median±inter quartile range). The point to mesh residual distance between the deformed mesh and the ground truth was 1.224±2.202 mm (median±inter quartile range). Further investigation on a larger patient dataset is required for a more robust confirmation of model accuracy in predicting breast deformations.

Dual energy pulses for Electrical Impedance Spectroscopy with the stochastic Gabor function.

This paper introduces the stochastic Gabor function (SGF), an excitation waveform that can be used to design optimal excitation pulses for Electrical Impedance Spectroscopy (EIS) of the brain. The SGF is a Gaussian function modulated by uniformly distributed noise; it has wide frequency spectrum representation regardless of the stimuli pulse length. The SGF was studied in the time-frequency domain. As shown by frequency concentration measurements, the SGF is least compact in the sample frequency phase plane. Numerical results obtained by using a realistic human head model indicate that the SGF may allow for both shallow and deeper tissue penetration than is currently obtainable with conventional stimulus paradigms, potentially facilitating tissue subtraction assessment of parenchymal dielectric changes in frequency. This could be of value in advancing EIS of stroke and hemorrhage.