Maria Ida Iacono

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.

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

ABSTRACT 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

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.

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 mm3 head model (mRes) refined in the basal ganglia by a 200 μm2 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.

Investigation of assumptions underlying current safety guidelines on EM-induced nerve stimulation

An intricate network of a variety of nerves is embedded within the complex anatomy of the human body. Although nerves are shielded from unwanted excitation, they can still be stimulated by external electromagnetic sources that induce strongly non-uniform field distributions. Current exposure safety standards designed to limit unwanted nerve stimulation are based on a series of explicit and implicit assumptions and simplifications. This paper demonstrates the applicability of functionalized anatomical phantoms with integrated coupled electromagnetic and neuronal dynamics solvers for investigating the impact of magnetic resonance exposure on nerve excitation within the full complexity of the human anatomy. The impact of neuronal dynamics models, temperature and local hot-spots, nerve trajectory and potential smoothing, anatomical inhomogeneity, and pulse duration on nerve stimulation was evaluated. As a result, multiple assumptions underlying current safety standards are questioned. It is demonstrated that coupled EM-neuronal dynamics modeling involving realistic anatomies is valuable to establish conservative safety criteria.

A computational model for bipolar deep brain stimulation of the subthalamic nucleus

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been shown to reduce some of the symptoms of advanced, levodopa-responsive Parkinsons 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.

Simulation platform for coupled modeling of EM-induced neuronal dynamics and functionalized anatomical models

A computational platform has been developed that is capable of simulating electromagnetic (EM) field interactions with neurons in complex tissue-structure environments. The platform has been tested in three case studies, namely: a) transcranial alternating current brain stimulation; b) MRI gradient coil switching induced nerve stimulation; and c) muscle activation by a neuroprosthetic implant. These applications were based on the use of a functionalized head and a whole-body model. Additionally a dedicated EM solver coupled with dynamic models of neuronal activity was also implemented. A high-resolution model of the head was developed for the analysis of EM-neuron interactions. Multimodal magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data were acquired to guide neuron model placement and provide information on tissue anisotropy. The model, called “MIDA”, features a large number of structures, particularly those (ears, eyes, and selected deep brain structures) relevant for applications such as DBS (Deep Brain Stimulation) and neuroprosthetics. A DBS application example is also shown.

Computational platform combining detailed and precise functionalized anatomical phantoms with EM-Neuron interaction modeling

A computational framework including functionalized anatomical phantoms able to simulate electromagnetic (EM)-neuron interactions in complex tissue-structure environments was developed. The anatomic head model distinguishes a large number of structures, particularly in regions relevant to EM-neuron interactions (i.e., ear, eye, deep brain structures). Multimodal Magnetic Resonance (MR) images were acquired together with Diffusion Tensor Imaging (DTI) data to guide neuron model placement and inform about tissue anisotropy. A dedicated EM solver was implemented and coupled with dynamic models of neuronal activity. The topologically conforming, non-self-intersecting, high-element-quality surfaces are suitable for a wide range of numerical methods and solvers, as demonstrated in an application derived from transcranial alternating current stimulation. The platform was validated against literature data, e.g., on the SENN [1] model which was further extended to account for local thermal effects. Additionally, the EM-neuron coupling simulation platform was also applied to investigate MRI gradient coil switching induced nerve stimulation.

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.

Retrospective analysis of RF heating measurements of passive medical implants

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.