Effect of subject-specific head morphometry on specific absorption rate estimates in parallel-transmit MRI at 7 T.

PURPOSE: To assess the accuracy of morphing an established reference electromagnetic head model to a subject-specific morphometry for the estimation of specific absorption rate (SAR) in 7T parallel-transmit (pTx) MRI. METHODS: Synthetic T1 -weighted MR images were created from three high-resolution open-source electromagnetic head voxel models. The accuracy of morphing a "reference" (multimodal image-based detailed anatomical [MIDA]) electromagnetic model into a different subject's native space (Duke and Ella) was compared. Both linear and nonlinear registration methods were evaluated. Maximum 10-g averaged SAR was estimated for circularly polarized mode and for 5000 random RF shim sets in an eight-channel transmit head coil, and comparison made between the morphed MIDA electromagnetic models and the native Duke and Ella electromagnetic models, respectively. RESULTS: The averaged error in maximum 10-g averaged SAR estimation across pTx MRI shim sets between the MIDA and the Duke target model was reduced from 17.5% with only rigid-body registration, to 11.8% when affine linear registration was used, and further reduced to 10.7% when nonlinear registration was used. The corresponding figures for the Ella model were 16.7%, 11.2%, and 10.1%. CONCLUSION: We found that morphometry accounts for up to half of the subject-specific differences in pTx SAR. Both linear and nonlinear morphing of an electromagnetic model into a target subject improved SAR agreement by better matching head size, morphometry, and position. However, differences remained, likely arising from details in tissue composition estimation. Thus, the uncertainty of the head morphometry and tissue composition may need to be considered separately to achieve personalized SAR estimation.

A new method to improve RF safety of implantable medical devices using inductive coupling at 3.0 T MRI.

OBJECTIVE: To enhance RF safety when implantable medical devices are located within the body coil but outside the imaging region by using a secondary resonator (SR) to reduce electric fields, the corresponding specific absorption rate (SAR), and temperature change during MRI. MATERIALS AND METHODS: This study was conducted using numerical simulations with an American Society for Testing and Materials (ASTM) phantom and adult human models of Ella and Duke from Virtual Family Models, along with corresponding experimental results of temperature change obtained using the ASTM phantom. The circular SR was designed with an inner diameter of 150 mm and a width of 6 mm. Experimental measurements were carried out using a 3 T Medical Implant Test System (MITS) body coil, electromagnetic (EM) field mapping probes, and an ASTM phantom. RESULTS: The magnitudes of B1+ (|B1+|) and SAR1g were reduced by 15.2% and 5.85% within the volume of interest (VoI) of an ASTM phantom, when a SR that generates opposing electromagnetic fields was utilized. Likewise, the Δ|B1+| and ΔSAR1g were reduced by up to 56.7% and 57.5% within the VoI of an Ella model containing a copper rod when an opposing SR was used. CONCLUSION: A novel method employing the designed SR, which generates opposing magnetic fields to partially shield a sample, has been proposed to mitigate the risk of induced-RF heating at the VoI through numerical simulations and corresponding experiments under various conditions at 3.0 T.

The MotoNet: A 3 Tesla MRI-Conditional EEG Net with Embedded Motion Sensors.

We introduce a new electroencephalogram (EEG) net, which will allow clinicians to monitor EEG while tracking head motion. Motion during MRI limits patient scans, especially of children with epilepsy. EEG is also severely affected by motion-induced noise, predominantly ballistocardiogram (BCG) noise due to the heartbeat. METHODS: The MotoNet was built using polymer thick film (PTF) EEG leads and motion sensors on opposite sides in the same flex circuit. EEG/motion measurements were made with a standard commercial EEG acquisition system in a 3 Tesla (T) MRI. A Kalman filtering-based BCG correction tool was used to clean the EEG in healthy volunteers. RESULTS: MRI safety studies in 3 T confirmed the maximum heating below 1 °C. Using an MRI sequence with spatial localization gradients only, the position of the head was linearly correlated with the average motion sensor output. Kalman filtering was shown to reduce the BCG noise and recover artifact-clean EEG. CONCLUSIONS: The MotoNet is an innovative EEG net design that co-locates 32 EEG electrodes with 32 motion sensors to improve both EEG and MRI signal quality. In combination with custom gradients, the position of the net can, in principle, be determined. In addition, the motion sensors can help reduce BCG noise.

Aluminum Thin Film Nanostructure Traces in Pediatric EEG Net for MRI and CT Artifact Reduction.

Magnetic resonance imaging (MRI) and continuous electroencephalogram (EEG) monitoring are essential in the clinical management of neonatal seizures. EEG electrodes, however, can significantly degrade the image quality of both MRI and CT due to substantial metallic artifacts and distortions. Thus, we developed a novel thin film trace EEG net ("NeoNet") for improved MRI and CT image quality without compromising the EEG signal quality. The aluminum thin film traces were fabricated with an ultra-high-aspect ratio (up to 17,000:1, with dimensions 30 nm × 50.8 cm × 100 µm), resulting in a low density for reducing CT artifacts and a low conductivity for reducing MRI artifacts. We also used numerical simulation to investigate the effects of EEG nets on the B1 transmit field distortion in 3 T MRI. Specifically, the simulations predicted a 65% and 138% B1 transmit field distortion higher for the commercially available copper-based EEG net ("CuNet", with and without current limiting resistors, respectively) than with NeoNet. Additionally, two board-certified neuroradiologists, blinded to the presence or absence of NeoNet, compared the image quality of MRI images obtained in an adult and two children with and without the NeoNet device and found no significant difference in the degree of artifact or image distortion. Additionally, the use of NeoNet did not cause either: (i) CT scan artifacts or (ii) impact the quality of EEG recording. Finally, MRI safety testing confirmed a maximum temperature rise associated with the NeoNet device in a child head-phantom to be 0.84 °C after 30 min of high-power scanning, which is within the acceptance criteria for the temperature for 1 h of normal operating mode scanning as per the FDA guidelines. Therefore, the proposed NeoNet device has the potential to allow for concurrent EEG acquisition and MRI or CT scanning without significant image artifacts, facilitating clinical care and EEG/fMRI pediatric research.

An investigation into the minimum number of tissue groups required for 7T in-silico parallel transmit electromagnetic safety simulations in the human head.

PURPOSE: Safety limits for the permitted specific absorption rate (SAR) place restrictions on pulse sequence design, especially at ultrahigh fields (≥ 7 tesla). Due to intersubject variability, the SAR is usually conservatively estimated based on standard human models that include an applied safety margin to ensure safe operation. One approach to reducing the restrictions is to create more accurate subject-specific models from their segmented MR images. This study uses electromagnetic simulations to investigate the minimum number of tissue groups required to accurately determine SAR in the human head. METHODS: Tissue types from a fully characterized electromagnetic human model with 47 tissue types in the head and neck region were grouped into different tissue clusters based on the conductivities, permittivities, and mass densities of the tissues. Electromagnetic simulations of the head model inside a parallel transmit head coil at 7 tesla were used to determine the minimum number of required tissue clusters to accurately determine the subject-specific SAR. The identified tissue clusters were then evaluated using 2 additional well-characterized electromagnetic human models. RESULTS: A minimum of 4-clusters-plus-air was found to be required for accurate SAR estimation. These tissue clusters are centered around gray matter, fat, cortical bone, and cerebrospinal fluid. For all 3 simulated models, the parallel transmit maximum 10g SAR was consistently determined to within an error of <12% relative to the full 47-tissue model. CONCLUSION: A minimum of 4-clusters-plus-air are required to produce accurate personalized SAR simulations of the human head when using parallel transmit at 7 tesla.

Numerical simulation of the radiofrequency safety of 128-channel hd-EEG nets on a 29-month-old whole-body model in a 3 Tesla MRI.

This study investigates the radiofrequency (RF) induced heating in a pediatric whole-body voxel model with a high-density electroencephalogram (hd-EEG) net during magnetic resonance imaging (MRI) at 3 Tesla. A total of three cases were studied: no net (NoNet), a resistive hd-EEG (NeoNet), and a copper (CuNet) net. The maximum values of specific absorption rate averaged over 10g-mass (10gSAR) in the head were calculated with the NeoNet was 12.51 W/kg and in the case of the NoNet was 12.40 W/kg. In contrast, the CuNet case was 17.04 W/Kg. Temperature simulations were conducted to determine the RF-induced heating without and with hd-EEG nets (NeoNet and CuNet) during an MRI scan using an age-corrected and thermoregulated perfusion for the child model. The results showed that the maximum temperature estimated in the child's head was 38.38 °C for the NoNet, 38.43 °C for the NeoNet, and 43.05 °C for the CuNet. In the case of NeoNet, the maximum temperature estimated in the child's head remained compliant with IEC 60601 for the MRI RF safety limit. However, the case of CuNet estimated to exceed the RF safety limit, which may require an appropriate cooling period or a hardware design to suppress the RF-induced heating.

High-quality multimodal MRI with simultaneous EEG using conductive ink and polymer-thick film nets.

Objective Combining magnetic resonance imaging (MRI) and electroencephalography (EEG) provides a powerful tool for investigating brain function at varying spatial and temporal scales. Simultaneous acquisition of both modalities can provide unique information that a single modality alone cannot reveal. However, current simultaneous EEG-fMRI studies are limited to a small set of MRI sequences due to the image quality and safety limitations of commercially available MR-conditional EEG nets. We tested whether the Inknet2, a high-resistance polymer thick film (PTF) based EEG net that uses conductive ink, could enable the acquisition of a variety of MR image modalities with minimal artifacts by reducing the RF-shielding caused by traditional MR-conditional nets. Approach We first performed simulations to model the effect of the EEG nets on the magnetic field and image quality. We then performed phantom scans to test image quality with a conventional copper EEG net, with the new Inknet2, and without any EEG net. Finally, we scanned five human subjects at 3 Tesla (3T) and three human subjects at 7 Tesla (7T) with and without the Inknet2 to assess structural and functional MRI image quality. Main results Across these simulations, phantom scans, and human studies, the Inknet2 induced fewer artifacts than the conventional net and produced image quality similar to scans with no net present. Significance Our results demonstrate that high-quality structural and functional multimodal imaging across a variety of MRI pulse sequences at both 3T and 7T is achievable with an EEG net made with conductive ink and polymer thick film technology. .

A high-resolution pediatric female whole-body numerical model with comparison to a male model.

Objective. Numerical models are central in designing and testing novel medical devices and in studying how different anatomical changes may affect physiology. Despite the numerous adult models available, there are only a few whole-body pediatric numerical models with significant limitations. In addition, there is a limited representation of both male and female biological sexes in the available pediatric models despite the fact that sex significantly affects body development, especially in a highly dynamic population. As a result, we developed Athena, a realistic female whole-body pediatric numerical model with high-resolution and anatomical detail.Approach. We segmented different body tissues through Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images of a healthy 3.5 year-old female child using 3D Slicer. We validated the high anatomical accuracy segmentation through two experienced sub-specialty-certified neuro-radiologists and the inter and intra-operator variability of the segmentation results comparing sex differences in organ metrics with physiologic values. Finally, we compared Athena with Martin, a similar male model, showing differences in anatomy, organ metrics, and MRI dosimetric exposure.Main results. We segmented 267 tissue compartments, which included 50 brain tissue labels. The tissue metrics of Athena displayed no deviation from the literature value of healthy children. We show the variability of brain metrics in the male and female models. Finally, we offer an example of computing Specific Absorption Rate and Joule heating in a toddler/preschooler at 7 T MRI.Significance. This study introduces a female realistic high-resolution numerical model using MRI and CT scans of a 3.5 year-old female child, the use of which includes but is not limited to radiofrequency safety studies for medical devices (e.g. an implantable medical device safety in MRI), neurostimulation studies, and radiation dosimetry studies. This model will be open source and available on the Athinoula A. Martinos Center for Biomedical Imaging website.

Short-pulsed micro-magnetic stimulation of the vagus nerve.

Vagus nerve stimulation (VNS) is commonly used to treat drug-resistant epilepsy and depression. The therapeutic effect of VNS depends on stimulating the afferent vagal fibers. However, the vagus is a mixed nerve containing afferent and efferent fibers, and the stimulation of cardiac efferent fibers during VNS may produce a rare but severe risk of bradyarrhythmia. This side effect is challenging to mitigate since VNS, via electrical stimulation technology used in clinical practice, requires unique electrode design and pulse optimization for selective stimulation of only the afferent fibers. Here we describe a method of VNS using micro-magnetic stimulation (µMS), which may be an alternative technique to induce a focal stimulation, enabling a selective fiber stimulation. Micro-coils were implanted into the cervical vagus nerve in adult male Wistar rats. For comparison, the physiological responses were recorded continuously before, during, and after stimulation with arterial blood pressure (ABP), respiration rate (RR), and heart rate (HR). The electrical VNS caused a decrease in ABP, RR, and HR, whereas µM-VNS only caused a transient reduction in RR. The absence of an HR modulation indicated that µM-VNS might provide an alternative technology to VNS with fewer heart-related side effects, such as bradyarrhythmia. Numerical electromagnetic simulations helped estimate the optimal coil orientation with respect to the nerve to provide information on the electric field's spatial distribution and strength. Furthermore, a transmission emission microscope provided very high-resolution images of the cervical vagus nerve in rats, which identified two different populations of nerve fibers categorized as large and small myelinated fibers.

Numerical estimation of the B1 transmit field distortion in a copper EEG trace comparison with the thin-film based resistive trace "NeoNet".

This study investigates the effects of EEG traces in B1 transmit field distortion in a 3T MRI. EEG is a non-invasive method to monitor brain activities. Although EEG monitors brain activities with a high temporal resolution, it has trouble localizing the signal source. The EEG-fMRI is the multimodal imaging method, but care is needed to use EEG while in MRI as EEG traces create the signal distortion to the MRI. To tackle this problem, resistive traces are developed using thin-film technology to reduce the signal distortion during MRI. Numerical simulation was used to estimate the amount of B1 transmit field distortion of NeoNet and copper-based EEG nets (CuNet - with and without current limiting resistors) compared with the case without EEG net (NoNet). The reduced B1 transmit field distortion is estimated in the case of NeoNet compared to the CuNets. NeoNet is an MR-compatible high-density EEG net designed for pediatric subjects. The proposed NeoNet traces will facilitate/enable such EEG/fMRI pediatric studies with mitigated artifacts, which in turn will help to move the pediatric EEG/fMRI field forward.Clinical Relevance-This study estimates the benefit of the thin-film based EEG net with reduced B1 transmit artifact for the multimodal study of EEG-fMRI. The results are compared with commercial EEG trace made with copper metal with current limiting resistors. It is reported that about 470,000 children are suffering from Epilepsy. The MR-compatible resistive EEG traces se EEG-fMRI has potential to be a valuable tool to help understand pediatric Epilepsy and move the pediatric EEG-fMRI field forward.

Planar figure-8 coils for ultra-focal and directional micromagnetic brain stimulation.

Recently, white-matter fiber tract pathways carrying neural signals through the brain were shown to follow curved, orthogonal grids. This study focuses on how these white-matter fibers may be selectively excited using micromagnetic stimulation (µMS), a new type of neuronal stimulation, which generates microscopic eddy currents capable of directionally activating neurons. One of the most remarkable properties of this novel type of stimulation is that the µMS fields provide unique directional activation of neuronal elements not seen with traditional electrical stimulation. An initial prototype built with SU-8 based photolithography technology shows that the structure can be fabricated. The coil design was optimized through electrical resistance calculations and electric field simulations to elicit the brain's maximal focal and directional neural responses.

Assessment of radio-frequency heating of a parallel transmit coil in a phantom using multi-echo proton resonance frequency shift thermometry.

We propose a workflow for validating parallel transmission (pTx) radio-frequency (RF) magnetic field heating patterns using Proton-Resonance Frequency shift (PRF)-based MR thermometry. Electromagnetic (EM) and thermal simulations of a 7 T 8-channel dipole coil were done using commercially available software (Sim4Life) to assess RF heating. The fabrication method for a phantom with electrical properties matched to human tissue is also described, along with methods for its electrical and thermal characterisation. Energy was deposited to specific transmit channels, whilst acquiring 3D PRF data using a pair of interleaved RF shim transmit modes. A multi-echo readout and pre-scan stabilisation protocol were used for increased sensitivity and to correct for measurement-to-measurement instabilities. The electrical properties of the phantom were found to be within 10% of the intended values. Adoption of a 14-min stabilisation scan gave sufficient suppression of any evolving background spatial variation in the B0 field to achieve <0.001 °C/mm thermometry drift over 10 min of subsequent scanning. Using two RF shim transmit modes enabled full phantom coverage and combining multiple echo times enabled a 13-54% improvement in the RMSE sensitivity to temperature changes. Combining multiple echoes reduced the peak RMSE by 45% and visually reduced measurement-to-measurement instabilities. A reference fibre optic probe showed temperature deviations from the PRF-estimated temperature to be smaller than 0.5 °C. Given the importance of RF safety in pTx applications, this workflow enables accurate validation of RF heating simulations with minimal additional hardware requirements.

Development, validation, and pilot MRI safety study of a high-resolution, open source, whole body pediatric numerical simulation model.

Numerical body models of children are used for designing medical devices, including but not limited to optical imaging, ultrasound, CT, EEG/MEG, and MRI. These models are used in many clinical and neuroscience research applications, such as radiation safety dosimetric studies and source localization. Although several such adult models have been reported, there are few reports of full-body pediatric models, and those described have several limitations. Some, for example, are either morphed from older children or do not have detailed segmentations. Here, we introduce a 29-month-old male whole-body native numerical model, "MARTIN", that includes 28 head and 86 body tissue compartments, segmented directly from the high spatial resolution MRI and CT images. An advanced auto-segmentation tool was used for the deep-brain structures, whereas 3D Slicer was used to segment the non-brain structures and to refine the segmentation for all of the tissue compartments. Our MARTIN model was developed and validated using three separate approaches, through an iterative process, as follows. First, the calculated volumes, weights, and dimensions of selected structures were adjusted and confirmed to be within 6% of the literature values for the 2-3-year-old age-range. Second, all structural segmentations were adjusted and confirmed by two experienced, sub-specialty certified neuro-radiologists, also through an interactive process. Third, an additional validation was performed with a Bloch simulator to create synthetic MR image from our MARTIN model and compare the image contrast of the resulting synthetic image with that of the original MRI data; this resulted in a "structural resemblance" index of 0.97. Finally, we used our model to perform pilot MRI safety simulations of an Active Implantable Medical Device (AIMD) using a commercially available software platform (Sim4Life), incorporating the latest International Standards Organization guidelines. This model will be made available on the Athinoula A. Martinos Center for Biomedical Imaging website.