Magnetic Resonance Imaging Radiofrequency Research Articles

Numerical simulation in magnetic resonance imaging radiofrequency dosimetry.

Magnetic Resonance Imaging (MRI) employs a radiofrequency electromagnetic field to create pictures on a computer. The consequences of radiofrequency (RF) absorption include the heating of the tissue and the patient's capacity to remove excess heat. The prospective biological consequences of exposure to radiofrequency electromagnetic fields (RF EMFs) have not yet been demonstrated, and there is not enough evidence on biological hazards to offer a definite response concerning possible RF health dangers. Therefore, it is crucial to research the health concerns in reaction to RF EMFs, considering the entire exposure in terms of patients receiving MRI. Monitoring increases in temperature in-vivo throughout MRI is extremely invasive and has resulted in a rise in the utilization of computational methods to estimate distributions of temperatures. The purpose of this study is to estimate the absorbed power of the brain exposed to RF in patients undergoing brain MRI. A three-dimensional Penne's bio-heat equation was modified to computationally analyze the effects of RF radiation at frequencies exceeding 100 kHz exposures on the brain. The instantaneous temperature distributions of the in-vivo tissue in the brain temperatures measured at a time, t = 20.62 seconds is 0.2 °C and t = 30.92 seconds is 0.4 °C, while the highest temperatures recorded at 1.03 minutes and 2.06 minutes were 0.4 °C and 0.6 °C accordingly. From the temperature distributions of the in-vivo tissue in the brain temperatures measured, there is heat build-up in patients who are exposed to electromagnetic frequency ranges, and, consequently, temperature increases within patients are difficult to prevent. The study has, however, indicated that lengthier imaging duration appears to be related to increasing body temperature.&#xD.

Uncertainty Quantification in SAR Induced by Ultra-High-Field MRI RF Coil via High-Dimensional Model Representation.

As magnetic field strength in Magnetic Resonance Imaging (MRI) technology increases, maintaining the specific absorption rate (SAR) within safe limits across human head tissues becomes challenging due to the formation of standing waves at a shortened wavelength. Compounding this challenge is the uncertainty in the dielectric properties of head tissues, which notably affects the SAR induced by the radiofrequency (RF) coils in an ultra-high-field (UHF) MRI system. To this end, this study introduces a computational framework to quantify the impacts of uncertainties in head tissues' dielectric properties on the induced SAR. The framework employs a surrogate model-assisted Monte Carlo (MC) technique, efficiently generating surrogate models of MRI observables (electric fields and SAR) and utilizing them to compute SAR statistics. Particularly, the framework leverages a high-dimensional model representation technique, which constructs the surrogate models of the MRI observables via univariate and bivariate component functions, approximated through generalized polynomial chaos expansions. The numerical results demonstrate the efficiency of the proposed technique, requiring significantly fewer deterministic simulations compared with traditional MC methods and other surrogate model-assisted MC techniques utilizing machine learning algorithms, all while maintaining high accuracy in SAR statistics. Specifically, the proposed framework constructs surrogate models of a local SAR with an average relative error of 0.28% using 289 simulations, outperforming the machine learning-based surrogate modeling techniques considered in this study. Furthermore, the SAR statistics obtained by the proposed framework reveal fluctuations of up to 30% in SAR values within specific head regions. These findings highlight the critical importance of considering dielectric property uncertainties to ensure MRI safety, particularly in 7 T MRI systems.

Citizen science approach to assessing patient perception of MRI with flexible radiofrequency coils

Magnetic Resonance Imaging (MRI) is a major medical imaging modality, which is non-invasive and provides unique soft tissue contrast without ionizing radiation. The successful completion of MRI exams critically depends on patient compliance, and, thus patient comfort. The design, appearance and usability of local MRI radiofrequency (RF) coils potentially influences the patients’ perception of the exam. However, systematic investigations and empirical evidence for these aspects are missing. A questionnaire specifically evaluating the impact of RF coils on patient comfort in MRI would be a valuable addition to clinical studies comparing the performance of novel flexible RF coils with standard rigid coils. This paper describes the development of such a questionnaire in the scope of a citizen science (CS) initiative conducted with a group of students at the upper secondary school level. In this work, the CS initiative is presented in the format of a case report and its impact on scientific projects and the students’ education is outlined. The resulting questionnaire is made available in German and English so as to be directly applicable by researchers working on the clinical evaluation of novel RF coils or the comfort evaluation of specific hardware setups in general.

On the Relationship Between Impedances of Active Implantable Medical Devices and Device Safety Under MRI RF Emission

Impedances of different portions of active implantable medical devices (AIMDs) can influence its magnetic resonance imaging (MRI) radio-frequency (RF) safety dramatically. To better understand this behavior, in this article, we analytically derive relationships between the impedances of AIMDs and the MRI RF safety. Numerical simulations and measurements are performed to validate the proposed relationships. In addition, effective measurement setups for the AIMD impedances are proposed. The analysis in this article gives a clear design strategy for MR-conditional safe AIMDs.

A hybrid 2D-FDTD/3D-MoM method used for the analysis of MRI RF coils

The design of radiofrequency (RF) coils is crucial for ultra-high field (UHF) magnetic resonance imaging (MRI) systems. To analyze RF coils, various numerical methods, such as finite-difference time-domain (FDTD) and method of moments (MoM), are usually adopted. In this paper, we present a novel hybrid approach that combines a two-dimensional (2D) FDTD with a three-dimensional (3D) MoM to analyze MRI RF problems. In our algorithm, the MoM is utilized for calculating the coil current, and FDTD is assigned for solving the electromagnetic (EM) fields in the imaging region. The hybrid method achieves superior efficiency and acceptable accuracy than using either method individually. To validate the hybrid method, we analyze an ellipse coil loaded with a uniform phantom and a realistic human head model, with the objective of tailoring the magnetic field intensity by adding a multilayer dielectric pad (DP). The results show an improvement in the magnetic field after optimizing the DP configuration. These simulation studies indicate the potential of the new numerical method for the design and analysis of RF systems for ultra-high field applications.

Numerical simulations of an integrated radio-frequency/wireless coil design for simultaneous acquisition and wireless transfer of magnetic resonance imaging data

Objective. A novel magnetic resonance imaging (MRI) radio-frequency (RF) coil design, termed an integrated RF/wireless (iRFW) coil design, can simultaneously perform MRI signal reception and far-field wireless data transfer with the same coil conductors between the coil in the scanner bore and an access point (AP) on the scanner room wall. The objective of this work is to optimize the design inside the scanner bore to provide a link budget between the coil and the AP for the wireless transmission of MRI data. Approach. Electromagnetic simulations were performed at the Larmor frequency of a 3T scanner and in a WiFi wireless communication band to optimize the radius and position of an iRFW coil located near the head of a human model inside the scanner bore, which were validated by performing both imaging and wireless experiments. Main Results. The simulated iRFW coil with a 40 mm radius positioned near the model forehead provided: a signal-to-noise ratio (SNR) comparable to that of a traditional RF coil with the same radius and position, a power absorbed by the human model within regulatory limits, and a gain pattern in the scanner bore resulting in a link budget of 51.1 dB between the coil and an AP located behind the scanner 3 m from the isocenter, which would be sufficient to wirelessly transfer MRI data acquired with a 16-channel coil array. The SNR, gain pattern, and link budget for initial simulations were validated by experimental measurements in an MRI scanner and anechoic chamber to provide confidence in this methodology. These results show that the iRFW coil design must be optimized within the scanner bore for the wireless transfer of MRI data. Significance. The MRI RF coil array coaxial cable assembly connected to the scanner increases patient setup time, can present a serious burn risk to patients and is an obstacle to the development of the next generation of lightweight, flexible or wearable coil arrays that provide an improved coil sensitivity for imaging. Significantly, the RF coaxial cables and corresponding receive chain electronics can be removed from within the scanner by integrating the iRFW coil design into an array for the wireless transmission of MRI data outside of the bore.

A hybrid FDTD/MoM algorithm with a conformal Huygens' equivalent surface for MRI RF coil design and analysis

Accurate design and analysis of radiofrequency (RF) coils are crucial for ultra-high field (UHF) magnetic resonance imaging (MRI) applications. To improve the numerical accuracy of electromagnetic (EM) simulations, we propose a hybrid finite difference time domain (FDTD)/method of moments (MoM) method. Unlike conventional cuboid-like Huygens' equivalent surfaces (HES), we proposed to use a conformal HES to interface the EM data of the FDTD and MoM zone. The shape and size of the conformal surface can be adjusted to fit different RF coil models, thus broadening the application range of the hybrid FDTD/MoM method. Two numerical models: an 8-channel ellipse array, and an 8-channel bent dipole array, are simulated and compared with the conventional HES counterpart. Numerical results demonstrate the capability of the conformal HES method in the analysis of RF coils.

Effect of field strength on RF power deposition near conductive leads: A simulation study of SAR in DBS lead models during MRI at 1.5 T-10.5 T.

Since the advent of magnetic resonance imaging (MRI) nearly four decades ago, there has been a quest for ever-higher magnetic field strengths. Strong incentives exist to do so, as increasing the magnetic field strength increases the signal-to-noise ratio of images. However, ensuring patient safety becomes more challenging at high and ultrahigh field MRI (i.e., ≥3 T) compared to lower fields. The problem is exacerbated for patients with conductive implants, such as those with deep brain stimulation (DBS) devices, as excessive local heating can occur around implanted lead tips. Despite extensive effort to assess radio frequency (RF) heating of implants during MRI at 1.5 T, a comparative study that systematically examines the effects of field strength and various exposure limits on RF heating is missing. This study aims to perform numerical simulations that systematically compare RF power deposition near DBS lead models during MRI at common clinical and ultra-high field strengths, namely 1.5, 3, 7, and 10.5 T. Furthermore, we assess the effects of different exposure constraints on RF power deposition by imposing limits on either the B1+ or global head specific absorption rate (SAR) as these two exposure limits commonly appear in MRI guidelines. We created 33 unique DBS lead models based on postoperative computed tomography (CT) images of patients with implanted DBS devices and performed electromagnetic simulations to evaluate the SAR of RF energy in the tissue surrounding lead tips during RF exposure at frequencies ranging from 64 MHz (1.5 T) to 447 MHz (10.5 T). The RF exposure was implemented via realistic MRI RF coil models created based on physical prototypes built in our institutions. We systematically examined the distribution of local SAR at different frequencies with the input coil power adjusted to either limit the B1+ or the global head SAR. The MRI RF coils at higher resonant frequencies generated lower SARs around the lead tips when the global head SAR was constrained. The trend was reversed when the constraint was imposed on B1+. At higher static fields, MRI is not necessarily more dangerous than at lower fields for patients with conductive leads. Specifically, when a conservative safety criterion, such as constraints on the global SAR, is imposed, coils at a higher resonant frequency tend to generate a lower local SAR around implanted leads due to the decreased B1+ and, by proxy, E field levels.

Application of Machine learning to predict RF heating of cardiac leads during magnetic resonance imaging at 1.5 T and 3 T: A simulation study

Predicting magnetic resonance imaging (MRI)-induced heating of elongated conductive implants, such as leads in cardiovascular implantable electronic devices, is essential to assessing patient safety. Phantom experiments have traditionally been used to estimate radio-frequency (RF) heating of implants, but they are time-consuming. Recently, machine learning has shown promise for fast prediction of RF heating of orthopaedic implants when the implant position within the MRI RF coil was predetermined. We explored whether deep learning could be applied to predict RF heating of conductive leads with variable positions and orientations during MRI at 1.5 T and 3 T. Models of 600 cardiac leads with clinically relevant trajectories were generated, and electromagnetic simulations were performed to calculate the maximum of the 1 g-averaged specific absorption rate (SAR) of RF energy at the tips of lead models during MRI at 1.5 T and 3 T. Neural networks were trained to predict the maximum SAR at the lead tip from the knowledge of the coordinates of points along the lead trajectory. Despite the large range of SAR values (∼230 W/kg to ∼ 3200 W/kg and ∼ 10 W/kg to ∼ 3300 W/kg), the root- mean-square error of the predicted vs ground truth SAR remained at 223 W/kg and 206 W/kg, with the R2 scores of 0.89 and 0.85 on the testing set for 1.5 T and 3 T models, respectively. The results suggest that machine learning is a promising approach for fast assessment of RF heating of lead-like implants when only the knowledge of the lead geometry and MRI RF coil features are in hand.

A hybrid FDTD/MoM algorithm with a non-uniform grid for MRI RF coil design

In ultra-high-field (UHF) magnetic resonance imaging (MRI) applications, the design and analysis of high-frequency radio frequency (RF) coils requires full-wave electromagnetic (EM) methods that can handle complex field-tissue interactions. Using a Huygens' equivalent surface, the Method of Moments (MoM) and the Finite-Difference Time-Domain (FDTD) algorithm can be combined to accurately model the high-frequency RF coils. In previous research, a uniform FDTD mesh structure was considered, providing a compromised solution for coil-tissue interactions. This paper proposes a hybrid FDTD/MoM algorithm with non-uniform meshes. The fine mesh domain is set at the Huygens' surface, and the other domain uses coarse meshes. The proposed algorithms are strictly validated, and their computational performance is compared against conventional methods. Results show that the new algorithm can improve the calculation efficiency without losing accuracy. Specifically, compared with the uniform FDTD method, the numerical difference between both hybrid methods remains at 3.2%. Still, the calculation time of the non-uniform grid algorithm is reduced by 64.2%, demonstrating the effectiveness of the new algorithm for modeling RF coils for UHF-MRI applications.

The Position and Orientation of the Pulse Generator Affects MRI RF Heating of Epicardial Leads in Children.

Infants and children with congenital heart defects often receive a cardiac implantable electronic device (CIED). Because transvenous access to the heart is difficult in patients with small veins, the majority of young children receive epicardial CIEDs. Unfortunately, however, once an epicardial CIED is placed, patients are no longer eligible to receive magnetic resonance imaging (MRI) exams due to the unknown risk of MRI-induced radiofrequency (RF) heating of the device. Although many studies have assessed the role of device configuration in RF heating of endocardial CIEDs in adults, such case for epicardial devices in pediatric patients is relatively unexplored. In this study, we evaluated the variation in RF heating of an epicardial lead due to changes in the lateral position and orientation of the implantable pulse generator (IPG). We found that changing the orientation and position of the IPG resulted in a five-fold variation in the RF heating at the lead's tip. Maximum heating was observed when the IPG was moved to a left lateral abdominal position of patient, and minimum heating was observed when the IPG was positioned directly under the heart. Clinical Relevance- This study examines the role of device configuration on MRI-induced RF heating of an epicardial CIED in a pediatric phantom. Results could help pediatric cardiac surgeons to modify device implantation to reduce future risks of MRI in patients.

Metamaterial Liner for MRI Excitation—Part 1: Theory, Modeling and Design

This work details the practical and theoretical concepts underlying the design of a metamaterial (MM) liner for magnetic resonance imaging (MRI) radio frequency (RF) excitation. The Part 2 companion to this paper details the practical design and performance comparison to a conventional birdcage coil. The operation of the MM liner relies on specifically engineered effective permittivity and permeability of a thin liner on the inner surface of the MRI bore, to enable the propagation of electromagnetic (EM) waves at frequencies below the natural-cutoff of the bore itself. Here, the effective anisotropic EM properties of the MM liner structure are calculated by a combined circuit- and effective-medium model, and the analytical dispersion characteristics are compared to full-wave eigenmode simulations. The results of the effective medium model representation of the MM liner agree fundamentally with simulation. The model may thus assist the design and tuning of the liner to achieve a standing-wave resonance with field distribution and mode spacing suitable for MRI RF excitation. The transmission properties and EM fields of a full-scale MM lined bore for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{B}_{0}=4.7$ </tex-math></inline-formula> T MRI are simulated including realistic losses. These methods enable robust design of thin MM liners for arbitrary bore sizes and B <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> field strengths.

Predicting RF Heating of Conductive Leads During Magnetic Resonance Imaging at 1.5 T: A Machine Learning Approach.

The number of patients with active implantable medical devices continues to rise in the United States and around the world. It is estimated that 50-75% of patients with conductive implants will need magnetic resonance imaging (MRI) in their lifetime. A major risk of performing MRI in patients with elongated conductive implants is the radiofrequency (RF) heating of the tissue surrounding the implant's tip due to the antenna effect. Currently, applying full-wave electromagnetic simulation is the standard way to predict the interaction of MRI RF fields with the human body in the presence of conductive implants; however, these simulations are notoriously extensive in terms of memory requirement and computational time. Here we present a proof-of-concept simulation study to demonstrate the feasibility of applying machine learning to predict MRI-induced power deposition in the tissue surrounding conductive wires. We generated 600 clinically relevant trajectories of leads as observed in patients with cardiac conductive implants and trained a feedforward neural network to predict the 1g-averaged SAR at the lead tips knowing only the background field of MRI RF coil and coordinates of points along the lead trajectory. Training of the network was completed in 11.54 seconds and predictions were made within a second with R2 = 0.87 and Root Mean Squared Error (RMSE) = 14.5 W/kg. Our results suggest that machine learning could provide a promising approach for safety assessment of MRI in patients with conductive leads.Clinical Relevance- Machine learning can potentially allow real-time assessment of MRI RF safety in patients with conductive leads when only the knowledge of lead's trajectory (image-based) and MRI RF coil features (vendor-specific) are in hand.

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.

Receiver phase alignment using fitted SVD derived sensitivities from routine prescans

Magnetic resonance imaging radio frequency arrays are composed of multiple receive coils that have their signals combined to form an image. Combination requires an estimate of the radio frequency coil sensitivities to align signal phases and prevent destructive interference. At lower fields this can be accomplished using a uniform physical reference coil. However, at higher fields, uniform volume coils are lacking and, when available, suffer from regions of low receive sensitivity that result in poor sensitivity estimation and combination. Several approaches exist that do not require a physical reference coil but require manual intervention, specific prescans, or must be completed post-acquisition. This makes these methods impractical for large multi-volume datasets such as those collected for novel types of functional MRI or quantitative susceptibility mapping, where magnitude and phase are important. This pilot study proposes a fitted SVD method which utilizes existing combination methods to create a phase sensitive combination method targeted at large multi-volume datasets. This method uses any multi-image prescan to calculate the relative receive sensitivities using voxel-wise singular value decomposition. These relative sensitivities are fitted to the solid harmonics using an iterative least squares fitting algorithm. Fits of the relative sensitivities are used to align the phases of the receive coils and improve combination in subsequent acquisitions during the imaging session. This method is compared against existing approaches in the human brain at 7 Tesla by examining the combined data for the presence of singularities and changes in phase signal-to-noise ratio. Two additional applications of the method are also explored, using the fitted SVD method in an asymmetrical coil and in a case with subject motion. The fitted SVD method produces singularity-free images and recovers between 95–100% of the phase signal-to-noise ratio depending on the prescan data resolution. Using solid harmonic fitting to interpolate singular value decomposition derived receive sensitivities from existing prescans allows the fitted SVD method to be used on all acquisitions within a session without increasing exam duration. Our fitted SVD method is able to combine imaging datasets accurately without supervision during online reconstruction.

A Novel Device Model Validation Strategy for 1.5- and 3-T MRI Heating Safety Assessment

This article presents a novel test instrument and strategy for active implantable medical device (AIMD) model validation under a radiofrequency (RF) field generated by a magnetic resonance imaging (MRI) system. A high electric field generator is developed as an alternative instrument for standard MRI RF coils. This system is both compact and power efficient. In addition, a set of validation pathways are proposed based on the Hadamard matrix. These pathways provide low correlations among incident electric fields and yet generate relatively high temperature rises. Two generic AIMDs with different lengths are used to validate the strategy experimentally. It is demonstrated that this method provides an efficient and effective alternative for future AIMD model validation under MRI RF emissions.

Reducing MRI RF-induced heating for the external fixation using capacitive structures

This paper presents a generic method to reduce the radiofrequency (RF) induced heating of external fixation devices during the magnetic resonance imaging (MRI) procedure. A simplified equivalent circuit model was developed to illustrate the interaction between the external fixation device and the MRI RF field. Carefully designed mechanical structures, which utilize capacitive reactance from the circuit model, were applied to the external fixation device to mitigate the coupling between the external fixation device and the MRI RF field for RF-induced heating reduction. Both numerical and experimental studies were performed to demonstrate the validity of the circuit model and the effectiveness of the proposed method. By adding capacitive structures in both the clamp-pin and rod-clamp joints, the peak specific absorption rate averaged in 1 gram (SAR1g) near the pin tips were reduced from 760.4 W kg−1 to 12.0 W kg−1 at 1.5 T and 391.5 W kg−1 to 25.2 W kg−1 at 3 T from numerical simulations. Experimental results showed that RF-induced heating was reduced from 7.85 °C to 1.01 °C at 1.5 T and from 16.70 °C to 0.32 °C at 3 T for the external fixation device studied here. The carefully designed capacitive structures can be used to detune the coupling between the external fixation device and the MRI fields to reduce the RF-induced heating in the human body for both 1.5 T and 3 T MRI systems. However, as RF-induced heating is very device and design specific all devices must be thoroughly tested based on its final design.

Evaluating Accuracy of Numerical Simulations in Predicting Heating of Wire Implants During MRI at 1.5 T.

Patients with long conductive implants such as deep brain stimulation (DBS) leads are often denied access to magnetic resonance imaging (MRI) exams due to safety concerns associated with radiofrequency (RF) heating of implants. Experimental temperature measurements in tissue-mimicking gel phantoms under MRI RF exposure conditions are common practices to predict in-vivo heating in the tissue surrounding wire implants. Such experiments are both expensive-as they require access to MRI units-and time-consuming due to complex implant setups. Recently, full-wave numerical simulations, which include realistic MRI RF coil models and human phantoms, are suggested as an alternative to experiments. There is however, little literature available on the accuracy of such numerical models against direct thermal measurements. This study aimed to evaluate the agreement between simulations and measurements of temperature rise at the tips of wire implants exposed to RF exposure at 64 MHz (1.5 T) for different implant trajectories typically encountered in patients with DBS leads. Heating was assessed in seven patient-derived lead configurations using both simulations and RF heating measurements during imaging of an anthropomorphic head phantom with implanted wires. We found substantial variation in RF heating as a function of lead trajectory; there was a 9.5-fold and 9-fold increase in temperature rise from ID1 to ID7 during simulations and experimental measurements, respectively. There was a strong correlation (r2 = 0.74) between simulated and measured temperatures for different lead trajectories. The maximum difference between simulated and measured temperature was 0.26 °C with simulations overestimating the temperature rise.

Erratum to “A Transmission Line Model for the Evaluation of MRI RF-Induced Fields on Active Implantable Medical Devices”

In this paper, a transmission line model is applied to evaluate magnetic resonance imaging (MRI) radio frequency (RF)-induced fields on active implantable medical devices (AIMDs). The influences of the AIMD lead body, the lead tip, and the implantable pulse generator (IPG) are analyzed based on this model. The transmission line model, together with the transfer function method, forms a systematic approach for analyzing the MRI RF safety problems. It can be used to understand the mechanisms and predict the MRI RF safety risks for various IPGs and leads. Both numerical simulation and measurement results demonstrate the accuracy and the efficiency of this method.

An Absorbing Radio Frequency Shield to Reduce RF Heating Induced by Deep Brain Stimulator During 1.5-T MRI

In this paper, an absorbing radio frequency shield (ARFS) is developed to reduce the radio frequency (RF)-induced heating for active implantable medical device (AIMD) during magnetic resonance imaging (MRI). Using the ARFS, the strength of the incident electric field within the shielded region is significantly decreased, and subsequently the induced temperature rises near the tip of AIMD. Both numerical and experimental studies show that the proposed design of ARFS can effectively reduce the temperature rise induced by an AIMD and can mitigate the MRI RF heating risks for patients with AIMDs.