Radiofrequency Coil For Magnetic Resonance Imaging Research Articles

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.

Machine Learning for the Design and the Simulation of Radiofrequency Magnetic Resonance Coils: Literature Review, Challenges, and Perspectives.

Radiofrequency (RF) coils for magnetic resonance imaging (MRI) applications serve to generate RF fields to excite the nuclei in the sample (transmit coil) and to pick up the RF signals emitted by the nuclei (receive coil). For the purpose of optimizing the image quality, the performance of RF coils has to be maximized. In particular, the transmit coil has to provide a homogeneous RF magnetic field, while the receive coil has to provide the highest signal-to-noise ratio (SNR). Thus, particular attention must be paid to the coil simulation and design phases, which can be performed with different computer simulation techniques. Being largely used in many sectors of engineering and sciences, machine learning (ML) is a promising method among the different emerging strategies for coil simulation and design. Starting from the applications of ML algorithms in MRI and a short description of the RF coil's performance parameters, this narrative review describes the applications of such techniques for the simulation and design of RF coils for MRI, by including deep learning (DL) and ML-based algorithms for solving electromagnetic problems.

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.

Segmented solenoid RF coils for MRI of ex vivo brain samples at ultra-high field preclinical and clinical scanners

Magnetic resonance imaging (MRI) is a well-known and widespread imaging modality for neuroscience studies and the clinical diagnoses of neurological disorders, mainly due to its capability to visualize brain microstructures and quantify various metabolites. Additionally, its noninvasive nature makes possible the correlation of high-resolution MRI from ex vivo brain samples with histology, supporting the study of neurodegenerative disorders such as Alzheimer's or Parkinson's disease. However, the quality and resolution of ex vivo MRI highly depend on the availability of specialized radiofrequency coils with maximized filling factors for the different sizes and shapes of the samples to be studied. For instance, small, dedicated radiofrequency (RF) coils are not always commercially available in ultrahigh field whole-body MRI scanners. Even for ultrahigh field preclinical scanners, specific RF coils for ex vivo MRI are expensive and not always available. Here, we describe the design and construction of two RF coils based on the solenoid geometry for ex vivo MRI of human brain tissues in a 7T whole-body scanner and for ex vivo MRI of marmoset brain samples in a 9.4T preclinical scanner. We designed the 7T solenoid RF coil to maximize the filling factor of human brain samples conditioned on cassettes for histology, while the 9.4T solenoid was constructed to accommodate marmoset brain samples conditioned in 50 ml centrifuge tubes. Both solenoid designs operate in transceiver mode. The measured B1+ maps show a high level of homogeneity in the imaging volume of interest, with a high signal-to-noise ratio over the imaging volume. High-resolution (80 µm in plane, 500 µm slice thickness) images of human brain samples were acquired with the 7T solenoid, while marmoset brain samples were acquired with an isotropic resolution of 60 µm using the 9.4T solenoid coil.

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.

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.

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.

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.

Experimental setup for bulk susceptibility effect-minimized, multi-orientation MRI of ex vivo tissue samples.

Many conventional ex vivo magnetic resonance imaging (MRI) setups utilize cylindrical or other nonspherical tissue containers which can cause static field (B0 ) inhomogeneity affecting the accuracy of the measurements in an orientation-dependent manner. In this work we demonstrate an experimental method to obtain MRI of ex vivo tissue samples held in a spherical container in order to minimize bulk susceptibility-induced B0 inhomogeneity in arbitrary orientations. B0 inhomogeneity caused by tissue-air susceptibility mismatch can be theoretically eliminated if the surface of susceptibility discontinuity is spherical. This situation can be approximated by putting a tissue sample in a spherical shell filled with materials with tissue-like magnetic susceptibility. We achieved this on an intact monkey brain by (a) holding the brain with a three-dimensional (3D)-printed holder with tissue-like (within 0.5ppm) susceptibility, and (b) enclosing the brain and the holder in an acrylic spherical shell filled with diamagnetic liquid. Furthermore, the sphere and the radio-frequency coil for MRI were mounted on a 3D-printed frame designed to reduce B0 inhomogeneity contributions. The sphere could be rotated freely without disturbing the RF coil to facilitate multi-orientation imaging. We verified our setup by mapping B0 in the monkey brain at 13 different orientations in a human 7T scanner, and measuring orientation-dependent relaxation rates in the white and gray matters of the brain. The results were then compared with a setup where the brain was held inside a cylindrical container. In all orientations, the B0 standard deviation in the brain in the spherical setup (converted to Larmor frequency offset) was less than about 10Hz. This corresponds to two-sigma deviation of B0 of <0.07ppm. The B0 gradient was <9Hz/mm in 95 % of the brain voxels in all orientations. In high-resolution imaging with e.g. voxel size <0.4mm, this corresponds to voxel line broadening of <4Hz (0.013ppm). in the corpus callosum showed distinctly different orientation dependence compared to the gray matter. The B0 uniformity and reliability were much reduced in the cylindrical container setup. We have demonstrated an experimental method to effectively minimize bulk susceptibility-induced B0 perturbation in multi-orientation ex vivo MRI. The method promises to benefit a range of tissue orientation-dependent MR property studies.

Simplified Transfer Function Assessment of Implantable Leads for MRI Safety Evaluations

This paper presents a novel, efficient, and simple method to characterize the transfer function (TF) of leads for active implantable medical devices. The method characterizes the TF using a set of base functions and can be obtained using a few voltage measurements. This procedure requires a few direct measurements of the radiofrequency (RF)-induced voltages on the leads during magnetic resonance imaging (MRI) exposure, and the simulated, or measured, electric field generated by MRI RF coil inside the American Society for Testing and Materials (ASTM) phantom. Consequently, the measurement time of the TF can be reduced and the overall process significantly simplified compared to existing TF measurement methods. The theory of the new method is presented and two examples are given to demonstrate the accuracy and efficiency.

A Novel Flexible Electrotextile 3T MRI RF Coil Array for Carotid Artery Imaging: Design, Characterization, and Prototyping

Magnetic resonance imaging (MRI) is one of the most powerful imaging modality in clinics and is essential for the diagnosis of strokes through carotid artery imaging. The limiting factor for high-quality MRI is the signal-to-noise ratio (SNR) performance of the radio frequency (RF) coils. The current RF surface coils, however, are made of rigid or semiflexible materials with very limited bending properties. As a result, their SNR is limited because they cannot be placed very close to the imaging area, thus receiving noises from parts of the human body, which are not intended to be imaged. Taking advantage of the computerized embroidery and laser cutting technology, in this paper, we utilize electrotextile to design, fabricate, and measure multilayer RF coil array system for 3 Tesla (3T) MRI to improve the SNR performance. The proposed RF coil array system provides an ergonomic and high-performance solution to the 3T MRI systems. A roadmap to systematically design electrotextile RF coil arrays is proposed. RF coil array is characterized to have the accurate resonant frequency, good impedance matching, and low mutual coupling. In addition, magnetic field distribution, bending effects, and human body effects are also discussed. A systematic method to characterize the performance of the electrotextile pattern is studied and used to assist the development and performance characterization. Finally, the high resolution and high SNR images of various kinds of phantoms are obtained using the University of California at Los Angeles (UCLA) Antenna Lab electrotextile coil array after its integration with the 3T MRI scanners at UCLA David Geffen School of Medicine Translational Research Imaging Center. Compared with the conventional surface coil, more than 10 dB SNR increase is observed at the depth of 0.5 cm and 3 dB increase at the depth of 3 cm.

An radio frequency coil design for rat spinal magnetic resonance imaging at 9.4 T

For rat spinal magnetic resonance imaging (MRI) experiments, due to the lower main magnetic field strength, shallower detected depth and poor spatial compatibility of the traditional radio frequency (RF) coil, the image signal-to-noise ratio (SNR) of rat spinal was rather lower. In this paper, a RF coil for rat spinal MRI at 9.4 T was developed to improve the image quality and at the same time to avoid the space limitation while scanning in special conditions (cardiac catheterization, etc.). In this article, open birdcage structure was built and magnetic field distribution was calculated. The phantom and rat spine MRI imaging were experimented at 9.4 T to verify the advantage of the coil in rat spine MRI application.

A Coaxial RF Applicator for Ultra-High Field Human MRI.

To develop a novel radio-frequency (RF) concept for ultra-high field (UHF) human magnetic resonance imaging (MRI) based on a coaxial resonant cavity. A two-channel slotted coaxial cavity RF applicator was designed for human head MRI at 9.4T. Physical dimensions made the proposed conducting structure resonant at the required frequency without tuning lumped elements. Numerical electromagnetic modeling was used to optimize the design. RF safety was assessed with two representative human body models. MR experiments on a 9.4T scanner included gradient echo images and mapping of a circularly polarized RF magnetic field in the human head phantom. The simulations and the phantom MR experiments agreed both qualitatively and quantitatively. The design was relatively simple, robust and required only a few additional reactive elements for the applicator's input impedance matching. The transmit efficiency and homogeneity of the excitation field were only 20% and 4% lower compared to a conventional 8-channel head array. The coaxial RF applicator was feasible for human MRI at UHF and required no lumped elements for its tuning. Imaging performance of the RF applicator was only moderately lower compared to the conventional transmit array, but would be sufficient to provide an anatomical reference for the heteronuclei MRI. An alternative approach with the minimal involvement of lumped elements becomes feasible to design volume-type RF coils for UHF human MRI.

FPGA-based RF interference reduction techniques for simultaneous PET–MRI

The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET–MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling–decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion IID PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution, followed by MRI noise and SNR scans performed with an operating PET module using different clock frequencies and phase patterns. The methods were implemented via firmware design changes without any hardware modifications. This introduces new means of flexibility by enabling adaptive RF interference reduction optimisations in the field, e.g. when using a PET insert with different MRI systems or when different MRI RF coil types are to be operated with the same PET detector.

RESCUE - Reduction of MRI SNR Degradation by Using an MR-Synchronous Low-Interference PET Acquisition Technique

Devices aiming at combined Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) to enable simultaneous PET/MR image acquisition have to fulfill demanding requirements to avoid mutual magnetic- as well as electromagnetic-field-related interferences which lead to image quality degradation. Particularly Radio-Frequency (RF)-field-related interferences between PET and MRI may lead to MRI SNR reduction, thereby deteriorating MR image quality. RF shielding of PET electronics is therefore commonly applied to reduce RF emission and lower the potential coupling into MRI RF coil(s). However, shields introduce eddy-current-induced MRI field distortions and should thus be minimized or ideally omitted. Although the MRI noise floor increase caused by a PET system might be acceptable for many MRI applications, some MRI protocols, such as fast or high-resolution MRI scans, typically suffer from low SNR and might need more attention regarding RF silence to preserve the intrinsic MRI SNR. For such cases, we propose RESCUE, an MRI-synchronously-gated PET data acquisition technique: By interrupting the PET acquisition during MR signal receive phases, PET-related RF emission may be minimized, leading to MRI SNR preservation. Our PET insert $Hyperion II^D$ using Philips Digital Photon Counting (DPC) sensors serves as the platform to demonstrate RESCUE. To make the DPC sensor suitable for RESCUE to be applied for many MRI sequences with acquisition time windows in the range of a few milliseconds, we present in this paper a new technique which enables rapid DPC sensor operation interruption by dramatically lowering the overhead time to interrupt and restart the sensor operation. Procedures to enter and leave gated PET data acquisition may imply sensitivity losses which add to the ones occurring during MRI RF acquisition. For the case of our PET insert, the new DPC quick-interruption technique yields a PET sensitivity loss reduction by a factor of 78 when compared to the loss introduced with the standard start/stop procedure. For instance, PET sensitivity losses related to overhead time are 2.9% in addition to the loss related to PET gating being equal to the MRI RF acquisition duty cycle (14.7%) for an exemplary T1-weighted 3D-FFE MRI sequence. MRI SNR measurement results obtained with one $Hyperion II^D$ Singles Detection Module (SDM) using no RF shield demonstrate a noise floor reduction by a factor of 2.1, getting close to the noise floor level of the SNR reference scan (SDM off-powered) when RESCUE was active.

Radiation induced currents in MRI RF coils: application to linac/MRI integration

The integration of medical linear accelerators (linac) with magnetic resonance imaging (MRI) systems is advancing the current state of image-guided radiotherapy. The MRI in these integrated units will provide real-time, accurate tumor locations for radiotherapy treatment, thus decreasing geometric margins around tumors and reducing normal tissue damage. In the real-time operation of these integrated systems, the radiofrequency (RF) coils of MRI will be irradiated with radiation pulses from the linac. The effect of pulsed radiation on MRI radio frequency (RF) coils is not known and must be studied. The instantaneous radiation induced current (RIC) in two different MRI RF coils were measured and presented. The frequency spectra of the induced currents were calculated. Some basic characterization of the RIC was also done: isolation of the RF coil component responsible for RIC, dependence of RIC on dose rate, and effect of wax buildup placed on coil on RIC. Both the time and frequency characteristics of the RIC were seen to vary with the MRI RF coil used. The copper windings of the RF coils were isolated as the main source of RIC. A linear dependence on dose rate was seen. The RIC was decreased with wax buildup, suggesting an electronic disequilibrium as the cause of RIC. This study shows a measurable RIC present in MRI RF coils. This unwanted current could be possibly detrimental to the signal to noise ratio in MRI and produce image artifacts.