Navigated intraoperative ultrasound in pediatric brain tumors.

PURPOSE: The aim of this study was to evaluate the diagnostic value and accuracy of navigated intraoperative ultrasound (iUS) in pediatric oncological neurosurgery as compared to intraoperative magnetic resonance imaging (iMRI). METHODS: A total of 24 pediatric patients undergoing tumor debulking surgery with iUS, iMRI, and neuronavigation were included in this study. Prospective acquisition of iUS images was done at two time points during the surgical procedure: (1) before resection for tumor visualization and (2) after resection for residual tumor assessment. Dice similarity coefficients (DSC), Hausdorff distances 95th percentiles (HD95) and volume differences, sensitivity, and specificity were calculated for iUS segmentations as compared to iMRI. RESULTS: A high correlation (R = 0.99) was found for volume estimation as measured on iUS and iMRI before resection. A good spatial accuracy was demonstrated with a median DSC of 0.72 (IQR 0.14) and a median HD95 percentile of 4.98 mm (IQR 2.22 mm). The assessment after resection demonstrated a sensitivity of 100% and a specificity of 84.6% for residual tumor detection with navigated iUS. A moderate accuracy was observed with a median DSC of 0.58 (IQR 0.27) and a median HD95 of 5.84 mm (IQR 4.04 mm) for residual tumor volumes. CONCLUSION: We found that iUS measurements of tumor volume before resection correlate well with those obtained from preoperative MRI. The accuracy of residual tumor detection was reliable as compared to iMRI, indicating the suitability of iUS for directing the surgeon's attention to areas suspect for residual tumor. Therefore, iUS is considered as a valuable addition to the neurosurgical armamentarium. TRIAL REGISTRATION NUMBER AND DATE: PMCLAB2023.476, February 12th 2024.

In vivo B 1 + enhancement of calf MRI at 7 T via optimized flexible metasurfaces.

PURPOSE: Ultrahigh field (≥7 T) MRI is at the cutting edge of medical imaging, enabling enhanced spatial and spectral resolution as well as enhanced susceptibility contrast. However, transmit ( B 1 + $$ {\mathrm{B}}_1^{+} $$ ) field inhomogeneity due to standing wave effects caused by the shortened RF wavelengths at 7 T is still a challenge to overcome. Novel hardware methods such as dielectric pads have been shown to improve the B 1 + $$ {\mathrm{B}}_1^{+} $$ field inhomogeneity but are currently limited in their corrective effect by the range of high-permittivity materials available and have a fixed shelf life. In this work, an optimized metasurface design is presented that demonstrates in vivo enhancement of the B 1 + $$ {\mathrm{B}}_1^{+} $$ field. METHODS: A prototype metasurface was optimized by an empirical capacitor sweep and by varying the period size. Phantom temperature experiments were performed to evaluate potential metasurface heating effects during scanning. Lastly, in vivo gradient echo images and B 1 + $$ {\mathrm{B}}_1^{+} $$ maps were acquired on five healthy subjects on a 7 T system. Dielectric pads were also used as a comparison throughout the work as a standard comparison. RESULTS: The metasurfaces presented here enhanced the average relative SNR of the gradient echo images by a factor of 2.26 compared to the dielectric pads factor of 1.61. Average B 1 + $$ {\mathrm{B}}_1^{+} $$ values reflected a similar enhancement of 27.6% with the metasurfaces present versus 8.9% with the dielectric pads. CONCLUSION: The results demonstrate that metasurfaces provide superior performance to dielectric padding as shown by B 1 + $$ {\mathrm{B}}_1^{+} $$ maps reflecting their direct effects and resulting enhancements in image SNR at 7 T.

Flexible metasurface for improving brain imaging at 7T.

PURPOSE: Ultra-high field MRI offers unprecedented detail for noninvasive visualization of the human brain. However, brain imaging is challenging at 7T due to the B 1 + $$ {}_1^{+} $$ field inhomogeneity, which results in signal intensity drops in temporal lobes and a bright region in the brain center. This study aims to evaluate using a metasurface to improve brain imaging at 7T and simplify the investigative workflow. METHODS: Two flexible metasurfaces comprising a periodic structure of copper strips and parallel-plate capacitive elements printed on an ultra-thin substrate were optimized for brain imaging and implemented via PCB. We considered two setups: (1) two metasurfaces located near the temporal lobes and (2) one metasurface placed near the occipital lobe. The effect of metasurface placement on the transmit efficiency and specific absorption rate was evaluated via electromagnetic simulation studies with voxelized models. In addition, their impact on signal-to-noise ratio (SNR) and diagnostic image quality was assessed in vivo for two male and one female volunteers. RESULTS: Placement of metasurfaces near the regions of interest led to an increase in homogeneity of the transmit field by 5% and 10.5% in the right temporal lobe and occipital lobe for a male subject, respectively. SAR efficiency values changed insignificantly, dropping by less than 8% for all investigated setups. In vivo studies also confirmed the numerically predicted improvement in field distribution and receive sensitivity in the desired ROI. CONCLUSION: Optimized metasurfaces enable homogenizing transmit field distribution in the brain at 7T. The proposed lightweight and flexible structure can potentially provide MR examination with higher diagnostic value images.

A review of recent developments and applications of high-permittivity dielectric shimming in magnetic resonance.

We present a review outlining the basic mechanism, background, recent technical developments, and clinical applications of aqueous dielectric padding in the field of MRI. Originally meant to be a temporary solution, it has gained traction as an effective method for correcting B1 + inhomogeneities due to the unique properties of the calcium titanate and barium titanate perovskites used. Aqueous dielectric pads have used a variety of high-permittivity materials over the years to improve the quality of MRI acquisitions at 1.5 and 3 T and more recently for 7 T neuroimaging applications. The technical development and assessment of these pads have been advanced by an increased use of mathematical modeling and electromagnetic simulations. These tools have allowed for a more complete understanding of the physical interactions between dielectric pads and the RF coil, making testing and safety assessments more accurate. The ease of use and effectiveness that dielectric pads offer have allowed them to become more commonplace in tackling imaging challenges in more clinically focused environments. More recently, they have seen usage not only in anatomical imaging methods but also in specialized metabolic imaging sequences such as GluCEST and NOEMTR . New colossally high-permittivity materials have been proposed; however, practical utilization has been a continued challenge due to unfavorable frequency dependences as well as safety limitations. A new class of metasurfaces has been under development to address the shortcomings of conventional dielectric padding while also providing increased performance in enhancing MRI images.

An anthropomorphic thyroid phantom for ultrasound-guided radiofrequency ablation of nodules.

BACKGROUND: Needle-based procedures, such as fine needle aspiration and thermal ablation, are often applied for thyroid nodule diagnosis and therapeutic purposes, respectively. With blood vessels and nerves nearby, these procedures can pose risks in damaging surrounding critical structures. PURPOSE: The development and validation of innovative strategies to manage these risks require a test object with well-characterized physical properties. For this work, we focus on the application of ultrasound-guided thermal radiofrequency ablation. METHODS: We have developed a single-use anthropomorphic phantom mimicking the thyroid and surrounding anatomical and physiological structures that are relevant to ultrasound-guided thermal ablation. The phantom was composed of a mixture of polyacrylamide, water, and egg white extract and was cast using molds in multiple steps. The thermal, acoustical, and electrical characteristics were experimentally validated. The ablation zones were analyzed via non-destructive T2 -weighted magnetic resonance imaging scans utilizing the relaxometry changes of coagulated egg albumen, and the temperature distribution was monitored using an array of fiber Bragg grating sensors. RESULTS: The physical properties of the phantom were verified both on ultrasound as well as in terms of the phantom response to thermal ablation. The final temperature achieved (92°C), the median percentage of the nodule ablated (82.1%), the median volume ablated outside the nodule (0.8 mL), and the median number of critical structures affected (0) were quantified. CONCLUSION: An anthropomorphic phantom that can provide a realistic model for development and training in ultrasound-guided needle-based thermal interventions for thyroid nodules has been presented.

The Development and External Validation of Artificial Intelligence-Driven MRI-Based Models to Improve Prediction of Lesion-Specific Extraprostatic Extension in Patients with Prostate Cancer.

Adequate detection of the histopathological extraprostatic extension (EPE) of prostate cancer (PCa) remains a challenge using conventional radiomics on 3 Tesla multiparametric magnetic resonance imaging (3T mpMRI). This study focuses on the assessment of artificial intelligence (AI)-driven models with innovative MRI radiomics in predicting EPE of prostate cancer (PCa) at a lesion-specific level. With a dataset encompassing 994 lesions from 794 PCa patients who underwent robot-assisted radical prostatectomy (RARP) at two Dutch hospitals, the study establishes and validates three classification models. The models were validated on an internal validation cohort of 162 lesions and an external validation cohort of 189 lesions in terms of discrimination, calibration, net benefit, and comparison to radiology reporting. Notably, the achieved AUCs ranged from 0.86 to 0.91 at the lesion-specific level, demonstrating the superior accuracy of the random forest model over conventional radiological reporting. At the external test cohort, the random forest model was the best-calibrated model and demonstrated a significantly higher accuracy compared to radiological reporting (83% vs. 67%, p = 0.02). In conclusion, an AI-powered model that includes both existing and novel MRI radiomics improves the detection of lesion-specific EPE in prostate cancer.

Deep learning for automated contouring of neurovascular structures on magnetic resonance imaging for prostate cancer patients.

Background and purpose: Manual contouring of neurovascular structures on prostate magnetic resonance imaging (MRI) is labor-intensive and prone to considerable interrater disagreement. Our aim is to contour neurovascular structures automatically on prostate MRI by deep learning (DL) to improve workflow and interrater agreement. Materials and methods: Segmentation of neurovascular structures was performed on pre-treatment 3.0 T MRI data of 131 prostate cancer patients (training [n = 105] and testing [n = 26]). The neurovascular structures include the penile bulb (PB), corpora cavernosa (CCs), internal pudendal arteries (IPAs), and neurovascular bundles (NVBs). Two DL networks, nnU-Net and DeepMedic, were trained for auto-contouring on prostate MRI and evaluated using volumetric Dice similarity coefficient (DSC), mean surface distances (MSD), Hausdorff distances, and surface DSC. Three radiation oncologists evaluated the DL-generated contours and performed corrections when necessary. Interrater agreement was assessed and the time required for manual correction was recorded. Results: nnU-Net achieved a median DSC of 0.92 (IQR: 0.90-0.93) for the PB, 0.90 (IQR: 0.86-0.92) for the CCs, 0.79 (IQR: 0.77-0.83) for the IPAs, and 0.77 (IQR: 0.72-0.81) for the NVBs, which outperformed DeepMedic for each structure (p < 0.03). nnU-Net showed a median MSD of 0.24 mm for the IPAs and 0.71 mm for the NVBs. The median interrater DSC ranged from 0.93 to 1.00, with the majority of cases (68.9%) requiring manual correction times under two minutes. Conclusions: DL enables reliable auto-contouring of neurovascular structures on pre-treatment MRI data, easing the clinical workflow in neurovascular-sparing MR-guided radiotherapy.

Radiofrequency safety of high permittivity pads in MRI-Impact of insulation material.

PURPOSE: High permittivity dielectric pads are known to be effective for tailoring the RF field and improving image quality in high field MRI. Despite a number of studies reporting benign specific absorption rate (SAR) effects, their "universal" safety remains an open concern. In this work, we evaluate the impact of the insulation material in between the pad and the body, using both RF simulations as well as phantom experiments. METHODS: A 3T configuration with high permittivity material was simulated and characterized experimentally in terms of B1 + fields and RF power absorption, both with and without electrical insulation in between the high permittivity material and the sample. Different insulation conditions were compared, and electromagnetic analyses on the induced current density were performed to elucidate the effect. RESULTS: Increases in RF heating of up to 49% were observed experimentally in a tissue-mimicking phantom after removing the material insulation. The B1 + magnitude and RF transceive phase were not affected. Simulations indicated that an insulation thickness of 0.5-2 mm should be accounted for in numerical models in order to ensure reliable results. CONCLUSION: A reliable RF safety assessment of high permittivity dielectric pads requires accounting for the insulating properties of the plastic encasing. Ignoring the electrical insulation can lead to erroneous results with substantial increases in local SAR at the interface. Conversely, the material insulation does not need to be modeled to predict the B1 + effects during the design of the pad geometry.

Personalized local SAR prediction for parallel transmit neuroimaging at 7T from a single T1-weighted dataset.

PURPOSE: Parallel RF transmission (PTx) is one of the key technologies enabling high quality imaging at ultra-high fields (≥7T). Compliance with regulatory limits on the local specific absorption rate (SAR) typically involves over-conservative safety margins to account for intersubject variability, which negatively affect the utilization of ultra-high field MR. In this work, we present a method to generate a subject-specific body model from a single T1-weighted dataset for personalized local SAR prediction in PTx neuroimaging at 7T. METHODS: Multi-contrast data were acquired at 7T (N = 10) to establish ground truth segmentations in eight tissue types. A 2.5D convolutional neural network was trained using the T1-weighted data as input in a leave-one-out cross-validation study. The segmentation accuracy was evaluated through local SAR simulations in a quadrature birdcage as well as a PTx coil model. RESULTS: The network-generated segmentations reached Dice coefficients of 86.7% ± 6.7% (mean ± SD) and showed to successfully address the severe intensity bias and contrast variations typical to 7T. Errors in peak local SAR obtained were below 3.0% in the quadrature birdcage. Results obtained in the PTx configuration indicated that a safety margin of 6.3% ensures conservative local SAR estimates in 95% of the random RF shims, compared to an average overestimation of 34% in the generic "one-size-fits-all" approach. CONCLUSION: A subject-specific body model can be automatically generated from a single T1-weighted dataset by means of deep learning, providing the necessary inputs for accurate and personalized local SAR predictions in PTx neuroimaging at 7T.

Design and evaluation of a modular multimodality imaging phantom to simulate heterogeneous uptake and enhancement patterns for radiomic quantification in hybrid imaging: A feasibility study.

BACKGROUND: Accuracy and precision assessment in radiomic features is important for the determination of their potential to characterize cancer lesions. In this regard, simulation of different imaging conditions using specialized phantoms is increasingly being investigated. In this study, the design and evaluation of a modular multimodality imaging phantom to simulate heterogeneous uptake and enhancement patterns for radiomics quantification in hybrid imaging is presented. METHODS: A modular multimodality imaging phantom was constructed that could simulate different patterns of heterogeneous uptake and enhancement patterns in positron emission tomography (PET), single-photon emission computed tomography (SPECT), computed tomography (CT), and magnetic resonance (MR) imaging. The phantom was designed to be used as an insert in the standard NEMA-NU2 IEC body phantom casing. The entire phantom insert is composed of three segments, each containing three separately fillable compartments. The fillable compartments between segments had different sizes in order to simulate heterogeneous patterns at different spatial scales. The compartments were separately filled with different ratios of 99m Tc-pertechnetate, 18 F-fluorodeoxyglucose ([18 F]FDG), iodine- and gadolinium-based contrast agents for SPECT, PET, CT, and T1 -weighted MR imaging respectively. Image acquisition was performed using standard oncological protocols on all modalities and repeated five times for repeatability assessment. A total of 93 radiomic features were calculated. Variability was assessed by determining the coefficient of quartile variation (CQV) of the features. Comparison of feature repeatability at different modalities and spatial scales was performed using Kruskal-Wallis-, Mann-Whitney U-, one-way ANOVA- and independent t-tests. RESULTS: Heterogeneous uptake and enhancement could be simulated on all four imaging modalities. Radiomic features in SPECT were significantly less stable than in all other modalities. Features in PET were significantly less stable than in MR and CT. A total of 20 features, particularly in the gray-level co-occurrence matrix (GLCM) and gray-level run-length matrix (GLRLM) class, were found to be relatively stable in all four modalities for all three spatial scales of heterogeneous patterns (with CQV < 10%). CONCLUSION: The phantom was suitable for simulating heterogeneous uptake and enhancement patterns in [18 F]FDG-PET, 99m Tc-SPECT, CT, and T1 -weighted MR images. The results of this work indicate that the phantom might be useful for the further development and optimization of imaging protocols for radiomic quantification in hybrid imaging modalities.

Electrical Properties Tomography: A Methodological Review.

Electrical properties tomography (EPT) is an imaging method that uses a magnetic resonance (MR) system to non-invasively determine the spatial distribution of the conductivity and permittivity of the imaged object. This manuscript starts by providing clear definitions about the data required for, and acquired in, EPT, followed by comprehensively formulating the physical equations underlying a large number of analytical EPT techniques. This thorough mathematical overview of EPT harmonizes several EPT techniques in a single type of formulation and gives insight into how they act on the data and what their data requirements are. Furthermore, the review describes machine learning-based algorithms. Matlab code of several differential and iterative integral methods is available upon request.

Optimal sequences and sequence parameters for GBCA-enhanced MRI of the glymphatic system: a systematic literature review.

BACKGROUND: The glymphatic system (GS) is a recently discovered waste clearance system in the brain. PURPOSE: To evaluate the most promising magnetic resonance imaging (MRI) sequence(s) and the most optimal sequence parameters for glymphatic MRI (gMRI) 4-24 h after administration of gadolinium-based contrast agent (GBCA). MATERIAL AND METHODS: Multiple literature databases were systematically searched for articles regarding gMRI or MRI of the perilymph in the inner ear until 11 May 2020. All relevant MRI sequence parameters were tabulated for qualitative analysis. Their potential was assessed based on detection of low dose GBCA, primarily measured as signal intensity (SI) ratio. RESULTS: Thirty articles were included in the analysis. Three-dimensional fluid attenuated inversion recovery (3D-FLAIR), 3D Real Inversion Recovery (3D-Real IR), and multiple 3D T1-weighted gradient echo sequences were used. In perilymph, 3D-FLAIR with a TE of at least 400 ms yielded the highest SIRs. In the qualitative analysis of inner ear studies using 3D-FLAIR, TR was in the range of 4400-10,000 ms, TI 1500-2600 ms, refocusing flip angle (rFA) (range 120°-180°), and echo train length (ETL) 23-173. In the gMRI studies, quantitative analysis was not possible. In the qualitative analysis, 3D-FLAIR was used in the majority (8/12) of the studies, usually with TR 4800-9000 ms, TI 1650-2500 ms, TE 311-561 ms, rFA 90°-120°, and ETL 167-278. CONCLUSION: Long TE 3D-FLAIR is the most promising sequence for detection of low-dose GBCA in the GS. Clinical and/or phantom studies on other MRI parameters are needed for further optimization of gMRI.

Accelerating implant RF safety assessment using a low-rank inverse update method.

PURPOSE: Patients who have medical metallic implants, e.g. orthopaedic implants and pacemakers, often cannot undergo an MRI exam. One of the largest risks is tissue heating due to the radio frequency (RF) fields. The RF safety assessment of implants is computationally demanding. This is due to the large dimensions of the transmit coil compared to the very detailed geometry of an implant. METHODS: In this work, we explore a faster computational method for the RF safety assessment of implants that exploits the small geometry. The method requires the RF field without an implant as a basis and calculates the perturbation that the implant induces. The inputs for this method are the incident fields and a library matrix that contains the RF field response of every edge an implant can occupy. Through a low-rank inverse update, using the Sherman-Woodbury-Morrison matrix identity, the EM response of arbitrary implants can be computed within seconds. We compare the solution from full-wave simulations with the results from the presented method, for two implant geometries. RESULTS: From the comparison, we found that the resulting electric and magnetic fields are numerically equivalent (maximum error of 1.35%). However, the computation was between 171 to 2478 times faster than the corresponding GPU accelerated full-wave simulation. CONCLUSIONS: The presented method enables for rapid and efficient evaluation of the RF fields near implants and might enable situation-specific scanning conditions.

A simulation study on the effect of optimized high permittivity materials on fetal imaging at 3T.

PURPOSE: One of the main concerns in fetal MRI is the radiofrequency power that is absorbed both by the mother and the fetus. Passive shimming using high permittivity materials in the form of "dielectric pads" has previously been shown to increase the B1+ efficiency and homogeneity in different applications, while reducing the specific absorption rate (SAR). In this work, we study the effect of optimized dielectric pads for 3 pregnant models. METHODS: Pregnant models in the 3rd, 7th, and 9th months of gestation were used for simulations in a birdcage coil at 3T. Dielectric pads were optimized regions of interest (ROI) using previously developed methods for B1+ efficiency and homogeneity and were designed for 2 ROIs: the entire fetus and the brain of the fetus. The SAR was evaluated in terms of the whole-body SAR, average SAR in the fetus and amniotic fluid, and maximum 10 g-averaged SAR in the mother, fetus, and amniotic fluid. RESULTS: The optimized dielectric pads increased the transmit efficiency up to 55% and increased the B1+ homogeneity in almost every tested configuration. The B1+ -normalized whole-body SAR was reduced by more than 31% for all body models. The B1+ -normalized local SAR was reduced in most scenarios by up to 62%. CONCLUSION: Simulations have shown that optimized high permittivity pads can reduce SAR in pregnant subjects at the 3rd, 7th, and 9th month of gestation, while improving the transmit field homogeneity in the fetus. However, significantly more work is required to demonstrate that fetal imaging is safe under standard operating conditions.

High-permittivity pad design tool for 7T neuroimaging and 3T body imaging.

PURPOSE: High-permittivity materials in the form of flexible "dielectric pads" have proved very useful for addressing RF inhomogeneities in high field MRI systems. Finding the optimal design of such pads is, however, a tedious task, reducing the impact of this technique. We present an easy-to-use software tool which allows researchers and clinicians to design dielectric pads efficiently on standard computer systems, for 7T neuroimaging and 3T body imaging applications. METHODS: The tool incorporates advanced computational methods based on field decomposition and model order reduction as a framework to efficiently evaluate the B1+ fields resulting from dielectric pads. The tool further incorporates optimization routines which can either optimize the position of a given dielectric pad, or perform a full parametric design. The optimization procedure can target either a single target field, or perform a sweep to explore the trade-off between homogeneity and efficiency of the B1+ field in a specific region of interest. The 3T version further allows for shifting of the imaging landmark to enable different imaging targets to be centered in the body coil. RESULTS: Example design results are shown for imaging the inner ear at 7T and for cardiac imaging at 3T. Computation times for all cases are approximately a minute per target field. CONCLUSION: The developed tool can be easily used to design dielectric pads for any 7T neuroimaging and 3T body imaging application within minutes. This bridges the gap between the advanced design methods and the practical application by the MR community.

Developments in Electrical-Property Tomography Based on the Contrast-Source Inversion Method.

The main objective of electrical-property tomography (EPT) is to retrieve dielectric tissue parameters from B ^ 1 + data as measured by a magnetic-resonance (MR) scanner. This is a so-called hybrid inverse problem in which data are defined inside the reconstruction domain of interest. In this paper, we discuss recent and new developments in EPT based on the contrast-source inversion (CSI) method. After a short review of the basics of this method, two- and three-dimensional implementations of CSI-EPT are presented along with a very efficient variant of 2D CSI-EPT called first-order induced current EPT (foIC-EPT). Practical implementation issues that arise when applying the method to measured data are addressed as well, and the limitations of a two-dimensional approach are extensively discussed. Tissue-parameter reconstructions of an anatomically correct male head model illustrate the performance of two- and three-dimensional CSI-EPT. We show that 2D implementation only produces reliable reconstructions under very special circumstances, while accurate reconstructions can be obtained with 3D CSI-EPT.

Studying neurons and glia non-invasively via anomalous subdiffusion of intracellular metabolites.

Cells in the central nervous system, neurons and glia, display a wide range of structural features. Molecular diffusion properties in the intracellular space of these cells reflect this structural diversity, deviating from standard Gaussian dynamics and resulting in anomalous subdiffusion. By tracking the displacement of intracellular metabolites, diffusion-weighted magnetic resonance spectroscopy allows for in vivo compartment-specific and cell-preferential morphological analysis of neurons and glia in the human brain. Suggestive of different intracellular environments between tissue type, the neuronal and glial intracellular space in gray matter is significantly more subdiffusive than in white matter. An important difference is found between the subdiffusion of choline, a predominantly glial metabolite, in gray and white matter, potentially reflecting differences in structural complexity between fibrous and protoplasmic astrocytes. The exclusively intracellular metabolite subdiffusive dynamics, taken together with water intra- and extracellular displacement, provide new insight of differing extracellular gray and white matter properties and exchange between tissue compartments.

3-D Contrast Source Inversion-Electrical Properties Tomography.

Contrast source inversion-electrical properties tomography (CSI-EPT) is an iterative reconstruction method to retrieve the electrical properties (EPs) of tissues from magnetic resonance data. The method is based on integral representations of the electromagnetic field and has been shown to allow EP reconstructions of small structures as well as tissue boundaries with compelling accuracy. However, to date, the CSI-EPT has been implemented for 2-D configurations only, which limits its applicability. In this paper, a full 3-D extension of the CSI-EPT method is presented, to enable CSI-EPT to be applied to realistic 3-D scenarios. Here, we demonstrate a proof-of-principle of 3-D CSI-EPT and present the reconstructions of a 3-D abdominal body section and a 3-D head model using different settings of the transmit coil. Numerical results show that the full 3-D approach yields accurate reconstructions of the EPs, even at tissue boundaries and is most accurate in regions where the absolute value of the electric field is highest.

A simple head-sized phantom for realistic static and radiofrequency characterization at high fields.

PURPOSE: To demonstrate a simple head-sized phantom for realistic static and RF field characterization in high field systems. METHODS: The head-sized phantom was composed of an ellipsoidal compartment and a spherical cavity to mimic the nasal cavity. The phantom was filled with an aqueous solution of polyvinylpyrrolidone (PVP), to mimic the average dielectric properties of brain tissue. The static and RF field distributions were characterized on a 7T MRI system and compared to in vivo measurements and simulations. MR thermometry was performed, and the results were compared to thermal simulations for RF validation purposes. RESULTS: Accurate reproduction of both static and RF fields patterns observed in vivo was confirmed experimentally and was shown to be strongly affected by the inclusion of the spherical cavity. MR thermometry and transmit efficiency ( B1+) measurements were obtained in close agreement with simulations (peak values agreeing within 0.3 °C and 0.02 µT/√W) as well as fiber optic thermal probes (RMSE < 0.18 °C). CONCLUSIONS: A simple head-sized phantom has been presented that produces B0 and B1+ nonuniformities similar to those encountered in the human head and allows for accurate MR thermometry measurements, making this a suitable reference phantom for RF validation and methodological development in high field MRI.