Specific Absorption Rate Estimation Research Articles

Modeling of the interaction between human body and electromagnetic waves near resonance using machine learning

Human-Like digital models have been around for quite some time. They significantly contributed to the increase of the accuracy of the whole-body-average specific absorption rate estimations. However, the anatomical and morphological diversity between human beings has not yet been embraced by the actual anthropomorphic models for several reasons such as financial costs, excessive exposure of volunteers to electromagnetic waves, and the required number of technical experts needed to build one voxelized model. Recently, machine learning has been used to reduce the complexity of certain tasks. Yet, at least, having an anthropomorphic model per nation is still far away to achieve. To reduce the building cost of new human-like models, we build on the success of anthropomorphic models and machine learning to derive mathematical equations that make it possible to predict the Whole-body-average SAR from low frequencies up to twice the resonance frequency without any cost and excessive electromagnetic exposure of new volunteers. The completely new machine learning based equations are applicable for any age, ethnic group, and for both genders. They depend only on the human body’s morphological (height and weight) and anatomical parameters (tissue weights). In this work, we first address the whole-body-average SAR peak and we present a set of two estimators. In second, we show that the resonance frequency is not only a function of the height of the human body, to end up with a third estimation for the resonance frequency. These completely new estimators are finally combined into a novel equation that links the whole-body-average SAR to the frequency. It shows the accurate prediction for low frequencies (10 MHz) up to twice the resonance frequency. The derived estimators for the maximum WBASAR and the resonance frequencies showed better results for low frequency exposure.

Simultaneous estimation of SAR, thermal diffusivity, and damping using periodic power modulation for MRgFUS quality assurance

Purpose: A crucial aspect of quality assurance in thermal therapy is periodic demonstration of the heating performance of the device. Existing methods estimate the specific absorption rate (SAR) from the temperature rise after a short power pulse, which yields a biased estimate as thermal diffusion broadens the apparent SAR pattern. To obtain an unbiased estimate, we propose a robust frequency-domain method that simultaneously identifies the SAR as well as the thermal dynamics. Methods: We propose a method consisting of periodic modulation of the FUS power while recording the response with MR thermometry (MRT). This approach enables unbiased measurements of spatial Fourier coefficients that encode the thermal response. These coefficients are substituted in a generic thermal model to simultaneously estimate the SAR, diffusivity, and damping. The method was tested using a cylindrical phantom and a 3 T clinical MR-HIFU system. Three scenarios with varying modulation strategies are chosen to challenge the method. The results are compared to the well-known power pulse technique. Results: The thermal diffusivity is estimated at 0.151 mm2s–1 with a standard deviation of 0.01 mm2s–1 between six experiments. The SAR estimates are consistent between all experiments and show an excellent signal-to-noise ratio (SNR) compared to the well established power pulse method. The frequency-domain method proved to be insensitive to B 0-drift and non steady-state initial temperature distributions. Conclusion: The proposed frequency-domain estimation method shows a high SNR and provided reproducible estimates of the SAR and the corresponding thermal diffusivity. The findings suggest that frequency-domain tools can be highly effective at estimating the SAR from (biased) MRT data acquired during periodic power modulation.

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

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

The effects of RF coils and SAR supervision strategies forclinically applicable nonselective parallel-transmit pulses at 7T.

To investigate the effects of using different parallel-transmit (pTx) head coils and specific absorption rate (SAR) supervision strategies on pTx pulse design for ultrahigh-field MRI using a 3D-MPRAGE sequence. The PTx universal pulses (UPs) and fast online-customized (FOCUS) pulses were designed with pre-acquired data sets (B0 , B1 + maps, specific absorption rate [SAR] supervision data) from two different 8 transmit/32 receive head coils on two 7T whole-body MR systems. For one coil, the SAR supervision model consisted of per-channel RF power limits. In the other coil, SAR estimations were done with both per-channel RF power limits as well as virtual observation points (VOPs) derived from electromagnetic field (EMF) simulations using three virtual human body models at three different positions. All pulses were made for nonselective excitation and inversion and evaluated on 132 B0 , B1 + , and SAR supervision datasets obtained with one coil and 12 from the other. At both sites, 3 subjects were examined using MPRAGE sequences that used UP/FOCUS pulses generated for both coils. For some subjects, the UPs underperformed when simulated on a different coil from which they were derived, whereas FOCUS pulses still showed acceptable performance in that case. FOCUS inversion pulses outperformed adiabatic pulses when scaled to the same local SAR level. For the self-built coil, the use of VOPs showed reliable overestimation compared with the ground-truth EMF simulations, predicting about 52% lower local SAR for inversion pulses compared with per-channel power limits. FOCUS inversion pulses offer a low-SAR alternative to adiabatic pulses and benefit from using EMF-based VOPs for SAR estimation.

Numerical Estimation of SAR and Temperature Distributions inside Differently Shaped Female Breast Tumors during Radio-Frequency Ablation.

Radio-frequency (RF) ablation is a reliable technique for the treatment of deep-seated malignant tumors, including breast carcinoma, using high ablative temperatures. The paper aims at a comparative analysis of the specific absorption rate and temperature distribution during RF ablation with regard to different female breast tumors. In the study, four tumor models equivalent to an irregular tumor were considered, i.e., an equivalent sphere and ellipsoid with the same surfaces and volumes as the irregular tumor and an equivalent sphere and ellipsoid inscribed in the irregular tumor. An RF applicator with a specific voltage, operating at 100 kHz inserted into the anatomically correct female breast, was applied as a source of electromagnetically induced heat. A conjugated Laplace equation with the modified Pennes equation was used to obtain the appropriate temperature gradient in the treated area. The levels of power dissipation in terms of the specific absorption rate (SAR) inside the naturalistically shaped tumor, together with the temperature profiles of the four simplified tumor models equivalent to the irregular one, were determined. It was suggested that the equivalent tumor models might successfully replace a real, irregularly shaped tumor, and the presented numeric methodology may play an important role in the complex therapeutic RF ablation process of irregularly shaped female breast tumors.

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

PurposeParallel 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.MethodsMulti‐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.ResultsThe 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.ConclusionA 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.

Safety for Human MR Scanners at 7T

After introduction of the first human 7 tesla (7T) system in 1999, 7T MR systems have been employed as one of the most advanced platforms for human MR research for more than 20 years. Currently, two 7T MR models are approved for clinical use in the U.S.A. The approval facilitated introduction of the 7T system, summing up to around 100 worldwide. The approval in Japan is much awaited. As a clinical MR scanner, the 7T MR system is drawing attention in terms of safety.Several large-sized studies on bioeffects have been reported for vertigo, dizziness, motion disturbances, nausea, and others. Such effects might also be found in MR workers and researchers. Frequency and severity of reported bioeffects will be presented and discussed, including their variances. The high resonance frequency and shorter RF wavelength of 7T increase the concern about the safety. Homogeneous RF pulse excitation is difficult even for the brain, and a multi-channel parallel transmit (pTx) system is considered mandatory. However, pTx may create a hot spot, which makes the estimation of specific absorption rate (SAR) to be difficult. The stronger magnetic field of 7T causes a large force of displacement and heating on metallic implants or devices, and the scan of patients with them should not be conducted at 7T. However, there are some opinions that such patients might be scanned even at 7T, if certain criteria are met. This article provides a brief review on the effect of the static magnetic field on humans (MR subjects, workers, and researchers) and neurons, in addition to scan sound, SAR, and metal implants and devices. Understanding and avoiding adverse effects will contribute to the reduction in safety risks and the prevention of incidents.

A Nested Eight-Channel Transmit Array With Open-Face Concept for Human Brain Imaging at 7 Tesla

Purpose: Parallel transmit technology for MRI at 7 tesla will significantly benefit from high performance transmit arrays that offer high transmit efficiency and low mutual coupling between the individual array elements. A novel dual-mode transmit array with nested array elements has been developed to support imaging the human brain in both the single-channel (sTx) and parallel-transmit (pTx) excitation modes of a 7 tesla MRI scanner. In this work, the design, implementation, validation, specific absorption rate (SAR) management, and performance of the head coil is presented.Methods: The transmit array consisted of a nested arrangement to improve decoupling between the second-neighboring elements. Two large cut-outs were introduced in the RF shield for an open-face design to reduce claustrophobia and to allow patient monitoring. A hardware interface allows the coil to be used in both the sTx and pTx modes. SAR monitoring is done with virtual observation points (VOP) derived from human body models. The transmit efficiency and coverage is compared with the commercial single-channel and parallel-transmit head coils.Results: Decoupling inductors between the second-neighboring coil elements reduced the coupling to less than −20 dB. Local SAR estimates from the electromagnetic (EM) simulations were always less than the EM-based VOPs, which in turn were always less than scanner predictions and measurements for static and dynamic pTx waveforms. In sTx mode, we demonstrate improved coverage of the brain compared to the commercial sTx coil. The transmit efficiency is within 10% of the commercial pTx coil despite the two large cut-outs in the RF shield. In pTx mode, improved signal homogeneity was shown when the Universal Pulse was used for acquisition in vivo.Conclusion: A novel head coil which includes a nested eight-channel transmit array has been presented. The large cut-outs improve patient monitoring and reduce claustrophobia. For pTx mode, the EM simulation and VOP-based SAR management provided greater flexibility to apply pTx methods without the limitations of SAR constraints. For scanning in vivo, the coil was shown to provide an improved coverage in sTx mode compared to a standard commercial head coil.

Temperature-based MRI safety simulations with a limited number of tissues.

Demonstrate ability to produce reasonable simulations of temperature using numerical models of the human body with a limited number of tissues. For both a male and female human body model, numerical simulations were used to calculate temperature distributions in three different models of the same human body: the original model with 35 tissues for the male model and 76 tissues for the female model, a simplified model having only three tissues (muscle, fat, and lung), and a simplified model having six tissues (muscle, fat, lung, bone, brain, and skin). Although a three-tissue model gave reasonable specific absorption rate estimates in comparison to an original with many more tissues, because of tissue-specific thermal and physiological properties that do not affect specific absorption rate, such as rate of perfusion by blood, the three-tissue model did not provide temperature distributions similar to those of the original model. Inclusion of a few additional tissues, as in the six-tissue model, produced results in much better agreement with those from the original model. Reasonable estimates of temperature can be simulated with a limited number of tissues, although this number is higher than the number of tissues required to produce reasonable simulations of specific absorption rate. For exposures primarily in the head and thorax, six tissues may be adequate for reasonable estimates of temperature.

The impact of data selection and fitting on SAR estimation for magnetic nanoparticle heating

Background Magnetic fluid heating has great potential in the fields of thermal medicine and cryopreservation. However, variations among experimental parameters, analysis methods and experimental uncertainty make quantitative comparisons of results among laboratories difficult. Herein, we focus on the impact of calculating the specific absorption rate (SAR) using Time-Rise and Box-Lucas fitting. Time-Rise assumes adiabatic conditions, which is experimentally unachievable, but can be reasonably assumed (quasi-adiabatic) only for specific and limited evaluation times when heat loss is negligible compared to measured heating rate. Box-Lucas, on the other hand, accounts for heat losses but requires longer heating. Methods Through retrospective analysis of data obtained from two laboratories, we demonstrate measurement time is a critical parameter to consider when calculating SAR. Volumetric SAR were calculated using the two methods and compared across multiple iron-oxide nanoparticles. Results We observed the lowest volumetric SAR variation from both fitting methods between 1–10 W/mL, indicating an ideal SAR range for heating measurements. Furthermore, our analysis demonstrates that poorly chosen fitting method can generate reproducible but inaccurate SAR. Conclusion We provide recommendations to select measurement time for data analysis with either Modified Time-Rise or Box-Lucas method, and suggestions to enhance experimental precision and accuracy when conducting heating experiments.

EVALUATION OF SPECIFIC ABSORPTION RATE IN THE FAR-FIELD, NEAR-TO-FAR FIELD AND NEAR-FIELD REGIONS FOR INTEGRATIVE RADIOFREQUENCY EXPOSURE ASSESSMENT.

The specific absorption rate (SAR) induced by wireless radiofrequency (RF) systems depends on different parameters. Previously, SAR was mainly assessed under conditions of a single frequency and technology and for a limited number of localized RF sources. The current and emerging mobile systems involve a wider range of usage scenarios and are frequently used simultaneously, leading to combined exposures for which almost no exposure evaluation exists. The aim and novelty of this study is to close this gap of knowledge by developing new methods to rapidly evaluate the SAR induced by RF systems in such scenarios at frequencies from 50MHz to 5.5GHz. To this aim, analytical methods for SAR estimation in several usage scenarios were derived through a large-scale numerical study. These include subject-specific characteristics, properties of the RF systems and provide an estimation of the SAR in the whole body, tissues and organs, and different brain regions.

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

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

Global and peak local specific absorption rate control on parallel transmit systems using k-means SAR compression model.

To improve the specific absorption rate (SAR) compression model capability in parallel transmission (pTx) MRI systems. A k-means clustering method is proposed to group voxels with similar SAR behaviors in the scanned object, providing a controlled upper-bounded estimation of peak local SARs. This k-means compression model and the conventional virtual observation point (VOP) model were tested in a pTx MRI framework. The pTx pulse design with different SAR controlling schemes was simulated using a numerical human head model and an eight-channel 7T coil array. Multiple criteria (including RF power, global and peak local SARs, and excitation accuracy) were compared for the performance testing. The k-means compression model generated a narrower overestimation bound, leading to a more accurate local SAR estimation. Among different pTx pulse design approaches, the k-means compression model showed the best trade-off between the SAR and excitation accuracy. The developed SAR compression model is advantageous for pTx framework given the narrower overestimation bound and control over the compression ratio. Results also illustrate that a moderate increase of maximum RF power can be useful for reducing the maximum local SAR deposition.

Individualized SAR calculations using computer vision-based MR segmentation and a fast electromagnetic solver.

We propose a fast, patient-specific workflow for on-line specific absorption rate (SAR) supervision. An individualized electromagnetic model is created while the subject is on the table, followed by rapid SAR estimates for that individual. Our goal is an improved correspondence between the patient and model, reducing reliance on general anatomical body models. A 3D fat-water 3T acquisition (~2minutes) is automatically segmented using a computer vision algorithm (~1minute) into what we found to be the most important electromagnetic tissue classes: air, bone, fat, and soft tissues. We then compute the individual's EM field exposure and global and local SAR matrices using a fast electromagnetic integral equation solver. We assess the approach in 10 volunteers and compare to the SAR seen in a standard generic body model (Duke). The on-the-table workflow averaged 7'44″. Simulation of the simplified Duke models confirmed that only air, bone, fat, and soft tissue classes are needed to estimate global and local SAR with an error of 6.7% and 2.7%, respectively, compared to the full model. In contrast, our volunteers showed a 16.0% and 20.3% population variability in global and local SAR, respectively, which was mostly underestimated by the Duke model. Timely construction and deployment of a patient-specific model is computationally feasible. The benefit of resolving the population heterogeneity compared favorably to the modest modeling error incurred. This suggests that individualized SAR estimates can improve electromagnetic safety in MRI and possibly reduce conservative safety margins that account for patient-model mismatch, especially in non-standard patients.

A deep learning method for image-based subject-specific local SAR assessment.

PurposeLocal specific absorption rate (SAR) cannot be measured and is usually evaluated by offline numerical simulations using generic body models that of course will differ from the patient's anatomy. An additional safety margin is needed to include this intersubject variability. In this work, we present a deep learning–based method for image‐based subject‐specific local SAR assessment. We propose to train a convolutional neural network to learn a “surrogate SAR model” to map the relation between subject‐specific B1+ maps and the corresponding local SAR.MethodOur database of 23 subject‐specific models with an 8–transmit channel body array for prostate imaging at 7 T was used to build 5750 training samples. These synthetic complex B1+ maps and local SAR distributions were used to train a conditional generative adversarial network. Extra penalization for local SAR underestimation errors was included in the loss function. In silico and in vivo validation were performed.ResultsIn silico cross‐validation shows a good qualitative and quantitative match between predicted and ground‐truth local SAR distributions. The peak local SAR estimation error distribution shows a mean overestimation error of 15% with 13% probability of underestimation. The higher accuracy of the proposed method allows the use of less conservative safety factors compared with standard procedures. In vivo validation shows that the method is applicable with realistic measurement data with impressively good qualitative and quantitative agreement to simulations.ConclusionThe proposed deep learning method allows online image‐based subject‐specific local SAR assessment. It greatly reduces the uncertainty in current state‐of‐the‐art SAR assessment methods, reducing the time in the examination protocol by almost 25%.

The impact of human age on the amount of absorbed energy from mobile phone

PurposeThe purpose of this paper is to determine the impact of human age on the distribution of electric field and absorbed energy that originates from a mobile phone.Design/methodology/approachThis research was performed for frequencies of 900, 1800 and 2100 MHz, which are used in a mobile communication system. To obtain the most accurate results, 3 D realistic model of the child’s head has been created whereby the dimensions of this model correspond to the dimensions of a seven-year-old child. Distribution of the electric field and specific absorption rate (SAR) through the child’s head was obtained by numerical analysis based on the finite integration technique.FindingsThe results discover that amount of absorbed energy is greater in the surface layers of the child’s head model when the electromagnetic (EM) characteristics of tissues are adjusted for the child. This deviation corresponds to different EM characteristics of biological tissues and organs of an adult person compared to a child.Research limitations/implicationsThe study deals with penetrated electrical field and absorbed EM field energy. There is space for further studies of other EM field effects (e.g. thermal effects).Practical implicationsThe analysis of obtained results leads to idea that mobile phones and devices aimed for children using should be modified to provide SAR values inside prescribed standards.Social implicationsThe obtained results are foundation for future research on influence of EM fields of mobile devices on human health.Originality/valueThe proposed procedure offers the model for accurate estimation and quality analysis of SAR and EM field distribution inside child head tissue.

Investigation of Nanomaterial Dipoles for SAR Reduction in Human Head

Abstract The Nanomaterial is a pioneer in the field of modern research for its unique properties. Human exposure analysis is inevitable due to the rapid growth in technology. The concern for human welfare indicates a need for reduction of human exposure towards the radiation caused by the devices. The dielectric properties of the nanomaterials can be ideal for exploration in the field of biomedical engineering. Specific absorption rate (SAR) is a vital parameter for exposure analysis. This paper investigates the impact of Nanomaterials on the human exposure analysis. For this purpose, a dipole radiating structure operating at GSM frequency of 900 MHz and 1800 MHz are designed with conventional Copper material and compared with Carbon nanomaterials such as Graphene, Single-walled carbon nanotube (SWCNT) and Multi-walled carbon nanotube (MWCNT) for performance evaluation. Further, the specific absorption rate estimates absorption of radiation in IEEE Sam phantom human head with equivalent tissue properties. The comparison of calculated SAR with the radiating structures that are designed with the equivalent properties of that of Nanomaterials. The evaluation of Nanomaterial Antennas at the center frequency is estimated, and performance is evaluated. The designed Nanomaterials interact with IEEE SAM Phantom and SAR is calculated. The analysis of SAR impact with nanomaterials is investigated in this work.

Whole-body average SAR measurement using flat phantoms for radio base station antennas and its applicability to adult and child human models

The specific absorption rate (SAR) measurement procedure for radio base station antennas using flat phantoms has been investigated and standardized by the International Electrotechnical Commission (IEC). This paper discusses the effectiveness of this procedure for considering Japanese human models based on numerical simulations with validation of whole-body average SAR (WBSAR) measurement. The WBSAR in two Japanese anatomical human models (adult male and 3-year-old child) and two box-shaped phantoms (large and small) using a standardized SAR measurement procedure are compared at 788 MHz and 3.5 GHz. Computational results show that the SAR measurement procedure in the IEC leads to overestimated WBSAR compared to those in Japanese anatomical human models. These results imply that the SAR measurement procedure above is applicable to not only some commonly used but Japanese human models. The WBSAR obtained using SAR estimation formulae in the IEC is also overestimated compared to those in Japanese anatomical human models. In addition, to reduce the measurement time and simplify the post-processing, this paper introduces a SAR measurement procedure based on the two-dimensional SAR distribution around the surface of the bottom of the phantom and the one-dimensional exponential decay of the SAR distribution in the direction of the phantom depth. SAR measurement examples of antennas for small radio base stations are also presented.

Computer-Vision Techniques for Water-Fat Separation in Ultra High-Field MRI Local Specific Absorption Rate Estimation.

The purpose of this paper is to prove that computer-vision techniques allow synthesizing water-fat separation maps for local specific absorption rate (SAR) estimation, when patient-specific water-fat images are not available. We obtained ground truth head models by using patient-specific water-fat images. We obtained two different label-fusion water-fat models generating a water-fat multiatlas and applying the STAPLE and local-MAP-STAPLE label-fusion methods. We also obtained patch-based water-fat models applying a local group-wise weighted combination of the multiatlas. Electromagnetic (EM) simulations were performed, and B1+ magnitude and 10 g averaged SAR maps were generated. We found local approaches provide a high DICE overlap (72.6±10.2% fat and 91.6±1.5% water in local-MAP-STAPLE, and 68.8±8.2% fat and 91.1±1.0% water in patch-based), low Hausdorff distances (18.6±7.7mm fat and 7.4±11.2mm water in local-MAP-STAPLE, and 16.4±8.5mm fat and 7.2±11.8mm water in patch-based) and a low error in volume estimation (15.6±34.4% fat and 5.6±4.1% water in the local-MAP-STAPLE, and 14.0±17.7% fat and 4.7±2.8% water in patch-based). The positions of the peak 10 g-averaged local SAR hotspots were the same for every model. We have created patient-specific head models using three different computer-vision-based water-fat separation approaches and compared the predictions of B1+ field and SAR distributions generated by simulating these models. Our results prove that a computer-vision approach can be used for patient-specific water-fat separation, and utilized for local SAR estimation in high-field MRI. Computer-vision approaches can be used for patient-specific water-fat separation and for patient specific local SAR estimation, when water-fat images of the patient are not available.

Miniaturized quad-band coplanar-fed monopole antenna for tablet computers

PurposeThis paper aims to present the design of a compact quad-band coplanar-fed monopole antenna for tablet computer applications.Design/methodology/approachThe antenna has the smallest size of 26 × 14 mm and supports GSM, Wi-Fi, WIMAX and Bluetooth. The proposed antenna consists of a coplanar fed main radiator, c-shaped stubs and parasitic meandered stub. The inverted c-shaped stubs enhance the bandwidth of upper frequencies. The resonance at 2.4 GHz is individually controlled by the coupled meandered stub.FindingsThe percentage bandwidth in the four operating bands are 8.7/4.12/27.8/13.3%. Furthermore, the antenna is integrated with the mock-up ground plane and specific absorption rate (SAR) calculations are performed. The estimated SAR is less than 1.6 W/kg for a 1 g body tissue. The gain and efficiency of the antenna are 3.56/4.37/4.97/6 dBi and 82.4/85/97.1/89.3%, respectively. The measured impedance and radiation characteristics of the fabricated prototype are in good correlation with the simulated results.Originality/valueIn the proposed work, vias and lumped elements are not used for lower band excitation, and most of the wireless applications in the tablet computers have been covered. Further, the effect of antenna with different orientation has been tested for the estimation of SAR.