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(1) Background: The 2023 approval of lecanemab for early-stage Alzheimer's disease (AD) highlighted the need for routine 1.5T or 3.0T MRI scans to monitor amyloid-related imaging abnormalities (ARIAs). Regional disparities in MRI scan frequency, MRI scanner availability, and scanner magnetic field strengths could affect readiness for anti-amyloid therapy and lead to inconsistencies in ARIA detection nationwide. (2) Methods: We assessed regional variance in MRI scan frequency and field strength across Japan using the National Database (NDB) Open Data website, which summarizes Japanese public health insurance claims from the fiscal years (FYs) 2015 to 2021. We employed a mixed-effects model with prefecture-level random intercepts and slopes over time, subsequently categorizing prefectures into clusters based on MRI usage. (3) Results: 1.5T MRI was the most common magnetic field strength, remaining stable from FY2015 to FY2021. 3.0T MRI usage slightly increased, although the COVID-19 pandemic in FY2020 led to a maximum reduction of 5%. Prefecture-level variance was higher for 3.0T MRIs, with more frequent usage in western Japan. (4) Conclusions: This study highlights prefecture-level variance in MRI usage across Japan. The insights gained could be instrumental in improving healthcare preparedness for anti-amyloid treatment and patient management.

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A significant number of steep cracks are frequently encountered in underground engineering, posing a threat to operation. The high-pressure grouting method is a commonly utilized repair technique. Nevertheless, conventional grout is prone to displacement due to its weight, making it challenging to ensure adequate filling of the cracks. Therefore, this study aims to develop a grouting material with targeted displacement and anchoring properties. Firstly, an optimal magnetic slurry composition was determined through an orthogonal test. Subsequently, XRD and SEM were used to analyze the impact of the magnetic field on the composition distribution, internal pore structure, and transient viscosity of the slurry. Afterwards, a model for localized grout diffusion under magnetic was established. The results show that the application of a magnetic field caused the slurry to compact due to magnetic forces, reducing its porosity. Moreover, the dynamic viscosity of the slurry increased exponentially with rising magnetic induction intensity. Notably, a 40.5% increase in the diffusion area was observed when the magnetic field intensity rose from 2500 to 4500 GS. The error between the measured and theoretical values of the magnetic slurry diffusion model was only 8.91%, indicating the model's accuracy in describing the slurry diffusion process under magnetic field influence.

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BACKGROUND: Cardiovascular magnetic resonance (CMR) imaging is an important tool for evaluating the severity of aortic stenosis (AS), co-existing aortic disease, and concurrent myocardial abnormalities. Acquiring this additional information requires protocol adaptations and additional scanner time, but is not necessary for the majority of patients who do not have AS. We observed that the relative signal intensity of blood in the ascending aorta on a balanced steady state free precession (bSSFP) 3-chamber cine was often reduced in those with significant aortic stenosis. We investigated whether this effect could be quantified and used to predict AS severity in comparison to existing gold-standard measurements. METHODS: Multi-centre, multi-vendor retrospective analysis of patients with AS undergoing CMR and transthoracic echocardiography (TTE). Blood signal intensity was measured in a ∼1 cm2 region of interest (ROI) in the aorta and left ventricle (LV) in the 3-chamber bSSFP cine. Because signal intensity varied across patients and scanner vendors, a ratio of the mean signal intensity in the aorta ROI to the LV ROI (Ao:LV) was used. This ratio was compared using Pearson correlations against TTE parameters of AS severity: aortic valve peak velocity, mean pressure gradient and the dimensionless index. The study also assessed whether field strength (1.5 T vs. 3 T) and patient characteristics (presence of bicuspid aortic valves (BAV), dilated aortic root and low flow states) altered this signal relationship. RESULTS: 314 patients (median age 69 [IQR 57-77], 64% male) who had undergone both CMR and TTE were studied; 84 had severe AS, 78 had moderate AS, 66 had mild AS and 86 without AS were studied as a comparator group. The median time between CMR and TTE was 12 weeks (IQR 4-26). The Ao:LV ratio at 1.5 T strongly correlated with peak velocity (r = -0.796, p = 0.001), peak gradient (r = -0.772, p = 0.001) and dimensionless index (r = 0.743, p = 0.001). An Ao:LV ratio of < 0.86 was 84% sensitive and 82% specific for detecting AS of any severity and a ratio of 0.58 was 83% sensitive and 92% specific for severe AS. The ability of Ao:LV ratio to predict AS severity remained for patients with bicuspid aortic valves, dilated aortic root or low indexed stroke volume. The relationship between Ao:LV ratio and AS severity was weaker at 3 T. CONCLUSIONS: The Ao:LV ratio, derived from bSSFP 3-chamber cine images, shows a good correlation with existing measures of AS severity. It demonstrates utility at 1.5 T and offers an easily calculable metric that can be used at the time of scanning or automated to identify on an adaptive basis which patients benefit from dedicated imaging to assess which patients should have additional sequences to assess AS.

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PURPOSE: Hemodynamics is important in the initiation, growth, and rupture of intracranial aneurysms. Since intracranial aneurysms are small, a high-field MR system with high spatial resolution and high SNR is desirable for this hemodynamic analysis. The purpose of this study was to investigate whether the accuracy of MR fluid dynamic (MRFD) results based on 3D phase-contrast MR (3D PC MR, non-electrocardiogram[ECG]-gated 4D Flow MRI) data from a human cerebrovascular phantom and human healthy subjects obtained by a 7T MR system was superior to those by a 3T MR system. METHODS: 3D PC MR and 3D time of flight MR angiography (3D TOF MRA) imaging were performed on a 3T MR system and a 7T MR system for a human cerebrovascular phantom and 10 healthy human subjects, and MRFD analysis was performed using these data. The MRFD results from each MR system were then compared with the following items based on the computational fluid dynamics (CFD) results: 3D velocity vector field; correlation coefficient (R), angular similarity index (ASI), and magnitude similarity index (MSI) of blood flow velocity vectors. RESULTS: In the MRFD results of 3D velocity vectors of the cerebrovascular phantom, noise-like vectors were observed near the vascular wall on the 3T MR system, but no noise was observed on the 7T MR system, showing results similar to those of CFD. In the MRFD results of the cerebrovascular phantom and healthy subjects, the correlation coefficients R, ASI, and MSI of the 7T MR system were higher than those of the 3T MR system, and ASI and MSI of healthy human subjects were significantly different between the two systems. CONCLUSIONS: The accuracy of high spatial resolution MRFD using the 7T MR system exceeded that of the 3T MR system.

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The purpose of this chapter is the mathematical study of the perturbation of a homogeneous static magnetic field caused by the embedding of a red blood cell. Analytical expressions for the magnetic potential and the magnetic strength vector are derived. From the obtained results, it emerges that the magnetic field inside the red blood cell is not uniform and the magnitude depends on the orientation of the erythrocyte. The expressions for the magnetic field quantities are significant in applications such as the magnetic resonance imaging and in the magnetic resonance spectroscopy.

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OBJECTIVE: This study presents an extended evaluation of a numerical approach to simulate artifacts of metallic implants in an MR environment. METHODS: The numerical approach is validated by comparing the artifact shape of the simulations and measurements of two metallic orthopedic implants at three different field strengths (1.5 T, 3 T, and 7 T). Furthermore, this study presents three additional use cases of the numerical simulation. The first one shows how numerical simulations can improve the artifact size evaluation according to ASTM F2119. The second use case quantifies the influence of different imaging parameters (TE and bandwidth) on the artifact size. Finally, the third use case shows the potential of performing human model artifact simulations. RESULTS: The numerical simulation approach shows a dice similarity coefficient of 0.74 between simulated and measured artifact sizes of metallic implants. The alternative artifact size calculation method presented in this study shows that the artifact size of the ASTM-based method is up to 50% smaller for complex shaped implants compared to the numerical-based approach. CONCLUSION: In conclusion, the numerical approach could be used in the future to extend MR safety testing according to a revision of the ASTM F2119 standard and for design optimization during the development process of implants.

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The paper considers non-destructive testing (NTDs) as a means to solve the flaw detection problems of magnetic products. It proposes a new probe-coil magnetic-field NDT, not requiring the pre-magnetization of the test object material, which is mandatory for all conventional magnetic flaw detection techniques. A new bifactor excitation of the fluxgate sensor's sensitive element, based on double µ-transformation through the simultaneous activation of magnetic-modulating and electromagnetic-acoustic effects, is theoretically justified. The physical processes underlying the proposed technique are considered in detail, and a scheme for its practical implementation is described. The authors provide a variant of the new fluxgate's original design, implementing the proposed excitation technique. The specifics of implementing the fluxgate operating modes are analyzed, testifying to the possibility of detecting a given class of flaws with the required coverage as well as ensuring the required diagnostic resolution during flaw detection, which, in fact, indicates a more reliable identification of both the flaw type and location. Herewith, the new fluxgate type features the advantages of improved functionality and lower cost due to its simple design. The paper also considers a method to experimentally study the capabilities of the proposed fluxgate sensor with a new bifactor excitation in detail. The results of the experimental study into its key specifications are provided, confirming its high resolution, narrower zone of uncertainty, and the possibility of detecting smaller flaws at greater depths compared to available analogs.

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There are many ways to acquire and process diffusion MRI (dMRI) data for group studies, but it is unknown which maximizes the sensitivity to white matter (WM) pathology. Inspired by this question, we analyzed data acquired for diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) at 3T (3T-DTI and 3T-DKI) and DTI at 7T in patients with systemic lupus erythematosus (SLE) and healthy controls (HC). Parameter estimates in 72 WM tracts were obtained using TractSeg. The impact on the sensitivity to WM pathology was evaluated for the diffusion protocol, the magnetic field strength, and the processing pipeline. Sensitivity was quantified in terms of Cohen's d for group comparison. Results showed that the choice of diffusion protocol had the largest impact on the effect size. The effect size in fractional anisotropy (FA) across all WM tracts was 0.26 higher when derived by DTI than by DKI and 0.20 higher in 3T compared with 7T. The difference due to the diffusion protocol was larger than the difference due to magnetic field strength for the majority of diffusion parameters. In contrast, the difference between including or excluding different processing steps was near negligible, except for the correction of distortions from eddy currents and motion which had a clearly positive impact. For example, effect sizes increased on average by 0.07 by including motion and eddy correction for FA derived from 3T-DTI. Effect sizes were slightly reduced by the incorporation of denoising and Gibbs-ringing removal (on average by 0.011 and 0.005, respectively). Smoothing prior to diffusion model fitting generally reduced effect sizes. In summary, 3T-DTI in combination with eddy current and motion correction yielded the highest sensitivity to WM pathology in patients with SLE. However, our results also indicated that the 3T-DKI and 7T-DTI protocols used here may be adjusted to increase effect sizes.

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Dynamic susceptibility contrast (DSC) MRI is clinically used to measure brain perfusion by monitoring the dynamic passage of a bolus of contrast agent through the brain. For quantitative analysis of the DSC images, the arterial input function is required. It is known that the original assumption of a linear relation between the R2(*) relaxation and the arterial contrast agent concentration is invalid, although the exact relation is as of yet unknown. Studying this relation in vitro is time-consuming, because of the widespread variations in field strengths, MRI sequences, contrast agents, and physiological conditions. This study aims to simulate the R2(*) versus contrast concentration relation under varying physiological and technical conditions using an adapted version of an open-source simulation tool. The approach was validated with previously acquired data in human whole blood at 1.5 T by means of a gradient-echo sequence (proof-of-concept). Subsequently, the impact of hematocrit, field strength, and oxygen saturation on this relation was studied for both gradient-echo and spin-echo sequences. The results show that for both gradient-echo and spin-echo sequences, the relaxivity increases with hematocrit and field strength, while the hematocrit dependency was nonlinear for both types of MRI sequences. By contrast, oxygen saturation has only a minor effect. In conclusion, the simulation setup has proven to be an efficient method to rapidly calibrate and estimate the relation between R2(*) and gadolinium concentration in whole blood. This knowledge will be useful in future clinical work to more accurately retrieve quantitative information on brain perfusion.

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OBJECTIVE: This study presents the development and evaluation of a numerical approach to simulate artifacts of metallic implants in an MR environment that can be applied to improve the testing procedure for MR image artifacts in medical implants according to ASTM F2119. METHODS: The numerical approach is validated by comparing simulations and measurements of two metallic test objects made of titanium and stainless steel at three different field strengths (1.5T, 3T and 7T). The difference in artifact size and shape between the simulated and measured artifacts were evaluated. A trend analysis of the artifact sizes in relation to the field strength was performed. RESULTS: The numerical simulation approach shows high similarity (between 75% and 84%) of simulated and measured artifact sizes of metallic implants. Simulated and measured artifact sizes in relation to the field strength resulted in a calculation guideline to determine and predict the artifact size at one field strength (e.g., 3T or 7T) based on a measurement that was obtained at another field strength only (e.g. 1.5T). CONCLUSION: This work presents a novel tool to improve the MR image artifact testing procedure of passive medical implants. With the help of this tool detailed artifact investigations can be performed, which would otherwise only be possible with substantial measurement effort on different MRI systems and field strengths.

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Post-mortem T2 weighted images of canine heads were acquired at 1.5T, 3T, and 7T. This study aimed to (1) identify anatomical structures of the canine brain using an ultra-high-field magnetic resonance imaging (MRI) (7T) to help to facilitate their localization on high field MRI images (3T and 1.5T), where these structures may appear less well defined and delineated and (2) evaluate the visibility of canine brain anatomical structures on 1.5T, 3T, and 7T MRI images for optimizing clinical utility. Our hypothesis was that the provided subjective image quality comparison at different field strengths may offer a general baseline for canine brain anatomy and may help clinicians evaluate MRI options better. Six canine heads were examined with 1.5T, 3T, and 7T MRI scanners. T2-weighted images were acquired in three orthogonal planes at each field strength using a turbo spin-echo sequence. Fifty neuroanatomic structures were identified and evaluated on the 7T MR images; subsequently, those were found on the 3T and 45 out of the 50 structures were detected on the 1.5T imaging. The structures that were not able to be identified on the 1.5T imaging included the septum pellucidum, oculomotor nucleus, substantia nigra, claustrum, and thalamic nucleus griseus. Images acquired at 7T were subjective of higher spatial and contrast resolution. However, the ultra-high-field images were prone to artifacts at the interface between tissues of different magnetic properties. In conclusion, 3T MR imaging appears to be the best comprise for evaluating canine brain anatomy on MRI with fewer imaging artifacts.

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BACKGROUND: Generative adversarial networks (GAN) can produce images of improved quality but their ability to augment image-based classification is not fully explored. We evaluated if a modified GAN can learn from magnetic resonance imaging (MRI) scans of multiple magnetic field strengths to enhance Alzheimer's disease (AD) classification performance. METHODS: T1-weighted brain MRI scans from 151 participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI), who underwent both 1.5-Tesla (1.5-T) and 3-Tesla imaging at the same time were selected to construct a GAN model. This model was trained along with a three-dimensional fully convolutional network (FCN) using the generated images (3T*) as inputs to predict AD status. Quality of the generated images was evaluated using signal to noise ratio (SNR), Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) and Natural Image Quality Evaluator (NIQE). Cases from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL, n = 107) and the National Alzheimer's Coordinating Center (NACC, n = 565) were used for model validation. RESULTS: The 3T*-based FCN classifier performed better than the FCN model trained using the 1.5-T scans. Specifically, the mean area under curve increased from 0.907 to 0.932, from 0.934 to 0.940, and from 0.870 to 0.907 on the ADNI test, AIBL, and NACC datasets, respectively. Additionally, we found that the mean quality of the generated (3T*) images was consistently higher than the 1.5-T images, as measured using SNR, BRISQUE, and NIQE on the validation datasets. CONCLUSION: This study demonstrates a proof of principle that GAN frameworks can be constructed to augment AD classification performance and improve image quality.

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Motion artifacts are a common occurrence in Magnetic Resonance Imaging exam. Motion during acquisition has a profound impact on workflow efficiency, often requiring a repeat of sequences. Furthermore, motion artifacts may escape notice by technologists, only to be revealed at the time of reading by the radiologists, affecting their diagnostic quality. There is a paucity of clinical tools to identify and quantitatively assess the severity of motion artifacts in MRI. An image with subtle motion may still have diagnostic value, while severe motion may be uninterpretable by radiologists and requires the exam to be repeated. Therefore, a tool for the automatic identification of motion artifacts would aid in maintaining diagnostic quality, while potentially driving workflow efficiencies. Here we aim to quantify the severity of motion artifacts from MRI images using deep learning. Impact of subject movement parameters like displacement and rotation on image quality is also studied. A state-of-the-art, stacked ensemble model was developed to classify motion artifacts into five levels (no motion, slight, mild, moderate and severe) in brain scans. The stacked ensemble model is able to robustly predict rigid-body motion severity across different acquisition parameters, including T1-weighted and T2-weighted slices acquired in different anatomical planes. The ensemble model with XGBoost metalearner achieves 91.6% accuracy, 94.8% area under the curve, 90% Cohen's Kappa, and is observed to be more accurate and robust than the individual base learners.

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A precise control of the particle size of dextran-coated magnetite nanoparticles (Dex-M NPs) was successfully performed by combination of co-precipitation and hydrothermal synthesis methods. The Dex-M NPs, in the size range 3.1-18.9 nm, were used to fabricate biocompatible magnetic fluids for application in magnetic hyperthermia therapy (MHT). The effects of the carrier fluid viscosity, particle size, and applied magnetic field strength (Happl) on the specific loss power (SLP) of the Dex-M NPs were investigated at a fixed magnetic field frequency (f). The experimental results show that SLP of the larger Dex-M NPs significantly decreases for a highly viscous carrier fluid. Moreover, regardless of the carrier fluid viscosity, the particle size strongly affects the heating efficiency of the Dex-M NPs. SLP ranges from zero for the smallest Dex-M NPs (with particle size d = 3.1 nm) to 55.21 W/g for the largest ones (d = 18.9 nm) at Happl = 28 kA/m and f = 120 kHz. The most important finding in our research is that, at a fixed frequency, the optimal size of the Dex-M NPs (the size that maximizes SLP) shows a rising trend by enhancing Happl. In fact, the highest values of SLP at Happl = 11 kA/m, 13 - 17.5 kA/m, and 19 - 28 kA/m are obtained for the Dex-M NPs with d = 11.5 nm, 15 nm, and 18.9 nm, respectively. The shift of optimal size to the higher values by increasing Happl could shed light on the correlated effects of the particle size and Happl on the heating efficiency of magnetic nanoparticles (MNPs) and pave a new way toward the better tuning of them for an effective and biologically safe treatment.

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PURPOSE: The purpose of this study was to investigate the influence of blade width and magnetic field strength on apparent diffusion coefficient values of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) diffusion-weighted imaging in the head and neck at 1.5 and 3.0 T magnetic resonance imaging. METHODS: Fifteen healthy volunteers (eight men and seven women; mean age 36.4 ± 10.1 years) underwent PROPELLER diffusion-weighted imaging using four blade widths at 3.0 T and three blade widths at 1.5 T. For the multigroup comparison of apparent diffusion coefficient values, we performed analysis of variance and Tukey-Kramer tests. The apparent diffusion coefficient values in each organ were compared among the different blade widths and magnetic field strengths by a t test. Inter and intra-observer agreements regarding apparent diffusion coefficient value measurements were evaluated using the intraclass correlation coefficient. RESULTS: No significant differences were observed in apparent diffusion coefficient values of the cerebellum in each blade width at both field strengths. The apparent diffusion coefficient values of the right parotid glands were significantly lower for blade width 32 than for blade width 16 at 3.0 T (1.16 × 10-3 mm2/s vs. 1.01 × 10-3 mm2/s; P < 0.05). The apparent diffusion coefficient values of bilateral parotid glands were significantly higher at 1.5 T than at 3.0 T. Intraclass correlation coefficients were almost perfect to substantial in the cerebellum, whereas they showed moderate agreement in the parotid glands. CONCLUSION: The largest blade width 32 at 3.0 T and high magnetic field strength lowered the apparent diffusion coefficient values of parotid glands of PROPELLER diffusion-weighted imaging. The apparent diffusion coefficient values in the parotid glands of PROPELLER diffusion-weighted imaging may be affected for blade width and magnetic field strength.

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The quantum regime of a plasma-whistler-wave-pumped free-electron laser (FEL) in the presence of an axial-guide magnetic field is presented. By quantizing both the plasma whistler field and axial magnetic field, an N-particle three-dimensional Hamiltonian of quantum-FEL (QFEL) has been derived. Employing Heisenberg evolution equations and introducing a new collective operator which controls the vertical motion of electrons, a quantum dispersion relation of the plasma whistler wiggler has been obtained analytically. Numerical results indicate that, by increasing the intrinsic quantum momentum spread and/or increasing the axial magnetic field strength, the bunching and the radiation fields grow exponentially. In addition, a spiking behavior of the spectrum was observed with increasing cyclotron frequency which provides an enormous improvement in the coherence of QFEL radiation even in a limit close-to-classical regime, where an overlapping of these spikes is observed. Also, an upper limit of the intrinsic quantum momentum spread which depends on the value of the cyclotron frequency was found.

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Objective To develop a sinusoidal alternating magnetic field therapy system in order to overcome the disadvantages of the single output frequency and the low effective value of the output magnetic field strength of the alternating magnetic field therapy system in the market,of which the frequency and magnetic density both were continuously adjustable. Methods Multi winding Helmholtz coil was used as the magnetic field generator.On the basis of inverter technology,bipolar equivalent area method considering dead zone and variable speed integral incremental PID control algorithm were used to achieve the accuracy control of magnetic frequency and density in the coil.The accuracy of the resulting waveform and the accuracy of the magnetic field strength was verified by simulation calculation and system current and magnetic field strength test.Results The magnetic field treatment system gained high performance,total harmonic distortion (THD)of sine wave met the requirements of international standards.The obtained magnetic density was as expected of the simulation and calculation. Conclusion The device provides continuously adjustable magnetic field,which has a positive effect on the research for the medical staff, and technical references are provided to the research of magnetic field therapy system.

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In this paper, we present a novel method for 3D pedestrian navigation of foot-mounted inertial systems by integrating a MEMS-IMU, barometer, and permanent magnet. Zero-velocity update (ZUPT) is a well-known algorithm to eliminate the accumulated error of foot-mounted inertial systems. However, the ZUPT stance phase detector using acceleration and angular rate is threshold-based, which may cause incorrect stance phase estimation in the running gait pattern. A permanent magnet-based ZUPT detector is introduced to solve this problem. Peaks extracted from the magnetic field strength waveform are mid-stances of stance phases. A model of peak-peak information and stance phase duration is developed to have a quantitative calculation method of stance phase duration in different movement patterns. Height estimation using barometer is susceptible to the environment. A height difference information aided barometer (HDIB) algorithm integrating MEMS-IMU and barometer is raised to have a better height estimation. The first stage of HDIB is to distinguish level ground/upstairs/downstairs and the second stage is to calculate height using reference atmospheric pressure obtained from the first stage. At last, a ZUPT-based adaptive average window length algorithm (ZUPT-AAWL) is proposed to calculate the true total travelled distance to have a more accurate percentage error (TTDE). This proposed method is verified via multiple experiments. Numerical results show that TTDE ranges from 0.32% to 1.04% in both walking and running gait patterns, and the height estimation error is from 0 m to 2.35 m.

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OBJECTIVES: This study prospectively evaluates objective image quality (IQ), subjective IQ, and PI-RADS scoring of prostate MRI at 3.0T (3T) and 1.5T (1.5T) within the same patients. METHODS: Sixty-three consecutive patients (64±9years) were prospectively included in this non-inferiority trial, powered at 80% to demonstrate a ≤10% difference in signal-to-noise (SNR) and contrast-to-noise ratio (CNR) of T2-weighted and diffusion-weighted imaging (T2WI, DWI) at 1.5T compared to 3T. Secondary endpoints were analysis of subjective IQ and PI-RADS v2 scoring. RESULTS: All patients received multi-parametric prostate MRI on a 3T (T2WI, DWI, DCE) and bi-parametric MRI (T2WI, DWI) on a 1.5T scanner using body coils, respectively. SNR and CNR of T2WI were similar at 1.5T and 3T (p=0.7-1), but of DWI significantly lower at 1.5T (p<0.01). Subjective IQ was significantly better at 3T for both, T2WI and DWI (p<0.01). PI-RADS scores were comparable for both field strengths (p=0.05-1). Inter-reader agreement was excellent for subjective IQ assessment and PI-RADS scoring (k=0.9-1). CONCLUSION: Prostate MRI at 1.5T can reveal comparable objective image quality in T2WI, but is inferior to 3T in DWI and subjective IQ. However, similar PI-RADS scoring and thus diagnostic performance seems feasible independent of the field strength even without an endorectal coil.

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The aim of this study is to investigate the effect of particles as filler in soft rubber sensors installed in artificial skin. We examine sensors made of natural rubber (NR-latex) that include magnetic particles of Ni and Fe3O4 using magnetic compound fluid (MCF). The 1-mm thickness of the electrolytically polymerized MCF rubber makes production of comparatively thin rubber sensors feasible. We first investigate the effect of magnetic particles Ni and Fe3O4 on the curing of MCF rubber. Next, in order to adjust the electric properties of the MCF rubber, we adopt Al2O3 dielectric particles. We investigate the effect of Al2O3 particles on changes in electric current, voltage and temperature of electrolytically polymerized MCF rubber liquid, and on the electric properties under the application of normal and shear forces. By adjusting the ratio of Ni, Fe3O4, Al2O3 and water in MCF rubber with Al2O3, it is possible to change the electric properties.

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