A head template for computational dose modelling for transcranial focused ultrasound stimulation.

Transcranial focused Ultrasound Stimulation (TUS) at low intensities is emerging as a novel non-invasive brain stimulation method with higher spatial resolution than established transcranial stimulation methods and the ability to selectively stimulate also deep brain areas. Accurate control of the focus position and strength of the TUS acoustic waves is important to enable a beneficial use of the high spatial resolution and to ensure safety. As the human skull causes strong attenuation and distortion of the waves, simulations of the transmitted waves are needed to accurately determine the TUS dose distribution inside the cranial cavity. The simulations require information of the skull morphology and its acoustic properties. Ideally, they are informed by computed tomography (CT) images of the individual head. However, suited individual imaging data is often not readily available. For this reason, we here introduce and validate a head template that can be used to estimate the average effects of the skull on the TUS acoustic wave in the population. The template was created from CT images of the heads of 29 individuals of different ages (between 20-50 years), gender and ethnicity using an iterative non-linear co-registration procedure. For validation, we compared acoustic and thermal simulations based on the template to the average of the simulation results of all 29 individual datasets. Acoustic simulations were performed for a model of a focused transducer driven at 500 kHz, placed at 24 standardized positions by means of the EEG 10-10 system. Additional simulations at 250 kHz and 750 kHz at 16 of the positions were used for further confirmation. The amount of ultrasound-induced heating at 500 kHz was estimated for the same 16 transducer positions. Our results show that the template represents the median of the acoustic pressure and temperature maps from the individuals reasonably well in most cases. This underpins the usefulness of the template for the planning and optimization of TUS interventions in studies of healthy young adults. Our results further indicate that the amount of variability between the individual simulation results depends on the position. Specifically, the simulated ultrasound-induced heating inside the skull exhibited strong interindividual variability for three posterior positions close to the midline, caused by a high variability of the local skull shape and composition. This should be taken into account when interpreting simulation results based on the template.

Optimized flip angle schemes for the split acquisition of fast spin-echo signals (SPLICE) sequence and application to diffusion-weighted imaging.

PURPOSE: The diffusion-weighted SPLICE (split acquisition of fast spin-echo signals) sequence employs split-echo rapid acquisition with relaxation enhancement (RARE) readout to provide images almost free of geometric distortions. However, due to the varying T 2 $$ {}_2 $$ -weighting during k-space traversal, SPLICE suffers from blurring. This work extends a method for controlling the spatial point spread function (PSF) while optimizing the signal-to-noise ratio (SNR) achieved by adjusting the flip angles in the refocusing pulse train of SPLICE. METHODS: An algorithm based on extended phase graph (EPG) simulations optimizes the flip angles by maximizing SNR for a flexibly chosen predefined target PSF that describes the desired k-space density weighting and spatial resolution. An optimized flip angle scheme and a corresponding post-processing correction filter which together achieve the target PSF was tested by healthy subject brain imaging using a clinical 1.5 T scanner. RESULTS: Brain images showed a clear and consistent improvement over those obtained with a standard constant flip angle scheme. SNR was increased and apparent diffusion coefficient estimates were more accurate. For a modified Hann k-space weighting example, considerable benefits resulted from acquisition weighting by flip angle control. CONCLUSION: The presented flexible method for optimizing SPLICE flip angle schemes offers improved MR image quality of geometrically accurate diffusion-weighted images that makes the sequence a strong candidate for radiotherapy planning or stereotactic surgery.

Volumetric measurements of weak current-induced magnetic fields in the human brain at high resolution.

PURPOSE: Clinical use of transcranial electrical stimulation (TES) requires accurate knowledge of the injected current distribution in the brain. MR current density imaging (MRCDI) uses measurements of the TES-induced magnetic fields to provide this information. However, sufficient sensitivity and image quality in humans in vivo has only been documented for single-slice imaging. METHODS: A recently developed, optimally spoiled, acquisition-weighted, gradient echo-based 2D-MRCDI method has now been advanced for volume coverage with densely or sparsely distributed slices: The 3D rectilinear sampling (3D-DENSE) and simultaneous multislice acquisition (SMS-SPARSE) were optimized and verified by cable-loop experiments and tested with 1-mA TES experiments for two common electrode montages. RESULTS: Comparisons between the volumetric methods against the 2D-MRCDI showed that relatively long acquisition times of 3D-DENSE using a single slab with six slices hindered the expected sensitivity improvement in the current-induced field measurements but improved sensitivity by 61% in the Laplacian of the field, on which some MRCDI reconstruction methods rely. Also, SMS-SPARSE acquisition of three slices, with a factor 2 CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) acceleration, performed best against the 2D-MRCDI with sensitivity improvements for the ∆ B z , c $$ \Delta {B}_{z,c} $$ and Laplacian noise floors of 56% and 78% (baseline without current flow) as well as 43% and 55% (current injection into head). SMS-SPARSE reached a sensitivity of 67 pT for three distant slices at 2 × 2 × 3 mm3 resolution in 10 min of total scan time, and consistently improved image quality. CONCLUSION: Volumetric MRCDI measurements with high sensitivity and image quality are well suited to characterize the TES field distribution in the human brain.

Tracking of rigid head motion during MRI using an EEG system.

PURPOSE: To demonstrate a novel method for tracking of head movements during MRI using electroencephalography (EEG) hardware for recording signals induced by native imaging gradients. THEORY AND METHODS: Gradient switching during simultaneous EEG-fMRI induces distortions in EEG signals, which depend on subject head position and orientation. When EEG electrodes are interconnected with high-impedance carbon wire loops, the induced voltages are linear combinations of the temporal gradient waveform derivatives. We introduce head tracking based on these signals (CapTrack) involving 3 steps: (1) phantom scanning is used to characterize the target sequence and a fast calibration sequence; (2) a linear relation between changes of induced signals and head pose is established using the calibration sequence; and (3) induced signals recorded during target sequence scanning are used for tracking and retrospective correction of head movement without prolonging the scan time of the target sequence. Performance of CapTrack is compared directly to interleaved navigators. RESULTS: Head-pose tracking at 27.5 Hz during echo planar imaging (EPI) was demonstrated with close resemblance to rigid body alignment (mean absolute difference: [0.14 0.38 0.15]-mm translation, [0.30 0.27 0.22]-degree rotation). Retrospective correction of 3D gradient-echo imaging shows an increase of average edge strength of 12%/-0.39% for instructed/uninstructed motion with CapTrack pose estimates, with a tracking interval of 1561 ms and high similarity to interleaved navigator estimates (mean absolute difference: [0.13 0.33 0.12] mm, [0.28 0.15 0.22] degrees). CONCLUSION: Motion can be estimated from recordings of gradient switching with little or no sequence modification, optionally in real time at low computational burden and synchronized to image acquisition, using EEG equipment already found at many research institutions.

On the reconstruction of magnetic resonance current density images of the human brain: Pitfalls and perspectives.

Magnetic resonance current density imaging (MRCDI) of the human brain aims to reconstruct the current density distribution caused by transcranial electric stimulation from MR-based measurements of the current-induced magnetic fields. So far, the MRCDI data acquisition achieves only a low signal-to-noise ratio, does not provide a full volume coverage and lacks data from the scalp and skull regions. In addition, it is only sensitive to the component of the current-induced magnetic field parallel to the scanner field. The reconstruction problem thus involves coping with noisy and incomplete data, which makes it mathematically challenging. Most existing reconstruction methods have been validated using simulation studies and measurements in phantoms with simplified geometries. Only one reconstruction method, the projected current density algorithm, has been applied to human in-vivo data so far, however resulting in blurred current density estimates even when applied to noise-free simulated data. We analyze the underlying causes for the limited performance of the projected current density algorithm when applied to human brain data. In addition, we compare it with an approach that relies on the optimization of the conductivities of a small number of tissue compartments of anatomically detailed head models reconstructed from structural MR data. Both for simulated ground truth data and human in-vivo MRCDI data, our results indicate that the estimation of current densities benefits more from using a personalized volume conductor model than from applying the projected current density algorithm. In particular, we introduce a hierarchical statistical testing approach as a principled way to test and compare the quality of reconstructed current density images that accounts for the limited signal-to-noise ratio of the human in-vivo MRCDI data and the fact that the ground truth of the current density is unknown for measured data. Our results indicate that the statistical testing approach constitutes a valuable framework for the further development of accurate volume conductor models of the head. Our findings also highlight the importance of tailoring the reconstruction approaches to the quality and specific properties of the available data.

Sensitivity and resolution improvement for in vivo magnetic resonance current-density imaging of the human brain.

PURPOSE: Magnetic resonance current-density imaging (MRCDI) combines MRI with low-intensity transcranial electrical stimulation (TES; 1-2 mA) to map current flow in the brain. However, usage of MRCDI is still hampered by low measurement sensitivity and image quality. METHODS: Recently, a multigradient-echo-based MRCDI approach has been introduced that presently has the best-documented efficiency. This MRCDI approach has now been advanced in three directions and has been validated by phantom and in vivo experiments. First, the importance of optimum spoiling for brain imaging was verified. Second, the sensitivity and spatial resolution were improved by using acquisition weighting. Third, navigators were added as a quality control measure for tracking physiological noise. Combining these advancements, the optimized MRCDI method was tested by using 1 mA TES for two different injection profiles. RESULTS: For a session duration of 4:20 min, the new MRCDI method was able to detect TES-induced magnetic fields at a sensitivity level of 84 picotesla, representing a twofold efficiency increase against our original method. A comparison between measurements and simulations based on personalized head models showed a consistent increase in the coefficient of determination of ΔR2 = 0.12 for the current-induced magnetic fields and ΔR2 = 0.22 for the current flow reconstructions. Interestingly, some of the simulations still clearly deviated from the measurements despite the strongly improved measurement quality. This highlights the utility of MRCDI to improve head models for TES simulations. CONCLUSION: The achieved sensitivity improvement is an important step from proof-of-concept studies toward a broader application of MRCDI in clinical and basic neuroscience research.

Elevated body weight modulates subcortical volume change and associated clinical response following electroconvulsive therapy.

Background: Obesity is a frequent somatic comorbidity of major depression, and it has been associated with worse clinical outcomes and brain structural abnormalities. Converging evidence suggests that electroconvulsive therapy (ECT) induces both clinical improvements and increased subcortical grey matter volume in patients with depression. However, it remains unknown whether increased body weight modulates the clinical response and structural neuroplasticity that occur with ECT. Methods: To address this question, we conducted a longitudinal investigation of structural MRI data from the Global ECT-MRI Research Collaboration (GEMRIC) in 223 patients who were experiencing a major depressive episode (10 scanning sites). Structural MRI data were acquired before and after ECT, and we assessed change in subcortical grey matter volume using FreeSurfer and Quarc. Results: Higher body mass index (BMI) was associated with a significantly lower increase in subcortical grey matter volume following ECT. We observed significant negative associations between BMI and change in subcortical grey matter volume, with pronounced effects in the thalamus and putamen, where obese participants showed increases in grey matter volume that were 43.3% and 49.6%, respectively, of the increases found in participants with normal weight. As well, BMI significantly moderated the association between subcortical grey matter volume change and clinical response to ECT. We observed no significant association between BMI and clinical response to ECT. Limitations: Because only baseline BMI values were available, we were unable to study BMI changes during ECT and their potential association with clinical and grey matter volume change. Conclusion: Future studies should take into account the relevance of body weight as a modulator of structural neuroplasticity during ECT treatment and aim to further explore the functional relevance of this novel finding.

Three-dimensional accelerated acquisition for hyperpolarized 13 C MR with blipped stack-of-spirals and conjugate-gradient SENSE.

PURPOSE: To test a new parallel imaging strategy for acceleration of hyperpolarized 13 C MR acquisitions based on a 3D blipped stack-of-spirals trajectory and conjugate-gradient SENSE reconstruction with precalibrated sensitivities. METHODS: The blipped stack-of-spirals trajectory was developed for an acceleration factor of 4, based on an undersampled stack-of-spirals with gradient blips during spiral readout. The trajectory was developed with volumetric coverage of a large FOV and with high spatial resolution. High temporal resolution was attained through spectral-spatial excitation and 4 excitations per volume. The blipped stack-of-spirals was evaluated in simulations and phantom experiments. Next, the method was evaluated for kidney and cardiac imaging in 2 separate healthy pigs. RESULTS: Simulation and phantom results showed successful acquisition and reconstruction, but also revealed reconstruction challenges for certain locations and for wide signal sources. For the kidney experiment, the accelerated acquisition showed high similarity to 2 separately acquired fully sampled data sets with matched spatial and temporal resolution, respectively. For the cardiac experiment, the accelerated acquisition proved able to map each metabolite in 3 dimensions within a single cardiac cycle. CONCLUSION: The proposed method demonstrated effective mapping of metabolism in both kidneys and the heart of healthy pigs. Limitations seen in phantom experiments, may be irrelevant for most clinical applications, but should be kept in mind as well as reconstruction challenges related to residual aliasing. All in all, we show that the blipped stack-of-spirals is a relevant parallel imaging method for hyperpolarized human imaging, facilitating better insights into metabolism compared with nonaccelerated acquisition.

Gamma-aminobutyric acid edited echo-planar spectroscopic imaging (EPSI) with MEGA-sLASER at 7T.

PURPOSE: For rapid spatial mapping of gamma-aminobutyric acid (GABA) at the increased sensitivity and spectral separation for ultra-high magnetic field strength (7 tesla [T]), an accelerated edited magnetic resonance spectroscopic imaging technique was developed and optimized for the human brain at 7 T. METHODS: A MEGA-sLASER sequence was used for GABA editing and volume selection to maximize editing efficiency and minimize chemical shift displacement errors. To accommodate the high bandwidth requirements at 7 T, a single-shot echo planar readout was used for rapid simultaneous encoding of the temporal dimension and 1 spatial. B0 and B1 field aspects specific for 7 T were studied together with correction procedures, and feasibility of the EPSI MEGA-sLASER technique was tested in vivo in 5 healthy subjects. RESULTS: Localized edited spectra could be measured in all subjects giving spatial GABA signal distributions over a central brain region, having 45- to 50-Hz spatial intervoxel B0 field variations and up to 30% B1 field deviations. MEGA editing was found unaffected by the B0 inhomogeneities for the optimized sequence. The correction procedures reduced effects of intervoxel B0 inhomogeneities, corrected for spatial editing efficiency variations, and compensated for GABA resonance phase and frequency shifts from subtle motion and acquisition instabilities. The optimized oscillating echo-planar gradient scheme permitted full spectral acquisition at 7 T and exhibited minimal spectral-spatial ghosting effects for the selected brain region. CONCLUSION: The EPSI MEGA-sLASER technique was shown to provide time-efficient mapping of regional variations in cerebral GABA in a central volume of interest with spatial B1 and B0 field variations typical for 7 T.

Coil profile estimation strategies for parallel imaging with hyperpolarized 13 C MRI.

PURPOSE: To investigate auto- and pre-calibration coil profile estimation for parallel imaging reconstruction of hyperpolarized 13 C MRI volumetric data. METHODS: Parallel imaging reconstruction was studied with 3 different approaches for coil profile estimation: auto-calibration, phantom calibration, and theoretic calibration. Acquisition was performed with a 3D stack-of-spirals sequence with spectral-spatial excitation and Cartesian undersampling. Parallel imaging reconstructions were done with conjugate gradient SENSE and 3D gridding with inhomogeneity correction. The approaches were compared in simulations with different SNR, through phantom experiments, and in an in vivo pig study focused on the kidneys. All imaging was done with a rigid home-built 12-channel 13 C receive coil at 3T. RESULTS: The phantom calibrated and theoretic approaches resulted in the best structural similarities in simulations and demonstrated higher image quality in the phantom experiments compared to the auto-calibrated approach. In vivo mapping of pyruvate uptake and lactate conversion improved for accelerated acquisitions because of a better temporal resolution. From a practical and image quality point of view, use of theoretic coil profiles led to improved results compared to the other approaches. CONCLUSION: The success of the theoretic coil profile estimation demonstrates a negligible effect of load on sensitivity profiles at the carbon frequency at 3T. Through theoretic or phantom calibrated parallel imaging, accelerated 3D volumes could be reconstructed with sufficient sensitivity, temporal, and spatial resolution to map the metabolism of kidneys exemplifying abdominal organs. This approach overcomes a critical step in the clinical translation of parallel imaging in hyperpolarized 13 C MR.

Inductive measurement and encoding of k-space trajectories in MR raw data.

OBJECTIVES:  The objective of this study was to concurrently acquire an inductive k-space trajectory measure and corresponding imaging data by an MR scanner. MATERIALS AND METHODS:  1D gradient measures were obtained by digital integration, regularized using measured gradient coil currents and recorded individually by the scanner concurrently with raw MR data. Gradient measures were frequency modulated into an RF signal receivable by the scanner, yielding a k-space trajectory measure from the cumulative phase of the acquired data. Generation of the gradient measure and frequency modulation was performed by previously developed custom, versatile circuitry. RESULTS:  For a normal echo planar imaging (EPI) sequence, the acquired k-space trajectory measure yielded slightly improved image quality compared to that obtained from using the scanner's estimated eddy current-compensated k-space trajectory. For a spiral trajectory, the regularized inductive k-space trajectory measure lead to a 76% decrease in the root-mean-square error of the reconstructed image. DISCUSSION:  While the proof-of-concept experiments show potential for further improvement, the feasibility of inductively measuring k-space trajectories and increasing the precision through regularization was demonstrated. The approach may offer an inexpensive method to acquire k-space trajectories concurrently with scanning.

Human in-vivo brain magnetic resonance current density imaging (MRCDI).

Magnetic resonance current density imaging (MRCDI) and MR electrical impedance tomography (MREIT) are two emerging modalities, which combine weak time-varying currents injected via surface electrodes with magnetic resonance imaging (MRI) to acquire information about the current flow and ohmic conductivity distribution at high spatial resolution. The injected current flow creates a magnetic field in the head, and the component of the induced magnetic field ΔBz,c parallel to the main scanner field causes small shifts in the precession frequency of the magnetization. The measured MRI signal is modulated by these shifts, allowing to determine ΔBz,c for the reconstruction of the current flow and ohmic conductivity. Here, we demonstrate reliable ΔBz,c measurements in-vivo in the human brain based on multi-echo spin echo (MESE) and steady-state free precession free induction decay (SSFP-FID) sequences. In a series of experiments, we optimize their robustness for in-vivo measurements while maintaining a good sensitivity to the current-induced fields. We validate both methods by assessing the linearity of the measured ΔBz,c with respect to the current strength. For the more efficient SSFP-FID measurements, we demonstrate a strong influence of magnetic stray fields on the ΔBz,c images, caused by non-ideal paths of the electrode cables, and validate a correction method. Finally, we perform measurements with two different current injection profiles in five subjects. We demonstrate reliable recordings of ΔBz,c fields as weak as 1 nT, caused by currents of 1 mA strength. Comparison of the ΔBz,c measurements with simulated ΔBz,c images based on FEM calculations and individualized head models reveals significant linear correlations in all subjects, but only for the stray field-corrected data. As final step, we reconstruct current density distributions from the measured and simulated ΔBz,c data. Reconstructions from non-corrected ΔBz,c measurements systematically overestimate the current densities. Comparing the current densities reconstructed from corrected ΔBz,c measurements and from simulated ΔBz,c images reveals an average coefficient of determination R2 of 71%. In addition, it shows that the simulations underestimated the current strength on average by 24%. Our results open up the possibility of using MRI to systematically validate and optimize numerical field simulations that play an important role in several neuroscience applications, such as transcranial brain stimulation, and electro- and magnetoencephalography.

Sensitivity analysis of magnetic field measurements for magnetic resonance electrical impedance tomography (MREIT).

PURPOSE: Clinical use of magnetic resonance electrical impedance tomography (MREIT) still requires significant sensitivity improvements. Here, the measurement of the current-induced magnetic field (ΔBz,c ) is improved using systematic efficiency analyses and optimization of multi-echo spin echo (MESE) and steady-state free precession free induction decay (SSFP-FID) sequences. THEORY AND METHODS: Considering T1 , T2 , and T2* relaxation in the signal-to-noise ratios (SNRs) of the MR magnitude images, the efficiency of MESE and SSFP-FID MREIT experiments, and its dependence on the sequence parameters, are analytically analyzed and simulated. The theoretical results are experimentally validated in a saline-filled homogenous spherical phantom with relaxation parameters similar to brain tissue. Measurement of ΔBz,c is also performed in a cylindrical phantom with saline and chicken meat. RESULTS: The efficiency simulations and experimental results are in good agreement. When using optimal parameters, ΔBz,c can be reliably measured in the phantom even at injected current strengths of 1 mA or lower for both sequence types. The importance of using proper crusher gradient selection on the phase evolution in a MESE experiment is also demonstrated. CONCLUSION: The efficiencies observed with the optimized sequence parameters will likely render in-vivo human brain MREIT feasible. Magn Reson Med 79:748-760, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Measuring motion-induced B0 -fluctuations in the brain using field probes.

PURPOSE: Fluctuations of the background magnetic field (B0 ) due to body and breathing motion can lead to significant artifacts in brain imaging at ultrahigh field. Corrections based on real-time sensing using external field probes show great potential. This study evaluates different aspects of field interpolation from these probes into the brain which is implicit in such methods. Measurements and simulations were performed to quantify how well B0 -fluctuations in the brain due to body and breathing motion are reflected in external field probe measurements. METHODS: Field probe measurements were compared with scanner acquired B0 -maps from experiments with breathing and shoulder movements. A realistic simulation of B0 -fluctuations caused by breathing was performed, and used for testing different sets of field probe positions. RESULTS: The B0 -fluctuations were well reflected in the field probe measurements in the shoulder experiments, while the breathing experiments showed only moderate correspondence. The simulations showed the importance of the probe positions, and that performing full 3(rd) order corrections based on 16 field probes is not recommended. CONCLUSION: Methods for quantitative assessment of the field interpolation problem were developed and demonstrated. Field corrections based on external field measurements show great potential, although potential pitfalls were identified.

The effects of the CXCR2 antagonist, MK-7123, on bone marrow functions in healthy subjects.

The CXCR2 antagonist MK-7123 causes dose-dependent reductions in absolute neutrophil counts (ANC) and decreases neutrophil tissue responses, but its effects on bone marrow functions are not yet known. We conducted a double-blind, randomized study in 18 healthy subjects comparing the effects of either MK-7123 (30mg, po, daily for 28days) or placebo on peripheral blood counts and bone marrow myeloid cell populations. MK-7123 caused a reversible decrease (approximately 50%) in the ANC as demonstrated on days 1 and 28, the first and last days of the treatment period. Bone marrow aspirate smears and biopsy imprints did not differ in the proportion of mature neutrophils in pretreatment, day 28, day 56 or placebo samples. There were no treatment effects on biopsy or aspirate clot cellularity, myeloid to erythroid or myeloid post-mitotic to mitotic ratios; flow-cytometric analyses of aspirate cells; or bone marrow fat to cell balance as assessed by MRI. MK-7123 was generally well tolerated with neutropenia being the most common adverse event; however, there were no clinical symptoms associated with decreased ANCs. These findings indicate that the CXCR2 antagonist MK-7123 causes rapidly reversible decrease in the ANC without measurable myelosuppressive effects. The results support the development of CXCR2 antagonists as potentially useful anti-inflammatory agents, primarily interrupting neutrophil trafficking.

Decomposition-based framework for tumor classification and prediction of treatment response from longitudinal MRI.

Objective.In the field of radiation oncology, the benefit of MRI goes beyond that of providing high soft-tissue contrast images for staging and treatment planning. With the recent clinical introduction of hybrid MRI linear accelerators it has become feasible to map physiological parameters describing diffusion, perfusion, and relaxation during the entire course of radiotherapy, for example. However, advanced data analysis tools are required for extracting qualified prognostic and predictive imaging biomarkers from longitudinal MRI data. In this study, we propose a new prediction framework tailored to exploit temporal dynamics of tissue features from repeated measurements. We demonstrate the framework using a newly developed decomposition method for tumor characterization.Approach.Two previously published MRI datasets with multiple measurements during and after radiotherapy, were used for development and testing:T2-weighted multi-echo images obtained for two mouse models of pancreatic cancer, and diffusion-weighted images for patients with brain metastases. Initially, the data was decomposed using the novel monotonous slope non-negative matrix factorization (msNMF) tailored for MR data. The following processing consisted of a tumor heterogeneity assessment using descriptive statistical measures, robust linear modelling to capture temporal changes of these, and finally logistic regression analysis for stratification of tumors and volumetric outcome.Main Results.The framework was able to classify the two pancreatic tumor types with an area under curve (AUC) of 0.999,P< 0.001 and predict the tumor volume change with a correlation coefficient of 0.513,P= 0.034. A classification of the human brain metastases into responders and non-responders resulted in an AUC of 0.74,P= 0.065.Significance.A general data processing framework for analyses of longitudinal MRI data has been developed and applications were demonstrated by classification of tumor type and prediction of radiotherapy response. Further, as part of the assessment, the merits of msNMF for tumor tissue decomposition were demonstrated.

Data-driven separation of MRI signal components for tissue characterization.

PURPOSE: MRI can be utilized for quantitative characterization of tissue. To assess e.g. water fractions or diffusion coefficients for compartments in the brain, a decomposition of the signal is necessary. Imposing standard models carries the risk of estimating biased parameters if model assumptions are violated. This work introduces a data-driven multicomponent analysis, the monotonous slope non-negative matrix factorization (msNMF), tailored to extract data features expected in MR signals. METHODS: The msNMF was implemented by extending the standard NMF with monotonicity constraints on the signal profiles and their first derivatives. The method was validated using simulated data, and subsequently applied to both ex vivo DWI data and in vivo relaxometry data. Reproducibility of the method was tested using the latter. RESULTS: The msNMF recovered the multi-exponential signals in the simulated data and showed superiority to standard NMF (based on the explained variance, area under the ROC curve, and coefficient of variation). Diffusion components extracted from the DWI data reflected the cell density of the underlying tissue. The relaxometry analysis resulted in estimates of edema water fractions (EWF) highly correlated with published results, and demonstrated acceptable reproducibility. CONCLUSION: The msNMF can robustly separate MR signals into components with relation to the underlying tissue composition, and may potentially be useful for e.g. tumor tissue characterization.

Safety evaluation of a new setup for transcranial electric stimulation during magnetic resonance imaging.

BACKGROUND: Transcranial electric stimulation during MR imaging can introduce safety issues due to coupling of the RF field with the stimulation electrodes and leads. OBJECTIVE: To optimize the stimulation setup for MR current density imaging (MRCDI) and increase maximum stimulation current, a new low-conductivity (σ = 29.4 S/m) lead wire is designed and tested. METHOD: The antenna effect was simulated to investigate the effect of lead conductivity. Subsequently, specific absorption rate (SAR) simulations for realistic lead configurations with low-conductivity leads and two electrode types were performed at 128 MHz and 298 MHz being the Larmor frequencies of protons at 3T and 7T. Temperature measurements were performed during MRI using high power deposition sequences to ensure that the electrodes comply with MRI temperature regulations. RESULTS: The antenna effect was found for copper leads at » RF wavelength and could be reliably eliminated using low-conductivity leads. Realistic lead configurations increased the head SAR and the local head SAR at the electrodes only minimally. The highest temperatures were measured on the rings of center-surround electrodes, while circular electrodes showed little heating. No temperature increase above the safety limit of 39 °C was observed. CONCLUSION: Coupling to the RF field can be reliably prevented by low-conductivity leads, enabling cable paths optimal for MRCDI. Compared to commercial copper leads with safety resistors, the low-conductivity leads had lower total impedance, enabling the application of higher currents without changing stimulator design. Attention must be paid to electrode pads.

Transducer modeling for accurate acoustic simulations of transcranial focused ultrasound stimulation.

OBJECTIVE: Low-intensity transcranial ultrasound stimulation (TUS) is emerging as a non-invasive brain stimulation technique with superior spatial resolution and the ability to reach deep brain areas. Medical image-based computational modeling could be an important tool for individualized TUS dose control and targeting optimization, but requires further validation. This study aims to assess the impact of the transducer model on the accuracy of the simulations. APPROACH: Using hydrophone measurements, the acoustic beam of a single-element focused transducer (SEFT) with a flat piezoelectric disc and an acoustic lens was characterized. The acoustic beam was assessed in a homogeneous water bath and after transmission through obstacles (3D-printed shapes and skull samples). The acoustic simulations employed the finite-difference time-domain method and were informed by computed tomography (CT) images of the obstacles. Transducer models of varying complexity were tested representing the SEFT either as a surface boundary condition with variable curvature or also accounting for its internal geometry. In addition, a back-propagated pressure distribution from the first measurement plane was used as source model. The simulations and measurements were quantitatively compared using key metrics for peak location, focus size, intensity and spatial distribution. MAIN RESULTS: While a surface boundary with an adapted, 'effective' curvature radius based on the specifications given by the manufacturer could reproduce the measured focus location and size in a homogeneous water bath, it regularly failed to accurately predict the beam after obstacle transmission. In contrast, models that were based on a one-time calibration to the homogeneous water bath measurements performed substantially better in all cases with obstacles. For one of the 3D-printed obstacles, the simulated intensities deviated substantially from the measured ones, irrespective of the transducer model. We attribute this finding to a standing wave effect, and further studies should clarify its relevance for accurate simulations of skull transmission. SIGNIFICANCE: Validated transducer models are important to ensure accurate simulations of the acoustic beam of SEFTs, in particular in the presence of obstacles such as the skull.

Multi-site benchmarking of clinical 13C RF coils at 3T.

A quality assurance protocol for RF coils is proposed, which can be used for volume (Tx/Rx) and surface (Rx) coils. Following this protocol, a benchmarking of seven coils (from three different MR sites) dedicated to 13C MRI at 3T is reported. Coil performance is particularly important for 3T MRI at the 13C frequency, since the coil-to-sample noise ratio is typically high. The coils are evaluated experimentally using the proposed protocol based on MR spectroscopic imaging performed with two different phantoms: one head-shaped, and one with cylindrical shape and nearly twice the volume of the first one. To achieve an unbiased SNR comparison of volume and array coils, coil combination was done using sensitivity profiles extracted from the data. SNR, noise correlation matrices and example g-factor maps are reported. For globally calibrated, equal excitation angles, the measured SNR shows large differences for the volume coils of up to 115% at the phantom center for a head phantom. The arrays show lower differences in superficial SNR. The sample surface depth at which the volume coils outperform the arrays is estimated to 7 cm, and SNR furthest away from the coil surface is 28% lower for the best array compared to the best volume coil. A broad set of coils for 13C at 3T have been benchmarked. The results reported, and the method used to benchmark them, should guide the 13C community to choose the most suitable coil for a given experiment.