Stealth RF energy harvesting in MRI using selective shielding.

PURPOSE: To utilize the transmit radiofrequency (RF) field in MRI as a power source, near or within the field of view but without affecting image quality or safety. METHODS: Power harvesting is performed by RF induction in a resonant coil. Resulting RF field distortion in the subject is canceled by a selective shield that couples to the harvester while being transparent to the RF transmitter. Such shielding is designed with the help of electromagnetic simulation. A shielded harvester of 3 cm diameter is implemented, assessed on the bench, and tested in a 3T MRI system, recording power yield during typical scans. RESULTS: The concept of selective shielding is confirmed by simulation. Bench tests show effective power harvesting in the presence of the shield. In the MRI system, it is confirmed that selective shielding virtually eliminates RF perturbation. In scans with the harvester immediately adjacent to a phantom, up to 100 mW of average power are harvested without affecting image quality. CONCLUSION: Selective shielding enables stealthy RF harvesting which can be used to supply wireless power to on-body devices during MRI.

Run-time motion and first-order shim control by expanded servo navigation.

PURPOSE: To provide a navigator-based run-time motion and first-order field correction for three-dimensional human brain imaging with high precision, minimal calibration and acquisition, and fast processing. METHODS: A complex-valued linear perturbation model with feedback control is extended to estimate and correct for gradient shim fields using orbital navigators (2.3 ms). Two approaches for sensitizing the model to gradient fields are presented, one based on finite differences with three additional navigators, and another projection-based approximation requiring no additional navigators. A mechanism for noise decorrelation of the matrix and the data is proposed and evaluated to reduce unwanted parameter biases. RESULTS: The rigid motion and first-order field control achieves robust motion and gradient shim corrections improving image quality in a series of phantom and in vivo experiments with varying field conditions. In phantom scans, magnet drifts, forced gradient field perturbations and field distortions from shifts of a second bottle phantom are successfully corrected. Field estimates of the magnet drifts are in good agreement with concurrent field probe measurements. For in vivo scans, the proposed method mitigates field variations from torso motions while being robust to head motion. In vivo gradient field precisions were 30 nT / m $$ 30\;\mathrm{nT}/\mathrm{m} $$ along with single-digit micrometer and millidegree rigid precisions. CONCLUSION: The navigator-based method achieves accurate, high-precision run-time motion and field corrections with low sequence impact and calibration requirements.

Servo navigators: Linear regression and feedback control for rigid-body motion correction.

PURPOSE: Navigator-based correction of rigid-body motion reconciling high precision with minimal acquisition, minimal calibration and simple, fast processing. METHODS: A short orbital navigator (2.3 ms) is inserted in a three-dimensional (3D) gradient echo sequence for human head imaging. Head rotation and translation are determined by linear regression based on a complex-valued model built either from three reference navigators or in a reference-less fashion, from the first actual navigator. Optionally, the model is expanded by global phase and field offset. Run-time scan correction on this basis establishes servo control that maintains validity of the linear picture by keeping its expansion point stable in the head frame of reference. The technique is assessed in a phantom and demonstrated by motion-corrected imaging in vivo. RESULTS: The proposed approach is found to establish stable motion control both with and without reference acquisition. In a phantom, it is shown to accurately detect motion mimicked by rotation of scan geometry as well as change in global B0 . It is demonstrated to converge to accurate motion estimates after perturbation well beyond the linear signal range. In vivo, servo navigation achieved motion detection with precision in the single-digit range of micrometers and millidegrees. Involuntary and intentional motion in the range of several millimeters were successfully corrected, achieving excellent image quality. CONCLUSION: The combination of linear regression and feedback control enables prospective motion correction for head imaging with high precision and accuracy, short navigator readouts, fast run-time computation, and minimal demand for reference data.

Advances in spiral fMRI: A high-resolution study with single-shot acquisition.

Spiral fMRI has been put forward as a viable alternative to rectilinear echo-planar imaging, in particular due to its enhanced average k-space speed and thus high acquisition efficiency. This renders spirals attractive for contemporary fMRI applications that require high spatiotemporal resolution, such as laminar or columnar fMRI. However, in practice, spiral fMRI is typically hampered by its reduced robustness and ensuing blurring artifacts, which arise from imperfections in both static and dynamic magnetic fields. Recently, these limitations have been overcome by the concerted application of an expanded signal model that accounts for such field imperfections, and its inversion by iterative image reconstruction. In the challenging ultra-high field environment of 7 Tesla, where field inhomogeneity effects are aggravated, both multi-shot and single-shot 2D spiral imaging at sub-millimeter resolution was demonstrated with high depiction quality and anatomical congruency. In this work, we further these advances towards a time series application of spiral readouts, namely, single-shot spiral BOLD fMRI at 0.8 mm in-plane resolution. We demonstrate that high-resolution spiral fMRI at 7 T is not only feasible, but delivers both excellent image quality, BOLD sensitivity, and spatial specificity of the activation maps, with little artifactual blurring. Furthermore, we show the versatility of the approach with a combined in/out spiral readout at a more typical resolution (1.5 mm), where the high acquisition efficiency allows to acquire two images per shot for improved sensitivity by echo combination.

Pulse encoding for ZTE imaging: RF excitation without dead-time penalty.

PURPOSE: To overcome limitations in the duration of RF excitation in zero-TE (ZTE) MRI by exploiting intrinsic encoding properties of RF pulses to retrieve data missed during the dead time caused by the pulse. METHODS: An enhanced ZTE signal model was developed using multiple RF pulses, which enables accessing information hidden in the pulse-induced dead time via encoding intrinsically applied by the RF pulses. Such ZTE with pulse encoding was implemented by acquisition of two ZTE data sets using excitation with similar frequency-swept pulses differing only by a small off-resonance in their center frequency. In this way, the minimum scan time is doubled but each acquisition contributes equally to the SNR, as with ordinary averaging. The method was demonstrated on long-T2 and short-T2 phantoms as well as in in vivo experiments. RESULTS: ZTE with pulse encoding provided good image quality at unprecedented dead-time gaps, demonstrated here up to 6 Nyquist dwells. In head imaging, the ability to use longer excitation pulses led to approximately 2-fold improvements in SNR efficiency as compared with conventional ZTE and allowed the creation of T1 contrast. CONCLUSION: Exploiting intrinsic encoding properties of RF pulses in a new signal model enables algebraic reconstruction of ZTE data sets with large dead-time gaps. This permits larger flip angles, which can be used to achieve enhanced T1 contrast and significant improvements in SNR efficiency in case the Ernst angle can be better approached, thus broadening the range of application of ZTE MRI.

Thermal variation in gradient response: measurement and modeling.

PURPOSE: Many aspects and imperfections of gradient dynamics in MRI have been successfully captured by linear time-invariant (LTI) models. Changes in gradient behavior due to heating, however, violate time invariance. The goal of this work is to study such changes at the level of transfer functions and model them by thermal extension of the LTI framework. METHODS: To study the impact of gradient heating on transfer functions, a clinical MR system was heated using a range of high-amplitude DC and AC waveforms, each followed by measuring transfer functions in rapid succession while the system cooled down. Simultaneously, gradient temperature was monitored with an array of temperature sensors positioned according to initial infrared recordings of the gradient tube. The relation between temperatures and transfer functions is cast into local and global linear models. The models are analysed in terms of self-consistency, conditioning, and prediction performance. RESULTS: Pronounced thermal effects are observed in the time resolved transfer functions, largely attributable to in-coil eddy currents and mechanical resonances. Thermal modeling is found to capture these effects well. The keys to good model performance are well-placed temperature sensors and suitable training data. CONCLUSION: Heating changes gradient response, violating time invariance. The utility of LTI modeling can nevertheless be recovered by a linear thermal extension, relying on temperature sensing and adequate one-time training.

Mono-planar T-Hex: Speed and flexibility for high-resolution 3D imaging.

PURPOSE: The aim of this work is the reconciliation of high spatial and temporal resolution for MRI. For this purpose, a novel sampling strategy for 3D encoding is proposed, which provides flexible k-space segmentation along with uniform sampling density and benign filtering effects related to signal decay. METHODS: For time-critical MRI applications such as functional MRI (fMRI), 3D k-space is usually sampled by stacking together 2D trajectories such as echo planar imaging (EPI) or spiral readouts, where each shot covers one k-space plane. For very high temporal and medium to low spatial resolution, tilted hexagonal sampling (T-Hex) was recently proposed, which allows the acquisition of a larger k-space volume per excitation than can be covered with a planar readout. Here, T-Hex is described in a modified version where it instead acquires a smaller k-space volume per shot for use with medium temporal and high spatial resolution. RESULTS: Mono-planar T-Hex sampling provides flexibility in the choice of speed, signal-to-noise ratio (SNR), and contrast for rapid MRI acquisitions. For use with a conventional gradient system, it offers the greatest benefit in a regime of high in-plane resolution <1 mm. The sampling scheme is combined with spirals for high sampling speed as well as with more conventional EPI trajectories. CONCLUSION: Mono-planar T-Hex sampling combines fast 3D encoding with SNR efficiency and favorable depiction characteristics regarding noise amplification and filtering effects from T2∗ decay, thereby providing flexibility in the choice of imaging parameters. It is attractive both for high-resolution time series such as fMRI and for applications that require rapid anatomical imaging.

Whole-brain estimates of directed connectivity for human connectomics.

Connectomics is essential for understanding large-scale brain networks but requires that individual connection estimates are neurobiologically interpretable. In particular, a principle of brain organization is that reciprocal connections between cortical areas are functionally asymmetric. This is a challenge for fMRI-based connectomics in humans where only undirected functional connectivity estimates are routinely available. By contrast, whole-brain estimates of effective (directed) connectivity are computationally challenging, and emerging methods require empirical validation. Here, using a motor task at 7T, we demonstrate that a novel generative model can infer known connectivity features in a whole-brain network (>200 regions, >40,000 connections) highly efficiently. Furthermore, graph-theoretical analyses of directed connectivity estimates identify functional roles of motor areas more accurately than undirected functional connectivity estimates. These results, which can be achieved in an entirely unsupervised manner, demonstrate the feasibility of inferring directed connections in whole-brain networks and open new avenues for human connectomics.

Feasibility of spiral fMRI based on an LTI gradient model.

Spiral imaging is very well suited for functional MRI, however its use has been limited by the fact that artifacts caused by gradient imperfections and B0 inhomogeneity are more difficult to correct compared to EPI. Effective correction requires accurate knowledge of the traversed k-space trajectory. With the goal of making spiral fMRI more accessible, we have evaluated image reconstruction using trajectories predicted by the gradient impulse response function (GIRF), which can be determined in a one-time calibration step. GIRF-predicted reconstruction was tested for high-resolution (0.8 mm) fMRI at 7T. Image quality and functional results of the reconstructions using GIRF-prediction were compared to reconstructions using the nominal trajectory and concurrent field monitoring. The reconstructions using nominal spiral trajectories contain substantial artifacts and the activation maps contain misplaced activation. Image artifacts are substantially reduced when using the GIRF-predicted reconstruction, and the activation maps for the GIRF-predicted and monitored reconstructions largely overlap. The GIRF reconstruction provides a large increase in the spatial specificity of the activation compared to the nominal reconstruction. The GIRF-reconstruction generates image quality and fMRI results similar to using a concurrently monitored trajectory. The presented approach does not prolong or complicate the fMRI acquisition. Using GIRF-predicted trajectories has the potential to enable high-quality spiral fMRI in situations where concurrent trajectory monitoring is not available.

Hemodynamic modeling of long-term aspirin effects on blood oxygenated level dependent responses at 7 Tesla in patients at cardiovascular risk.

Aspirin is considered a potential confound for functional magnetic resonance imaging (fMRI) studies. This is because aspirin affects the synthesis of prostaglandin, a vasoactive mediator centrally involved in neurovascular coupling, a process underlying blood oxygenated level dependent (BOLD) responses. Aspirin-induced changes in BOLD signal are a potential confound for fMRI studies of at-risk individuals or patients (e.g. with cardiovascular conditions or stroke) who receive low-dose aspirin prophylactically and are compared to healthy controls without aspirin. To examine the severity of this potential confound, we combined high field (7 Tesla) MRI during a simple hand movement task with a biophysically informed hemodynamic model. We compared elderly individuals receiving aspirin for primary or secondary prophylactic purposes versus age-matched volunteers without aspirin medication, testing for putative differences in BOLD responses. Specifically, we fitted hemodynamic models to BOLD responses from 14 regions activated by the task and examined whether model parameter estimates were significantly altered by aspirin. While our analyses indicate that hemodynamics differed across regions, consistent with the known regional variability of BOLD responses, we neither found a significant main effect of aspirin (i.e., an average effect across brain regions) nor an expected drug × region interaction. While our sample size is not sufficiently large to rule out small-to-medium global effects of aspirin, we had adequate statistical power for detecting the expected interaction. Altogether, our analysis suggests that patients with cardiovascular risk receiving low-dose aspirin for primary or secondary prophylactic purposes do not show strongly altered BOLD signals when compared to healthy controls without aspirin.

Elastomer coils for wearable MR detection.

PURPOSE: To explore the use of conductive elastomer for MR signal detection and the utility of this approach for wearable detector arrays. METHODS: An elastomer filled with silver microparticles was used to form stretchable radiofrequency coils for MR detection. Their electrical performance in terms of the Qunloaded and Q ratio was assessed in the relaxed state and under repeated strain up to 40%. In a phantom imaging study, the signal-to-noise ratio yield of conductive elastomer coils was compared with that of a reference copper coil. Four elastomer coils were integrated with a stretchable textile substrate to form a wearable array for knee imaging. The array was employed for multiple-angle and kinematic knee imaging in vivo. RESULTS: The elastomer coils proved highly stretchable and mechanically robust. Upon repeated stretching by 20%, a medium-sized coil element settled at Qunloaded of 42 in the relaxed state and 32 at full strain, reflecting sample-noise dominance. The signal-to-noise ratio of elastomer coils was found to be 8% to 16% lower than that achieved with a conventional copper coil. Multiple-angle and kinematic knee imaging with the wearable array yielded high-quality results indicating robustness of detection performance against stretching and warping of the array. CONCLUSION: Conductive elastomer is a viable material for MR detection. Coils made from this material reconcile high stretchability and adequate electrical performance with ease of manufacturing. Conductive elastomer also offers inherent restoring forces and is readily washable and sanitizable, making it an excellent basis of wearable detector front ends.

T-Hex: Tilted hexagonal grids for rapid 3D imaging.

PURPOSE: The purpose of this work is to devise and demonstrate an encoding strategy for 3D MRI that reconciles high speed with flexible segmentation, uniform k-space density, and benign T2∗ effects. METHODS: Fast sampling of a 3D k-space is typically accomplished by 2D readouts per shot using EPI trains or spiral readouts. Tilted hexagonal (T-Hex) sampling is a way of acquiring more k-space volume per excitation while maintaining uniform sampling density and a smooth T2∗ filter. The k-space volume covered per shot is controlled by the tilting angle. Image reconstruction is performed with a 3D extension of the iterative SENSE approach, incorporating actual field dynamics and static off-resonance. T-Hex imaging is compared with established 3D schemes in terms of speed and noise performance. RESULTS: Tilted hexagonal acquisition is found to achieve greater imaging speed than known alternatives, particularly in combination with spiral trajectories. The interplay of the proposed 3D trajectories, array detection, and off-resonance is successfully addressed by iterative inversion of the full signal model. Enhanced coverage per shot is of greatest utility for high speed in an intermediate resolution regime of 1 to 4 mm. T-Hex EPI combines the benefits of extended coverage per shot with increased robustness against off-resonance effects. CONCLUSION: Sampling of tilted hexagonal grids is a feasible means of gaining 3D imaging speed with near-optimal SNR efficiency and benign depiction properties. It is a particularly promising technique for time-resolved applications such as fMRI.

On the signal-to-noise ratio benefit of spiral acquisition in diffusion MRI.

PURPOSE: Spiral readouts combine several favorable properties that promise superior net sensitivity for diffusion imaging. The purpose of this study is to verify the signal-to-noise ratio (SNR) benefit of spiral acquisition in comparison with current echo-planar imaging (EPI) schemes. METHODS: Diffusion-weighted in vivo brain data from three subjects were acquired with a single-shot spiral sequence and several variants of single-shot EPI, including full-Fourier and partial-Fourier readouts as well as different diffusion-encoding schemes. Image reconstruction was based on an expanded signal model including field dynamics obtained by concurrent field monitoring. The effective resolution of each sequence was matched to that of full-Fourier EPI with 1 mm nominal resolution. SNR maps were generated by determining the noise statistics of the raw data and analyzing the propagation of equivalent synthetic noise through image reconstruction. Using the same approach, maps of noise amplification due to parallel imaging (g-factor) were calculated for different acceleration factors. RESULTS: Relative to full-Fourier EPI at b = 0 s/mm2 , spiral acquisition yielded SNR gains of 42-88% and 40-89% in white and gray matter, respectively, depending on the diffusion-encoding scheme. Relative to partial-Fourier EPI, the gains were 36-44% and 34-42%. Spiral g-factor maps exhibited less spatial variation and lower maxima than their EPI counterparts. CONCLUSION: Spiral readouts achieve significant SNR gains in the order of 40-80% over EPI in diffusion imaging at 3T. Combining systematic effects of shorter echo time, readout efficiency, and favorable g-factor behavior, similar benefits are expected across clinical and neurosciences uses of diffusion imaging.

Improved gradient waveforms for oscillating gradient spin-echo (OGSE) diffusion tensor imaging.

The dependence of the diffusion tensor on frequency is of great interest in studies of tissue microstructure because it reveals restrictions to the Brownian motion of water molecules caused by cell membranes. Oscillating gradient spin-echo (OGSE) sequences can sample this dependence with gradient shapes for which the power spectrum of the zeroth moment is focused at a target frequency. In order to maintain the total spectral power (ie the b-value), oscillating gradient amplitudes must grow with the frequency squared. For this reason, OGSE applications on clinical MRI scanners are limited to low frequencies, for which it is difficult to obtain a narrow frequency bandwidth of the gradient moment in a useful echo time. In particular, the commonly used pair of single-period trapezoidal-cosine pulses separated by a half-period produces significant side lobes away from the target frequency. To mitigate this effect, improved OGSE waveforms are proposed, which reduce the gap between the two gradient pulses to the minimum duration required for the refocusing RF pulse. Additionally, a slight deviation from the periodicity of the waveforms is proposed in order to permit using the maximum slew rate of the gradient system for all lobes of trapezoidal waveforms while maintaining advantageous spectral properties, which is not the case for the currently used OGSE sequences. Numerical calculations validate these changes, showing that both modifications significantly narrow the gradient moment power spectrum and increase the contribution of its main lobe to the b-value, thus improving the specificity of the measurement. The utility of the new shapes is demonstrated by diffusion tensor measurements of human white matter in vivo over the range of 30-75 Hz with a b-value of nearly 1000 s/mm2 , using a high-performance gradient insert. However, the improvement should increase the sampling precision of OGSE experiments for all gradient systems.

HYFI: Hybrid filling of the dead-time gap for faster zero echo time imaging.

The aim of this work was to improve the SNR efficiency of zero echo time (ZTE) MRI pulse sequences for faster imaging of short-T2 components at large dead-time gaps. ZTE MRI with hybrid filling (HYFI) is a strategy for retrieving inner k-space data missed during the dead-time gaps arising from radio-frequency excitation and switching in ZTE imaging. It performs hybrid filling of the inner k-space with a small single-point-imaging core surrounded by a stack of shells acquired on radial readouts in an onion-like fashion. The exposition of this concept is followed by translation into guidelines for parameter choice and implementation details. The imaging properties and performance of HYFI are studied in simulations as well as phantom, in vitro and in vivo imaging, with an emphasis on comparison with the pointwise encoding time reduction with radial acquisition (PETRA) technique. Simulations predict higher SNR efficiency for HYFI compared with PETRA at preserved image quality, with the advantage increasing with the size of the k-space gap. These results are confirmed by imaging experiments with gap sizes of 25 to 50 Nyquist dwells, in which scan times for similar image quality could be reduced by 25% to 60%. The HYFI technique provides both high SNR efficiency and image quality, thus outperforming previously known ZTE-based pulse sequences, in particular for large k-space gaps. Promising applications include direct imaging of ultrashort-T2 components, such as the myelin bilayer or collagen, T2 mapping of ultrafast relaxing signals, and ZTE imaging with reduced chemical shift artifacts.

Motion detection with NMR markers using real-time field tracking in the laboratory frame.

PURPOSE: To enhance the utility of motion detection with nuclear magnetic resonance (NMR) markers by removing the need for sequence-dependent calibration. METHODS: Two sets of NMR markers are used for simultaneous observation of magnetic field dynamics during imaging procedures. A set of stationary markers at known positions in the laboratory frame serves to determine the field evolution in that frame. Concurrent recording from a set of head-mounted markers then permits calculating their lab-frame positions and derived rigid-body motion parameters. The precision and accuracy of this approach are evaluated relative to current calibration-based solutions. Use for prospective motion correction is then demonstrated in high-resolution imaging of long scan duration. RESULTS: Motion detection with real-time field tracking overcomes the need for explicit calibration without compromising precision, which is assessed at 10 to 30 µm. Relative to full conventional calibration, it is found to offer superior robustness against thermal drift. Relative to more economical modes of calibration, it achieves substantially higher accuracy. Prospective motion correction based on real-time field tracking resulted in consistently high image quality even when head motion exceeded the image resolution by one order of magnitude. CONCLUSION: Real-time field tracking enables motion detection with NMR markers without calibration overhead and thus overcomes a key obstacle toward routine use. In addition, it renders this mode of motion tracking more robust against system imperfections.

Echo-planar imaging of the human head with 100 mT/m gradients and high-order modeling of eddy current fields.

PURPOSE: To demonstrate the utility of a high-performance gradient insert for ultrafast MRI of the human head. METHODS: EPI was used for the first time with a readout gradient amplitude of 100 mT/m, 1200 T/m/s slew rate, and nearly 1 MHz signal bandwidth for human head scanning. To avoid artefacts due to eddy currents, the magnetic field was dynamically monitored with NMR probes at multiple points, modeled by solid harmonics up to fifth order, and included in the image reconstruction. An approximation of a negligible intra-echo effect of the eddy currents was made to accelerate the high-order reconstruction. The field monitoring-based approach was compared with a recently proposed phase error estimation from separate reconstructions of even and odd echoes. RESULTS: Images obtained with the gradient insert have significantly lower distortions than it is the case with the whole body 30 mT/m, 200 T/m/s gradients of the same system. However, eddy currents of high spatial order must be properly characterized and corrected for in order to avoid a persistent 2D Nyquist ghost. Multi-position monitoring proves to be a robust method to measure the eddy currents and allows higher undersampling rates than the image-based approach. The proposed approximation of the eddy currents effect allows a significant acceleration of the high-order reconstruction by a separate processing of each spatial dimension. CONCLUSION: Strong gradients with adequate switching rates are highly beneficial for the quality of EPI provided that robust measures are taken to include the contribution of eddy currents to the image encoding.

A transmit-receive array for brain imaging with a high-performance gradient insert.

PURPOSE: The aim of this work was to provide parallel imaging capability for the human head in a gradient insert of 33-cm inner diameter within the related constraints of space, encoding ambiguity, and eddy current immunity. METHODS: Eddy current behavior of the 8-channel transmit-receive array coil was investigated via heating and field deviation measurements. RF performance was evaluated using S-parameters, noise statistics, B1 maps, and g-factor maps. In vivo images of a human head and knee were acquired with Cartesian readout and TE below 0.45 ms. RESULTS: Under intense gradient use, the shield was heated up to 55°C and other coil structures to 40°C. After standard preemphasis calibration, eddy current-related field distortions caused by the developed RF coil were smaller than for a commercial receive-only coil. In the ambiguous regions of the gradient, B1+ is 20 dB lower than in the center of the FOV. Coupling between elements is below -15 dB, and noise correlation is less than 0.31 when the coil is loaded with a head. Power efficiency was 0.52 ± 0.02 µT/√W, and the SD of the flip angle was below 10% in central slices of the brain. 2D, up to fourfold acceleration causes less than 30% noise amplification. The RF coil can be used during full gradient performance. CONCLUSION: Based on the described features, the presented coil enables parallel imaging in the high-performance gradient insert.

High-resolution short-T2 MRI using a high-performance gradient.

PURPOSE: To achieve high resolution in imaging of short-T2 materials and tissues by using a high-performance human-sized gradient insert with strength up to 200 mT/m and 100% duty cycle. METHODS: Dedicated short-T2 methodology and hardware are used, such as the pointwise encoding time reduction with radial acquisition (PETRA) technique with modulated excitation pulses, optimized radio-frequency hardware, and a high-performance gradient insert. A theoretical analysis of actual spatial resolution and SNR is provided to support the choice of scan parameters and interpretation of the results. Imaging is performed in resolution phantoms, animal specimen, and human volunteers at both conventional and maximum available gradient strengths and compared using image subtraction. RESULTS: Calculations suggest that increasing gradient strength beyond conventional values considerably improves both actual resolution and SNR efficiency in short-T2 imaging. Resolution improvements are confirmed in all investigated samples, in particular 2 mm slots were resolved in a hard-plastic plate with T2 ≈ 10 µs and in vivo musculoskeletal images were acquired at isotropic 200 µm resolution. Expected improvements in signal yield are realized in fine structures benefitting from high resolution but to less extent in regions of low contrast where decay-related blurring leads to signal overlap between neighboring locations. CONCLUSION: Strong gradients with high duty cycle enable short-T2 imaging at unprecedentedly high resolution, holding the potential for improving MRI of, eg, bone, tendon, lung, or teeth. Moreover, it allows direct access of tissues with T2 of tens of microseconds such as myelin or collagen.

A generative model of whole-brain effective connectivity.

The development of whole-brain models that can infer effective (directed) connection strengths from fMRI data represents a central challenge for computational neuroimaging. A recently introduced generative model of fMRI data, regression dynamic causal modeling (rDCM), moves towards this goal as it scales gracefully to very large networks. However, large-scale networks with thousands of connections are difficult to interpret; additionally, one typically lacks information (data points per free parameter) for precise estimation of all model parameters. This paper introduces sparsity constraints to the variational Bayesian framework of rDCM as a solution to these problems in the domain of task-based fMRI. This sparse rDCM approach enables highly efficient effective connectivity analyses in whole-brain networks and does not require a priori assumptions about the network's connectivity structure but prunes fully (all-to-all) connected networks as part of model inversion. Following the derivation of the variational Bayesian update equations for sparse rDCM, we use both simulated and empirical data to assess the face validity of the model. In particular, we show that it is feasible to infer effective connection strengths from fMRI data using a network with more than 100 regions and 10,000 connections. This demonstrates the feasibility of whole-brain inference on effective connectivity from fMRI data - in single subjects and with a run-time below 1 min when using parallelized code. We anticipate that sparse rDCM may find useful application in connectomics and clinical neuromodeling - for example, for phenotyping individual patients in terms of whole-brain network structure.