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Purpose We present a time-efficient water-selective, parallel transmit RF excitation pulsedesign for ultra-high field applications. Methods The proposed pulse design method achieves flip angle homogenization at ultrahigh fields by employing spatially non-selective kT-points pulses. In order tointroduce water-selection, the concept of binomial pulses is applied. Due to thecomposite nature of kT -points, the pulse can be split into multiple binomial sub-pulse blocks shorter than half the precession period of fat, that are playedout successively. Additional fat precession turns, that would otherwise impairthe spectral response, can thus be avoided. Bloch simulations of the proposedinterleaved binomial kT-points pulses were carried out and compared in terms ofduration, homogeneity, fat suppression and pulse energy. For validation, in vivoMP-RAGE and 3D-EPI data were acquired. Results Simulation results show that interleaved binomial kT-points pulses achieve shorter total pulse durations, improved flip angle homogeneity and more robustfat suppression compared to available methods. Interleaved binomial kT-pointscan be customized by changing the number of kT-points, the sub-pulse duration and the order of the binomial pulse. Using shorter sub-pulses, the number ofkT-points can be increased and hence better homogeneity is achieved, while still maintaining short total pulse durations. Flip angle homogenization and fatsuppression of interleaved binomial kT-points pulses is demonstrated in vivo at 27T, confirming Bloch simulation results. Conclusion In this work, we present a time efficient and robust parallel transmission technique for non-selective water excitation with simultaneous flip angle homogenizationat ultra-high field.

PURPOSE: Parallel transmission (pTx) is an approach to improve image uniformity for ultra-high field imaging. In this study, we modified an echo planar imaging (EPI) sequence to design subject-specific pTx pulses online. We compared its performance against EPI with conventional circularly polarised (CP) pulses. METHODS: We compared the pTx-EPI and CP-EPI sequences in a short EPI acquisition protocol and for two different functional paradigms in six healthy volunteers (2 female, aged 23-36 years, mean age 29.2 years). We chose two paradigms that are typically affected by signal dropout at 7 T: a visual objects localiser to determine face/scene selective brain regions and a semantic-processing task. RESULTS: Across all subjects, pTx-EPI improved whole-brain mean temporal signal-to-noise ratio (tSNR) by 11.0% compared to CP-EPI. We also compared the ability of pTx-EPI and CP-EPI to detect functional activation for three contrasts over the two paradigms: face > object and scene > object for the visual objects localiser and semantic association > pattern matching for the semantic-processing paradigm. Across all three contrasts, pTx-EPI showed higher median z-scores and detected more active voxels in relevant areas, as determined from previous 3 T studies. CONCLUSION: We have demonstrated a workflow for EPI acquisitions with online per-subject pulse calculations. We saw improved performance in both tSNR and functional acquisitions from pTx-EPI. Thus, we believe that online calculation pTx-EPI is robust enough for future fMRI studies, especially where activation is expected in brain areas liable to significant signal dropout.

Parallel transmission (pTx) MRI is an increasingly popular tool to overcome the inhomogeneous RF transmit field at ultra-high field (UHF, ≥7 T). However, the use of pTx requires dedicated RF coils and sequences including measurement of subject-specific RF maps and optimization of pulse waveforms. These extra obligations have historically caused the benefits of pTx to be shadowed by cumbersome workflows requiring high levels of expertise.\ud Fortunately, the UHF community has endeavored to find solutions for “push-and-play” pTx MRI in a step towards one-day clinical integration. In this abstract, we report our experience with two such development pTx sequences. In both cases, the pTx protocols were developed for a commercially available pTx coil, and were tested with the 7T setup in Glasgow using a self-built pTx coil of similar design.\ud The first development sequence investigated was the pTx Direct Signal Control with Variable Excitation and Refocusing (DiSCoVER) method for 2D Turbo Spin-Echo (TSE) imaging, developed by colleagues at King’s College London and Siemens Healthcare UK and Germany. DiSCoVER uses the TSE signal model to modify relative amplitudes and phases (shims) in each transmit channel during the TSE pulse train to generate a homogeneous signal. For T2w imaging, we compared DiSCOVER to conventional single transmission and standard volumetric shimming (fixed channel shims for all excitation and refocusing pulses) in the same volunteer.\ud The second development protocol used 3D MPRAGE and MP2RAGE sequences from the Package of Anatomical Sequences using parallel Transmission UniveRsal kT-point pulses (PASTeUR) developed by CEA Neurospin, Paris-Saclay, France. Figure 2 compares T1w images of a second volunteer from MPRAGE and the composite MP2RAGE UNI image using Universal Pulses (UPs) from PASTeUR.\ud In this initial investigation, both development pTx sequences were user-friendly and showed promising results with a few caveats. Further investigation could improve their performance with the Glasgow 7T pTx setup.

No abstract available.

Purpose\ud Tailored parallel-transmit (pTx) pulses produce uniform excitation profiles at 7 T, but are sensitive to head motion. A potential solution is real-time pulse redesign. A deep learning framework is proposed to estimate pTx urn:x-wiley:07403194:media:mrm29132:mrm29132-math-0003 distributions following within-slice motion, which can then be used for tailored pTx pulse redesign.\ud \ud Methods\ud Using simulated data, conditional generative adversarial networks were trained to predict urn:x-wiley:07403194:media:mrm29132:mrm29132-math-0004 distributions in the head following a displacement. Predictions were made for two virtual body models that were not included in training. Predicted maps were compared with ground-truth (simulated, following motion) B1 maps. Tailored pTx pulses were designed using B1 maps at the original position (simulated, no motion) and evaluated using simulated B1 maps at displaced position (ground-truth maps) to quantify motion-related excitation error. A second pulse was designed using predicted maps (also evaluated on ground-truth maps) to investigate improvement offered by the proposed method.\ud \ud Results\ud Predicted urn:x-wiley:07403194:media:mrm29132:mrm29132-math-0005 maps corresponded well with ground-truth maps. Error in predicted maps was lower than motion-related error in 99% and 67% of magnitude and phase evaluations, respectively. Worst-case flip-angle normalized RMS error due to motion (76% of target flip angle) was reduced by 59% when pulses were redesigned using predicted maps.\ud \ud Conclusion\ud We propose a framework for predicting urn:x-wiley:07403194:media:mrm29132:mrm29132-math-0006 maps online with deep neural networks. Predicted maps can then be used for real-time tailored pulse redesign, helping to overcome head motion–related error in pTx.

The pulsatility of blood flow through cerebral arteries is clinically important, as it is intrinsically associated with cerebrovascular health. In this study we outline a new MRI approach to measuring the real-time pulsatile flow in cerebral arteries, which is based on the inflow phenomenon associated with fast gradient-recalled-echo acquisitions. Unlike traditional phase-contrast techniques, this new method, which we dub Dynamic Inflow Magnitude Contrast (DIMAC), does not require velocity-encoding gradients as sensitivity to flow velocity is derived purely from the inflow effect. We achieved this using a highly accelerated single slice EPI acquisition with a very short TR (15 ms) and a 90° flip angle, thus maximizing inflow contrast. We simulate the spoiled GRE signal in the presence of large arteries and perform a sensitivity analysis to demonstrate that in the regime of high inflow contrast it shows much greater sensitivity to flow velocity over blood volume changes. We support this theoretical prediction with in-vivo data collected in two separate experiments designed to demonstrate the utility of the DIMAC signal contrast. We perform a hypercapnia challenge experiment in order to experimentally modulate arterial tone within subjects, and thus modulate the arterial pulsatile flow waveform. We also perform a thigh-cuff release challenge, designed to induce a transient drop in blood pressure, and demonstrate that the continuous DIMAC signal captures the complex transient change in the pulsatile and non-pulsatile components of flow. In summary, this study proposes a new role for a well-established source of MR image contrast and demonstrates its potential for measuring both steady-state and dynamic changes in arterial tone.

Parallel transmit (pTx) can reduce RF field inhomogeneity present at 7T, but needs additional consideration for the specific absorption rate (SAR) and subsequent tissue heating due to the superimposed electromagnetic fields. Virtual observation points (VOPs) provide a common method for evaluating SAR in parallel transmit (pTx) MRI. The VOP approach uses an Eigenvalue clustering method to group voxels in electromagnetic field (EMF) simulations of realistic human body models. The clustering amount is set by an overestimation factor with respect to the “worst case” SAR configuration of complex pTx channels. It has been suggested to include as many EMF body model simulations at as many positions as computationally feasible in the VOPs to account for potential local SAR hotpots. Nevertheless, commercial pTx coils for 7T are typically supplied without the EMF-based VOPs and instead apply a constant safety factor for local SAR supervision, which can be overly conservative. In this abstract we compare the use of EMF-based VOPs in a self-built pTx head coil to constant safety factor VOPs in a commercial pTx coil of similar design. We investigate the local SAR values with 7T MRI scans in healthy volunteers. Comparing the VOPs’ simulated and experimental performance in both coils, the commercial coil VOPs provide SAR estimates that are highly conservative compared to estimates from VOPs based on anatomical models, yet the image quality from both coils remains very similar (Figure 1). The self-built coil's EMF-based VOPs are closer to the modeled SAR deposition without clustering (Figure 2), thus allowing scanning within the IEC normal mode head limit of 10 W/kg, which wasn’t feasible with the commercial coil. In the future, larger scale EMF simulations are required to explore the effect of subject anatomy and to optimize the use of VOPs for wider application.

Neue Abtastschemata in der Echo-Planaren-Bildgebung Die Echo-Planare-Bildgebung (EPI) ist das schnellste Verfahren zur Datenaufnahme in der Magnetresonanztomographie [1]. Sie ermöglicht Aufnahmen des gesamten Kopfes in ca. 0.5-5 Sekunden. Wegen der hohen Aufnahmegeschwindigkeit wird sie speziell bei bewegungsanfälligen Anwendungen, wie der Diffusionsbildgebung eingesetzt [2]. Weiterhin wird EPI bei dynamischen Vorgängen wie der funktionellen Bildgebung eingesetzt [3]. Zu den Nachteilen der EPI zählen Bildverzerrungen, durch Inhomogenitäten im statischen Magnetfeld und Signalverluste bzw. Auflösungsverluste durch Relaxationseffekte [4]. Aufgrund des schnellen Schaltens der Bildkodiergradienten, vibriert die Gradientenspule im Magneten. Dies erzeugt hohe Lautstärken von bis zu 130 dB während der Messung [5]. Speziell bei Studien mittels funktionaler Magnetresonanzbildgebung sind die lauten Hintergrundgeräusche eine Herausforderung, da akustische Stimulationen, wie z.B. Musik oder die Anweisungen an dem Probanden, übertönt werden. Ersteres zeigt sich in einer verringerten Gehirnaktivität auf die Stimulation [6, 7]. Im ersten Teil dieser Arbeit wird untersucht, wie die Lautstärke von EPI Sequenzen reduziert werden kann. Im zweiten Teil werden Maßnahmen vorgestellt, um die Bildverzerrungen von EPI Sequenzen bei gleichbleibender Aufnahmegeschwindigkeit, zu minimieren. Die neue Methode erzielt eine Verringerung der Lautstärke durch eine Verlängerung der Phasenkodier-Gradienten und der Gradienten zur Multischicht-Kodierung. Gleichzeitig wird eine kontinuierliche Auslese vorgenommen, wodurch der k-Raum nicht mehr mittels eines kartesischen Rasters aufgenommen wird. Die Abweichungen von einem kartesischen k-Raum sind jedoch so gering, dass kartesische Rekonstruktionsverfahren eingesetzt werden können. Dadurch wird die Rekonstruktionszeit in einem klinisch akzeptablen Rahmen gehalten. Das neue Verfahren wird mit zwei bekannten Methoden die Lautstärke zu reduzieren kombiniert. Erstens wird ein sinusförmiger Auslese (engl. Readout, RO) Gradient benutzt, der den Vorteil hat, die Sequenz anhand des Frequenzspektrums auf ein lokales Minimum der Gradientenspule zu setzen [8]. Zweitens wird ROSegmentierung verwendet, wodurch Gradientenamplitude und Anstiegszeiten reduziert werden [9, 10]. Durch die Kombination aller Methoden lässt sich die Lautstärke der EPI um etwa 20 dB reduzieren. Eine Verringerung von Bildverzerrungen kann durch RO Segmentierung erreicht werden [11]. Hierdurch wird jedoch die gesamte Aufnahmezeit verlängert. Die neue Methode basiert auf einer RO Segmentierung, führt aber ein neues Unterabtastschema ein. Hierzu wird jedes RO Segment unterschiedlich Unterabgetastet. Dadurch kann die Messzeit halbiert werden, bei gleichbleibender Bildqualität. Eine alternative Möglichkeit, Bildverzerrungen zu reduzieren, ist interleaved EPI [12]. Hierbei wird der k-Raum entlang Phasenkodierung in mehreren Schritten unterabgetastet aufgenommen. Im Rahmen dieser Arbeit wird ein neues Verfahren zur randomisierten Unterabtastung des k-Raums vorgestellt. Dies ermöglicht zum ersten Mal die Anwendung von Compressed Sensing (CS) [13] in der Echoplanaren Bildgebung. Bei der anatomischen Bildgebung werden Gradientenecho Sequenzen mit CS bis zu 12-fach beschleunigt genutzt. Im Vergleich dazu erzielt die neue Methode (EPI mit CS) Beschleunigungsfaktoren von bis zu 131.6, bei vergleichbarer Bildqualität. Novel Sampling Trajectories in Echo-Planar-Imaging Echo-Planar-Imaging (EPI) is the fastest way to acquire images in Magnetic Resonance Imaging (MRI) [1]. It enables whole brain image acquisition in 0.5 to 5 seconds. Due to these short acquisition times, EPI is especially employed with applications like diffusion MRI that are sensitive to motion [2]. Furthermore, EPI is also used to capture dynamic processes like functional MRI [3]. However, EPI comes with certain disadvantages like distortions from static magnetic field inhomogeneities and signal dropout and blurring through relaxation effects [4]. EPI also produces noise levels of up to 130 dB [5] because the fast gradient switching required causes mechanical vibration of the gradient coil. This noise is detrimental to functional studies where it is critical to hear and understand acoustic stimulations like music or commands from the operator for adequate brain activity measurements [6, 7]. The first part of this work investigates how to decrease acoustic noise for EPI based sequences. In the second part, methods are developed to reduce distortions in EPI acquisitions whilst maintaining the same acquisition speed. The novel method reduces acoustic noise via prolonging the blipped Phase-Encoding (PE) and multiband encoding gradients. Additionally, data points are sampled throughout the whole Readout (RO) meaning k-space is acquired in a non-Cartesian way. However, the deviations from a Cartesian trajectory are small enough so that Cartesian reconstruction methods can still be employed. The reconstruction time is thereby kept in a clinical acceptable time frame of less than one second. The novel method is furthermore combined with two well-known techniques to reduce acoustic noise. Firstly, a sinusoidal RO gradient is used which also has the advantage of tuning the sequence frequency spectrum to a local minimum of the gradient system [8]. Secondly, RO segmentation is employed to reduce gradient amplitude and slew-rate [9, 10]. Through the combination of these methods the acoustic noise can be decreased by 20 dB. Distortions can be reduced by using RO segmentation [11]. This comes at a cost of increased measurement time. To reduce measurement time, a novel way of under-sampling k-space which considers the variation between segments along the RO direction is introduced. This enables a measurement time reduction by roughly a factor of 2 with no impact on image quality. Interleaved EPI is another way to reduce distortions [12]. In interleaved EPI, k-space is acquired in multiple shots along the PE direction. This work also demonstrates an additional novel technique for under-sampling k-space in 3D EPI while interleaving along both PE directions. This enables the application of Compressed Sensing (CS) [13] in EPI for the first time. For anatomical imaging typically gradient echo sequences with undersampling factors of up to 12 are used. In comparison, this novel method (combining EPI with CS), yields acceleration factors of up to 131.6 at a comparable image quality.