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Purpose: The delay alternating with nutation for tailored excitation (DANTE)–sampling perfection with application‐optimized contrasts (SPACE) sequence facilitates 3D intracranial vessel wall imaging with simultaneous suppression of blood and CSF. However, the achieved image contrast depends closely on the selected sequence parameters, and the clinical use of the sequence is limited in vivo by observed signal variations in the vessel wall, CSF, and blood. This paper introduces a comprehensive DANTE‐SPACE simulation framework, with the aim of providing a better understanding of the underlying contrast mechanisms and facilitating improved parameter selection and contrast optimization. Methods: An extended phase graph formalism was developed for efficient spin ensemble simulation of the DANTE‐SPACE sequence. Physiological processes such as pulsatile flow velocity variation, varying flow directions, intravoxel velocity variation, diffusion, and B1+$$ {\mathrm{B}}_1^{+} $$ effects were included in the framework to represent the mechanisms behind the achieved signal levels accurately. Results: Intravoxel velocity variation improved temporal stability and robustness against small velocity changes. Time‐varying pulsatile velocity variation affected CSF simulations, introducing periods of near‐zero velocity and partial rephasing. Inclusion of diffusion effects was found to substantially reduce the CSF signal. Blood flow trajectory variations had minor effects, but B1+$$ {\mathrm{B}}_1^{+} $$ differences along the trajectory reduced DANTE efficiency in low‐B1+$$ {\mathrm{B}}_1^{+} $$ areas. Introducing low‐velocity pulsatility of both CSF and vessel wall helped explain the in vivo observed signal heterogeneity in both tissue types. Conclusion: The presented simulation framework facilitates a more comprehensive optimization of DANTE‐SPACE sequence parameters. Furthermore, the simulation framework helps to explain observed contrasts in acquired data. [ABSTRACT FROM AUTHOR]

Purpose: Neurovascular MRI suffers from a rapid drop in B1+ into the neck when using transmit head coils at 7 T. One solution to improving B1+ magnitude in the major feeding arteries in the neck is to use custom RF shims on parallel‐transmit head coils. However, calculating such shims requires robust multichannel B1+ maps in both the head and the neck, which is challenging due to low RF penetration into the neck, limited dynamic range of multichannel B1+ mapping techniques, and B0 sensitivity. We therefore sought a robust, large‐dynamic‐range, parallel‐transmit field mapping protocol and tested whether RF shimming can improve carotid artery B1+ magnitude in practice. Methods: A pipeline is presented that combines B1+ mapping data acquired using circularly polarized (CP) and CP2‐mode RF shims at multiple voltages. The pipeline was evaluated by comparing the predicted and measured B1+ for multiple random transmit shims, and by assessing the ability of RF shimming to increase B1+ in the carotid arteries. Results: The proposed method achieved good agreement between predicted and measured B1+ in both the head and the neck. The B1+ magnitude in the carotid arteries can be increased by 43% using tailored RF shims or by 37% using universal RF shims, while also improving the RF homogeneity compared with CP mode. Conclusion: B1+ in the neck can be increased using RF shims calculated from multichannel B1+ maps in both the head and the neck. This can be achieved using universal phase‐only RF shims, facilitating easy implementation in existing sequences. [ABSTRACT FROM AUTHOR]

Complex engineered systems are often equipped with suites of sensors and ancillary devices that monitor their performance and maintenance needs. MRI scanners are no different in this regard. Some of the ancillary devices available to support MRI equipment, the ones of particular interest here, have the distinction of actually participating in the image acquisition process itself. Most commonly, such devices are used to monitor physiological motion or variations in the scanner's imaging fields, allowing the imaging and/or reconstruction process to adapt as imaging conditions change. "Classic" examples include electrocardiography (ECG) leads and respiratory bellows to monitor cardiac and respiratory motion, which have been standard equipment in scan rooms since the early days of MRI. Since then, many additional sensors and devices have been proposed to support MRI acquisitions. The main physical properties that they measure may be primarily "mechanical" (eg acceleration, speed, and torque), "acoustic" (sound and ultrasound), "optical" (light and infrared), or "electromagnetic" in nature. A review of these ancillary devices, as currently available in clinical and research settings, is presented here. In our opinion, these devices are not in competition with each other: as long as they provide useful and unique information, do not interfere with each other and are not prohibitively cumbersome to use, they might find their proper place in future suites of sensors. In time, MRI acquisitions will likely include a plurality of complementary signals. A little like the microbiome that provides genetic diversity to organisms, these devices can provide signal diversity to MRI acquisitions and enrich measurements. Machine‐learning (ML) algorithms are well suited at combining diverse input signals toward coherent outputs, and they could make use of all such information toward improved MRI capabilities. Evidence Level: 2 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

Purpose: To shorten the acquisition time of magnetization‐prepared absolute transmit field (B1+) mapping known as presaturation TurboFLASH, or satTFL, to enable single breath‐hold whole‐heart 3D B1+ mapping. Methods: SatTFL is modified to remove the delay between the reference and prepared images (typically 5 T1), with matching transmit configurations for excitation and preparation RF pulses. The new method, called Sandwich, is evaluated as a 3D sequence, measuring whole‐brain and gated whole‐heart B1+ maps in a single breath‐hold. We evaluate the sensitivity to B1+ and T1 using numerical Bloch, extended phase graph, and Monte Carlo simulations. Phantom and in vivo images were acquired in both the brain and heart using an 8‐channel transmit 7 Tesla MRI system to support the simulations. A segmented satTFL with a short readout train was used as a reference. Results: The method significantly reduces acquisition times of 3D measurements from 360 s to 20 s, in the brain, while simultaneously reducing bias in the measured B1+ due to T1 and magnetization history. The mean coefficient of variation was reduced by 81% for T1s of 0.5–3 s compared to conventional satTFL. In vivo, the reproducibility coefficient for flip angles in the range 0–130° was 4.5° for satTFL and 4.7° for our scheme, significantly smaller than for a short TR satTFL sequence, which was 12°. The 3D sequence measured B1+ maps of the whole thorax in 26 heartbeats. Conclusion: Our adaptations enable faster B1+ mapping, with minimal T1 sensitivity and lower sensitivity to magnetization history, enabling single breath‐hold whole‐heart absolute B1+ mapping. [ABSTRACT FROM AUTHOR]

Aims  Altered left atrial (LA) blood flow characteristics account for an increase in cardioembolic stroke risk in atrial fibrillation (AF). Here, we aimed to assess whether exposure to stroke risk factors is sufficient to alter LA blood flow even in the presence of sinus rhythm (SR). Methods and results  We investigated 95 individuals: 37 patients with persistent AF, who were studied before and after cardioversion [Group 1; median CHA2DS2-VASc = 2.0 (1.5–3.5)]; 35 individuals with no history of AF but similar stroke risk to Group 1 [Group 2; median CHA2DS2-VASc = 3.0 (2.0–4.0)]; and 23 low-risk individuals in SR [Group 3; median CHA2DS2-VASc = 0.0 (0.0–0.0)]. Cardiac function and LA flow characteristics were evaluated using cardiac magnetic resonance. Before cardioversion, Group 1 displayed impaired left ventricular (LV) and LA function, reduced LA flow velocities and vorticity, and a higher normalized vortex volume (all P  < 0.001 vs. Groups 2 and 3). After restoration of SR at ≥4-week post-cardioversion, LV systolic function and LA flow parameters improved significantly (all P  < 0.001 vs. pre-cardioversion) and were no longer different from those in Group 2. However, in the presence of SR, LA flow peak and mean velocity, and vorticity were lower in Groups 1 and 2 vs. Group 3 (all P  < 0.01), and were associated with impaired LA emptying fraction (LAEF) and LV diastolic dysfunction. Conclusion  Patients at moderate-to-high stroke risk display altered LA flow characteristics in SR in association with an LA myopathic phenotype and LV diastolic dysfunction, regardless of a history of AF. [ABSTRACT FROM AUTHOR]

Long acquisition times due to intrinsically low signal‐to‐noise ratio and the need for highly homogeneous B0 field make MRS particularly susceptible to motion or scanner instability compared with MRI. Motion‐induced changes in both localization and shimming (ie B0 homogeneity) degrade MRS data quality. To mitigate the effects of motion three approaches can be employed: (1) subject immobilization, (2) retrospective correction, and (3) prospective real‐time correction using internal and/or external tracking methods. Prospective real‐time correction methods can simultaneously update localization and the B0 field to improve MRS data quality. While localization errors can be corrected with both internal (navigators) and external (optical camera, NMR probes) tracking methods, the B0 field correction requires internal navigator methods to measure the B0 field inside the imaged volume and the possibility to update the scanner shim hardware in real time. Internal and external tracking can rapidly update the MRS localization with submillimeter and subdegree precision, while scanner frequency and first‐order shims of scanner hardware can be updated by internal methods every sequence repetition. These approaches are most well developed for neuroimaging, for which rigid transformation is primarily applicable. Real‐time correction greatly improves the stability of MRS acquisition and quantification, as shown in clinical studies on subjects prone to motion, including children and patients with movement disorders, enabling robust measurement of metabolite signals including those with low concentrations, such as gamma‐aminobutyric acid and glutathione. Thus, motion correction is recommended for MRS users and calls for tighter integration and wider availability of such methods by MR scanner manufacturers. [ABSTRACT FROM AUTHOR]

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

Purpose: To assess whether artifacts in multi‐slice multi‐echo spin echo neck imaging, thought to be caused by brief motion events such as swallowing, can be corrected by reacquiring corrupted central k‐space data and estimating the remainder with parallel imaging. Methods: A single phase‐encode line (ky = 0, phase‐encode direction anteroposterior) navigator echo was used to identify motion‐corrupted data and guide the online reacquisition. If motion corruption was detected in the 7 central k‐space lines, they were replaced with reacquired data. Subsequently, GRAPPA reconstruction was trained on the updated central portion of k‐space and then used to estimate the remaining motion‐corrupted k‐space data from surrounding uncorrupted data. Similar compressed sensing‐based approaches have been used previously to compensate for respiration in cardiac imaging. The g‐factor noise amplification was calculated for the parallel imaging reconstruction of data acquired with a 10‐channel neck coil. The method was assessed in scans with 9 volunteers and 12 patients. Results: The g‐factor analysis showed that GRAPPA reconstruction of 2 adjacent motion‐corrupted lines causes high noise amplification; therefore, the number of 2‐line estimations should be limited. In volunteer scans, median ghosting reduction of 24% was achieved with 2 adjacent motion‐corrupted lines correction, and image quality was improved in 2 patient scans that had motion corruption close to the center of k‐space. Conclusion: Motion‐corrupted echo‐trains can be identified with a navigator echo. Combined reacquisition and parallel imaging estimation reduced motion artifacts in multi‐slice MESE when there were brief motion events, especially when motion corruption was close to the center of k‐space. [ABSTRACT FROM AUTHOR]