Simultaneous Multislice Echo Planar Imaging Research Articles

Reproducibility and Repeatability of Intravoxel Incoherent Motion MRI Acquisition Methods in Liver.

Intravoxel incoherent motion (IVIM) diffusion weighted MRI (DWI) has potential for evaluating hepatic fibrosis but image acquisition technique influence on diffusion parameter estimation bears investigation. To minimize variability and maximize repeatably in abdominal DWI in terms of IVIM parameter estimates. Prospective test-retest and image quality comparison. Healthy volunteers (3F/7M, 29.9 ± 12.9 years) and Family Study subjects (18F/12M, 51.7 ± 16.7 years), without and with liver steatosis. Abdominal single-shot echo-planar imaging (EPI) and simultaneous multi-slice (SMS) DWI sequences with respiratory triggering (RT), breath-holding (BH), and navigator echo (NE) at 3 Tesla. SMS-BH, EPI-NE, and SMS-RT data from twice-scanned healthy volunteers were analyzed using 6 × b-values (0-800 s⋅mm-2 ) and lower (LO) and higher (HI) b-value ranges. Family Study subjects were scanned using SMS and standard EPI sequences. The biexponential IVIM model was used to estimate fast-diffusion coefficient (Df ), fraction of fast diffusion (f), and slow-diffusion coefficient (Ds ). Scan time, estimated signal-to-noise ratio (eSNR), eSNR per acquisition, and distortion ratio were compared. Coefficients of variation (CoV) and Bland Altman analyses were performed for test-retest repeatability. Interclass correlation coefficient (ICC) assessed interobserver agreement with P < 0.05 deemed significant. Within-subject CoVs among volunteers (N = 10) for f and Ds were lowest in EPI-NE-LO (11.6%) and SMS-RT-HI (11.1%). Inter-observer ICCs for f and Ds were highest for EPI-NE-LO (0.63) and SMS-RT-LO (0.76). Df could not be estimated for most subjects. Estimated eSNR (EPI = 21.9, SMS = 4.7) and eSNR time (EPI = 6.7, SMS = 16.6) were greater for SMS, with less distortion in the liver region (DR-PE: EPI = 23.6, SMS = 13.1). Simultaneous multislice acquisitions had significantly less variability and higher ICCs of Ds , higher eSNR, less distortion, and reduced scan time compared to EPI. 2 TECHNICAL EFFICACY: Stage 1.

3D motion strategy for online volumetric thermometry using simultaneous multi-slice EPI at 1.5T: an evaluation study

Purpose In presence of respiratory motion, temperature mapping is altered by in-plane and through-plane displacements between successive acquisitions together with periodic phase variations. Fast 2D Echo Planar Imaging (EPI) sequence can accommodate intra-scan motion, but limited volume coverage and inter-scan motion remain a challenge during free-breathing acquisition since position offsets can arise between the different slices. Method To address this limitation, we evaluated a 2D simultaneous multi-slice EPI sequence with multiband (MB) acceleration during radiofrequency ablation on a mobile gel and in the liver of a volunteer (no heating). The sequence was evaluated in terms of resulting inter-scan motion, temperature uncertainty and elevation, potential false-positive heating and repeatability. Lastly, to account for potential through-plane motion, a 3D motion compensation pipeline was implemented and evaluated. Results In-plane motion was compensated whatever the MB factor and temperature distribution was found in agreement during both the heating and cooling periods. No obvious false-positive temperature was observed under the conditions being investigated. Repeatability of measurements results in a 95% uncertainty below 2 °C for MB1 and MB2. Uncertainty up to 4.5 °C was reported with MB3 together with the presence of aliasing artifacts. Lastly, fast simultaneous multi-slice EPI combined with 3D motion compensation reduce residual out-of-plane motion. Conclusion Volumetric temperature imaging (12 slices/700 ms) could be performed with 2 °C accuracy or less, and offer tradeoffs in acquisition time or volume coverage. Such a strategy is expected to increase procedure safety by monitoring large volumes more rapidly for MR-guided thermotherapy on mobile organs.

Diffusion-weighted Imaging of the Abdomen during a Single Breath-hold Using Simultaneous-multislice Echo-planar Imaging.

This multi-scanner study aimed to investigate the validity of single breath-hold (BH) diffusion-weighted imaging (DWI) using simultaneous-multislice (SMS) echo-planar imaging in multiple abdominal organs to enable faster acquisition and reliable quantification of apparent diffusion coefficient (ADC). SNR, geometric distortion (GD), and ADC in a phantom; the ADC in the liver, renal cortex, paraspinal muscle, spleen, and pancreas; and the signal intensity ratio of the portal vein-to-muscle (SIRPV-M) in healthy volunteers were compared between BH- and respiratory-triggered (RT) DWI with b-values of 0 and 800 s/mm2 in two different MRI scanners. The phantom study showed that the SNR of BH-DWI was significantly lower than that of the RT-DWI (P < 0.05 for both scanners), whereas the GD and ADC of BH-DWI did not differ significantly from those of the RT-DWI (P = 0.09-0.60). In the volunteer study, the scan times were 23 seconds for BH-DWI and 184±33 seconds for RT-DWI, respectively. The ADC of the liver in BH-DWI was significantly lower than that in RT-DWI (P < 0.05 for both scanners), whereas there were no significant differences in the ADCs of the renal cortex, paraspinal muscle, spleen, or pancreas between BH-DWI and RT-DWI (P = 0.07-0.86). The SIRPV-M in BH-DWI was significantly smaller than in RT-DWI (P < 0.05 for both scanners). The proposed method enables the acquisition of abdominal diffusion-weighted images in a single BH.

Segmented simultaneous multi-slice diffusion-weighted imaging with navigated 3D rigid motion correction.

To improve the robustness of diffusion-weighted imaging (DWI) data acquired with segmented simultaneous multi-slice (SMS) echo-planar imaging (EPI) against in-plane and through-plane rigid motion. The proposed algorithm incorporates a 3D rigid motion correction and wavelet denoising into the image reconstruction of segmented SMS-EPI diffusion data. Low-resolution navigators are used to estimate shot-specific diffusion phase corruptions and 3D rigid motion parameters through SMS-to-volume registration. The shot-wise rigid motion and phase parameters are integrated into a SENSE-based full-volume reconstruction for each diffusion direction. The algorithm is compared to a navigated SMS reconstruction without gross motion correction in simulations and in vivo studies with four-fold interleaved 3-SMS diffusion tensor acquisitions. Simulations demonstrate high fidelity was achieved in the SMS-to-volume registration, with submillimeter registration errors and improved image reconstruction quality. In vivo experiments validate successful artifact reduction in 3D motion-compromised in vivo scans with a temporal motion resolution of approximately 0.3 s. This work demonstrates the feasibility of retrospective 3D rigid motion correction from shot navigators for segmented SMS DWI.

Real-Time Resting-State Functional Magnetic Resonance Imaging Using Averaged Sliding Windows with Partial Correlations and Regression of Confounding Signals.

Background/Introduction: There is considerable interest in using real-time functional magnetic resonance imaging (fMRI) for monitoring functional connectivity dynamics. To date, the majority of real-time resting-state fMRI studies have examined a limited number of brain regions. This is, in part, due to the computational demands of traditional seed- and independent component analysis-based methods, in particular when using increasingly available high-speed fMRI methods. Methods: This study describes a computationally efficient, real-time, seed-based, resting-state fMRI analysis pipeline using moving averaged sliding-windows (ASW) with partial correlations and regression of motion parameters and signals from white matter and cerebrospinal fluid. Results: Analytical and numerical analyses of ASW correlation and sliding-window regression as a function of window width show selectable bandpass filter characteristics and effective suppression of artifactual correlations resulting from signal drifts and transients. The analysis pipeline is compatible with multislab echo-volumar imaging and simultaneous multislice echo-planar imaging with repetition times as short as 136 msec. High-speed, resting-state fMRI data in healthy controls demonstrate the effectiveness of this approach for minimizing artifactual correlations in white and gray matter, which was comparable to conventional regression across the entire scan. Integrating sliding-window averaging (width: W1) within a second-level sliding-window (width: W2) enabled monitoring of intra- and internetwork correlation dynamics of up to 12 resting-state networks with bandpass filter characteristics determined by the first-level sliding-window and temporal resolution W1 + W2. Conclusions: The computational performance and confound tolerance make this seed-based, resting-state fMRI approach suitable for real-time monitoring of data quality and resting-state connectivity dynamics in neuroscience and clinical research studies. Impact statement Using averaged sliding-windows for seed-based correlation and regression of confounding signals provides a powerful model-free approach to increase tolerance to artifactual signal transients in resting-state analysis. The algorithmic efficiency of this sliding-window approach enables real-time, seed-based, resting-state functional magnetic resonance imaging (fMRI) of multiple networks with computation of connectivity matrices and online monitoring of data quality. Integration of a second-level sliding-window enables mapping of resting-state connectivity dynamics. Sensitivity and tolerance to confounding signals compare favorably with conventional correlation and confound regression across the entire scan. This methodological advance has the potential to enhance the clinical utility of resting-state fMRI and facilitate neuroscience applications.

Improved autoregressive model for correction of noise serial correlation in fast fMRI.

PurposeIn rapidly acquired functional MRI (fast fMRI) data, the noise serial correlations (SC) can produce problematically overestimated T‐statistics which lead to invalid statistical inferences. This study aims to evaluate and improve the accuracy of high‐order autoregressive model (AR(p), where p is the model order) based prewhitening method in the SC correction.MethodsFast fMRI images were acquired at rest (null data) using a multiband simultaneous multi‐slice echo planar imaging pulse sequence with repetition time (TR) = 300 and 500 ms. The SC effect in the fast fMRI data was corrected using the prewhitening method based on two AR(p) models: (1) the conventional model (fixed AR(p)) which preselects a constant p for all the image voxels; (2) an improved model (ARAICc) that employs the corrected Akaike information criterion voxel‐wise to automatically select the model orders for each voxel. To evaluate accuracy of SC correction, false positive characteristics were measured by assuming the presence of block and event‐related tasks in the null data without image smoothing. The performance of prewhitening was also examined in smoothed images by adding pseudo task fMRI signals into the null data and comparing the detected to simulated activations (ground truth).ResultsThe measured false positive characteristics agreed well with the theoretical curve when using the ARAICc, and the activation maps in the smoothed data matched the ground truth. The ARAICc showed improved performance than the fixed AR(p) method.ConclusionThe ARAICc can effectively remove noise SC, and accurate statistical analysis results can be obtained with the ARAICc correction in fast fMRI.

Extraction of the cardiac waveform from simultaneous multislice fMRI data using slice sorted averaging and a deep learning reconstruction filter

Cardiac signal contamination has long confounded the analysis of blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI). Cardiac pulsation results in significant BOLD signal changes, especially in and around blood vessels. Until the advent of simultaneous multislice echo-planar imaging (EPI) acquisition, the time resolution of whole brain EPI was insufficient to avoid cardiac aliasing (and acquisitions with repetition times (TRs) under 400–500 ms are still uncommon). As a result, direct detection and removal of the cardiac signal with spectral filters is generally not possible. Modelling methods have been developed to mitigate cardiac contamination, and recently developed techniques permit the visualization of cardiac signal propagation through the brain in undersampled data (e.g., TRs > 1s), which is useful in its own right for finding blood vessels. However, both of these techniques require data from which to estimate cardiac phase, which is generally not available for the data in many large databases of existing imaging data, and even now is not routinely recorded in many fMRI experiments.Here we present a method to estimate the cardiac waveform directly from a multislice fMRI dataset, without additional physiological measurements, such as plethysmograms. The pervasive spatial extent and temporal structure of the cardiac contamination signal across the brain offers an opportunity to exploit the nature of multislice imaging to extract this signal from the fMRI data itself. While any particular slice is recorded at the TR of the imaging experiment, slices are recorded much more quickly – typically from 10 to 20 Hz - sufficiently fast to fully sample the cardiac signal. Using the fairly permissive assumptions that the cardiac signal is a) pseudoperiodic b) somewhat coherent within any given slice, and c) is similarly shaped throughout the brain, we can extract a good estimate of the cardiac phase as a function of time from fMRI data alone. If we make further assumptions about the shape and consistency of cardiac waveforms, we can develop a deep learning filter to greatly improve our estimate of the cardiac waveform.

Simultaneous Multislice Echo Planar Imaging for Accelerated Diffusion-Weighted Imaging of Malignant and Benign Breast Lesions.

Comparison of the diagnostic value of simultaneous multislice (SMS) accelerated diffusion-weighted echo planar imaging (EPI) of malignant and benign lesions of the breast compared with a reference EPI sequence. The study was approved by the institutional ethics committee. Sixty-eight patients were examined with a diffusion-weighted EPI (reference EPI; TE = 54 milliseconds; TR = 9000 milliseconds; TA, 3:27 minutes) and a diffusion-weighted SMS accelerated EPI (SMS EPI; acceleration factor 2; TE = 58 milliseconds; TR = 4300 milliseconds; TA, 1:53 minutes) in addition to the standard magnetic resonance imaging (MRI) protocol. Further acquisition parameters were as follows: 3 T MAGNETOM Skyra (Siemens Healthcare, Erlangen, Germany), 2.5-mm isotropic resolution, field of view = 185 to 190 × 350 mm, 62 slices, b = 50 and 800 s/mm with 1 and 4 averages, respectively. A dedicated 16-channel bilateral breast coil was used for imaging. Image quality was evaluated with respect to the presence of artifacts, signal voids, and quality of fat suppression. These parameters were rated using a 5-point Likert scale (1 = very strong to 5 = negligible). The apparent diffusion coefficient (ADC) was measured in 72 focal lesions (46 breast carcinomas and 26 benign lesions), and the diagnostic value of the 2 datasets was statistically evaluated and compared. The evaluation was performed a second time excluding cysts. Artifacts and signal voids were negligible in both sequences (mean on Likert scale for reference EPI 4.68 vs SMS EPI 4.65, P = 0.52, and mean on Likert scale for reference EPI 4.85 vs SMS EPI 4.77, P = 0.14). Fat suppression was significantly better in SMS EPI (mean on Likert scale 3.28 vs 2.97, P < 0.001, Pearson r = 0.49). For benign lesions, the mean ADC in both EPI sequences was 1.86 · 10 mm/s. For malignant lesions, a mean ADC of 0.90 · 10 mm/s for the reference EPI and 0.89 · 10 mm/s for the SMS EPI was found. No significant difference between the EPI sequences was observed for ADC values (P = 0.75) and for the area under the curve (SMS, 0.985; no SMS, 0.975). The cutoff for differentiation of benign and malignant lesions was at ADC = 1.42 · 10 mm/s for SMS EPI (sensitivity, 1; specificity, 0.88) and at 1.23 · 10 mm/s for the reference EPI (sensitivity, 1; specificity, 0.92). Excluding the cysts, the cutoff for differentiation of benign and malignant lesions was at ADC = 1.11 · 10 mm/s for SMS EPI (sensitivity, 0.89; specificity, 0.93) and at 1.23 · 10 mm/s for the reference EPI (sensitivity, 1; specificity, 0.87). Our data indicate that SMS acceleration can be used for diffusion imaging in breast MRI in clinical practice. Simultaneous multislice EPI achieved the same diagnostic accuracy in breast MRI, but in a substantially reduced scan time.

The potential of MR-Encephalography for BCI/Neurofeedback applications with high temporal resolution

Real-time functional magnetic resonance imaging (rt-fMRI) enables the update of various brain-activity measures during an ongoing experiment as soon as a new brain volume is acquired. However, the recorded Blood-oxygen-level dependent (BOLD) signal also contains physiological artifacts such as breathing and heartbeat, which potentially cause misleading false positive effects especially problematic in brain-computer interface (BCI) and neurofeedback (NF) setups. The low temporal resolution of echo planar imaging (EPI) sequences (which is in the range of seconds) prevents a proper separation of these artifacts from the BOLD signal. MR-Encephalography (MREG) has been shown to provide the high temporal resolution required to unalias and correct for physiological fluctuations and leads to increased specificity and sensitivity for mapping task-based activation and functional connectivity as well as for detecting dynamic changes in connectivity over time. By comparing a simultaneous multislice echo planar imaging (SMS-EPI) sequence and an MREG sequence using the same nominal spatial resolution in an offline analysis for three different experimental fMRI paradigms (perception of house and face stimuli, motor imagery, Stroop task), the potential of this novel technique for future BCI and NF applications was investigated. First, adapted general linear model pre-whitening which accounts for the high temporal resolution in MREG was implemented to calculate proper statistical results and be able to compare these with the SMS-EPI sequence. Furthermore, the respiration- and cardiac pulsation-related signals were successfully separated from the MREG signal using independent component analysis which were then included as regressors for a GLM analysis. Only the MREG sequence allowed to clearly separate cardiac pulsation and respiration components from the signal time course. It could be shown that these components highly correlate with the recorded respiration and cardiac pulsation signals using a respiratory belt and fingertip pulse plethysmograph. Temporal signal-to-noise ratios of SMS-EPI and MREG were comparable. Functional connectivity analysis using partial correlation showed a reduced standard error in MREG compared to SMS-EPI. Also, direct time course comparisons by down-sampling the MREG signal to the SMS-EPI temporal resolution showed lower variance in MREG. In general, we show that the higher temporal resolution is beneficial for fMRI time course modeling and this aspect can be exploited in offline application but also, is especially attractive, for real-time BCI and NF applications.

Advantages of short repetition time resting-state functional MRI enabled by simultaneous multi-slice imaging

BackgroundRecent advancements in simultaneous multi-slice (SMS) imaging techniques have enabled whole-brain resting-state fMRI (rs-fMRI) scanning at sub-second temporal resolution, providing spectral ranges much wider than the typically used range of 0.01–0.1 Hz. However, the advantages of this accelerated acquisition for rs-fMRI have not been evaluated. New methodIn this study, we used SMS Echo Planar Imaging (EPI) to probe whole-brain functional connectivity with a short repetition time (TR = 350 ms) and compared it with standard EPI with a longer TR of 2000 ms. We determined the effect of scan length and investigated the temporal filtration strategies that optimize results based on metrics of signal-noise separation and test-retest reliability using both seed-based and independent component analysis (ICA). ResultsWe found that use of either the entire frequency range of 0.01–1.4 Hz or the entire frequency range with the exclusion of typical cardiac and respiratory frequency values tended to provide the best functional connectivity maps. Comparison with existing methodsWe found that the SMS-acquired rs-fMRI scans had improved the signal-noise separation, while preserving the same level of test-retest reliability compared to conventional EPI, and enabled the detection of reliable functional connectivity networks with scan times as short as 3 min. ConclusionsOur findings suggest that whole-brain rs-fMRI studies may benefit from the increased temporal resolution enabled by the SMS-EPI acquisition, leading to drastic scan time reductions, which in turn should enable the more widespread use of rs-fMRI in clinical research protocols.

High temporal resolution motion estimation using a self-navigated simultaneous multi-slice echo planar imaging acquisition.

Subject motion is known to produce spurious covariance among time-series in functional connectivity that has been reported to induce distance-dependent spurious correlations. To present a feasibility study for applying the extended Kalman filter (EKF) framework for high temporal resolution motion correction of resting state functional MRI (rs-fMRI) series using each simultaneous multi-slice (SMS) echo planar imaging (EPI) shot as its own navigator. Prospective feasibility study. Three human volunteers. 3T GE DISCOVERY MR750 scanner using a 32-channel head coil. Simultaneous multi-slice rs-fMRI sequence with repetition time (TR)/echo time (TE) = 800/30 ms, and SMS factor 6. Motion estimates were computed using two techniques: a conventional rigid-body volume-wise registration; and a high-temporal resolution motion estimation rigid-body approach. The reference image was resampled using the estimates obtained from both approaches and the difference between these predicted volumes and the original moving series was summarized using the normalized mean squared error (NMSE). Direct comparison of NMSE values. High-temporal motion estimation was always superior to volume-wise motion estimation for the sample presented. For staged continuous rotations, the NMSE using high-temporal resolution motion estimates ranged between [0.130, 0.150] for the first volunteer (in-plane rotations), between [0.060, 0.068] for the second volunteer (in-plane rotations), and between [0.063, 0.080] for the third volunteer (through-plane rotations). These values went up to [0.384, 0.464]; [0.136, 0.179]; and [0.080, 0.096], respectively, when using volume-wise motion estimates. Accurate high-temporal rigid-body motion estimates can be obtained for rs-fMRI taking advantage of simultaneous multi-slice EPI sub-TR shots. 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

Dynamic 2D self-phase-map Nyquist ghost correction for simultaneous multi-slice echo planar imaging.

To develop a reconstruction pipeline that intrinsically accounts for both simultaneous multislice echo planar imaging (SMS-EPI) reconstruction and dynamic slice-specific Nyquist ghosting correction in time-series data. After 1D slice-group average phase correction, the separate polarity (i.e., even and odd echoes) SMS-EPI data were unaliased by slice GeneRalized Autocalibrating Partial Parallel Acquisition. Both the slice-unaliased even and odd echoes were jointly reconstructed using a model-based framework, extended for SMS-EPI reconstruction that estimates a 2D self-phase map, corrects dynamic slice-specific phase errors, and combines data from all coils and echoes to obtain the final images. The percentage ghost-to-signal ratios (%GSRs) and its temporal variations for MB3Ry 2 with a field of view/4 shift in a human brain obtained by the proposed dynamic 2D and standard 1D phase corrections were 1.37 ± 0.11 and 2.66 ± 0.16, respectively. Even with a large regularization parameter λ applied in the proposed reconstruction, the smoothing effect in fMRI activation maps was comparable to a very small Gaussian kernel size 1 × 1 × 1 mm3 . The proposed reconstruction pipeline reduced slice-specific phase errors in SMS-EPI, resulting in reduction of GSR. It is applicable for functional MRI studies because the smoothing effect caused by the regularization parameter selection can be minimal in a blood-oxygen-level-dependent activation map.

Reducing task-based fMRI scanning time using simultaneous multislice echo planar imaging.

To maintain alertness and to remain motionless during scanning represent a substantial challenge for patients/subjects involved in both clinical and research functional magnetic resonance imaging (fMRI) examinations. Therefore, availability and application of new data acquisition protocols allowing the shortening of scan time without compromising the data quality and statistical power are of major importance. Higher order category-selective visual cortical areas were identified individually, and rapid event-related fMRI design was used to compare three different sampling rates (TR = 2000, 1000, and 410ms, using state-of-the-art simultaneous multislice imaging) and four different scanning lengths to match the statistical power of the traditional scanning methods to high sampling-rate design. The results revealed that ~ 4min of the scan time with 1Hz (TR = 1000ms) sampling rate and ~ 2min scanning at ~ 2.5Hz (TR = 410ms) sampling rate provide similar localization sensitivity and selectivity to that obtained with 11-min session at conventional, 0.5Hz (TR = 2000ms) sampling rate. Our findings suggest that task-based fMRI examination of clinical population prone to distress such as presurgical mapping experiments might substantially benefit from the reduced (20-40%) scanning time that can be achieved by the application of simultaneous multislice sequences.

Simultaneous Multislice Resting-State Functional Magnetic Resonance Imaging at 3 Tesla: Slice-Acceleration-Related Biases in Physiological Effects.

Simultaneous multislice echo-planar imaging (SMS-EPI) can enhance the spatiotemporal resolution of resting-state functional MRI (rs-fMRI) by encoding and simultaneously imaging "groups" of slices. However, phenomena, including respiration, cardiac pulsatility, respiration volume per time (RVT), and cardiac rate variation (CRV), referred to as "physiological processes," impact SMS-EPI rs-fMRI in a manner that is yet to be well characterized. In particular, physiological noise may incur aliasing and introduce spurious signals from one slice into another within the "slice group" in rs-fMRI data, resulting in a deleterious effect on resting-state functional connectivity MRI (rs-fcMRI) maps. In the present work, we aimed to quantitatively compare the effects of physiological noise on regular EPI and SMS-EPI in terms of rs-fMRI data and resulting functional connectivity measurements. We compare SMS-EPI and regular EPI data acquired from 11 healthy young adults with matching parameters. The physiological noise characteristics were compared between the two data sets through different combinations of physiological regression steps. We observed that the physiological noise characteristics differed between SMS-EPI and regular EPI, with cardiac pulsatility contributing more to noise in regular EPI data but low-frequency heart rate variability contributing more to SMS-EPI. In addition, a significant slice-group bias was observed in the functional connectivity density maps derived from SMS-EPI data. We conclude that making appropriate corrections for physiological noise is likely more important for SMS-EPI than for regular EPI acquisitions.

Using multi-echo simultaneous multi-slice (SMS) EPI to improve functional MRI of the subcortical nuclei of the basal ganglia at ultra-high field (7T)

The nuclei of the basal ganglia pose a special problem for functional MRI, especially at ultra-high field, because T2* variations between different regions result in suboptimal BOLD sensitivity when using gradient-echo echo-planar imaging (EPI). Specifically, the iron-rich lentiform nucleus of the basal ganglia, including the putamen and globus pallidus, suffers from substantial signal loss when imaging is performed using conventional single-echo EPI with echo times optimized for the cortex. Multi-echo EPI acquires several echoes at different echo times for every imaging slice, allowing images to be reconstructed with a weighting of echo times that is optimized individually for each voxel according to the underlying tissue or T2* properties. Here we show that multi-echo simultaneous multi-slice (SMS) EPI can improve functional activation of iron-rich subcortical regions while maintaining sensitivity within cortical areas. Functional imaging during a motor task known to elicit strong activations in the cortex and the subcortex (basal ganglia) was performed to compare the performance of multi-echo SMS EPI to single-echo SMS EPI. Notably within both the caudate nucleus and putamen of the basal ganglia, multi-echo SMS EPI yielded higher tSNR (an average 84% increase) and CNR (an average 58% increase), an approximate 3-fold increase in supra-threshold voxels, and higher t-values (an average 39% increase). The degree of improvement in the group level t-statistics was negatively correlated to the underlying T2* of the voxels, such that the shorter the T2*, as in the iron-rich nuclei of the basal ganglia, the higher the improvement of t-values in the activated region.

Influence of physiological noise on accelerated 2D and 3D resting state functional MRI data at 7 T.

Physiological noise often dominates the blood-oxygen level-dependent (BOLD) signal fluctuations in high-field functional MRI (fMRI) data. Therefore, to optimize fMRI protocols, it becomes crucial to investigate how physiological signal fluctuations impact various acquisition and reconstruction schemes at different acquisition speeds. In particular, further differences can arise between 2D and 3D fMRI acquisitions due to different encoding strategies, thereby impacting fMRI sensitivity in potentially significant ways. The amount of physiological noise to be removed from the BOLD fMRI signal acquired at 7 T was quantified for different sampling rates (repetition time from 3300 to 350 ms, acceleration 1 to 8) and techniques dedicated to fast fMRI (simultaneous multislice echo planar imaging [EPI] and 3D EPI). Resting state fMRI (rsfMRI) performances were evaluated using temporal signal-to-noise ratio (tSNR) and network characterization based on seed correlation and independent component analysis. Overall, acceleration enhanced tSNR and rsfMRI metrics. 3D EPI benefited the most from physiological noise removal at long repetition times. Differences between 2D and 3D encoding strategies disappeared at high acceleration factors (6- to 8-fold). After physiological noise correction, 2D- and 3D-accelerated sequences provide similar performances at high fields, both in terms of tSNR and resting state network identification and characterization. Magn Reson Med 78:888-896, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Functional Sensitivity of 2D Simultaneous Multi-Slice Echo-Planar Imaging: Effects of Acceleration on g-factor and Physiological Noise.

Accelerated data acquisition with simultaneous multi-slice (SMS) imaging for functional MRI studies leads to interacting and opposing effects that influence the sensitivity to blood oxygen level-dependent (BOLD) signal changes. Image signal to noise ratio (SNR) is decreased with higher SMS acceleration factors and shorter repetition times (TR) due to g-factor noise penalties and saturation of longitudinal magnetization. However, the lower image SNR is counteracted by greater statistical power from more samples per unit time and a higher temporal Nyquist frequency that allows for better removal of spurious non-BOLD high frequency signal content. This study investigated the dependence of the BOLD sensitivity on these main driving factors and their interaction, and provides a framework for evaluating optimal acceleration of SMS-EPI sequences. functional magnetic resonance imaging (fMRI) data from a scenes/objects visualization task was acquired in 10 healthy volunteers at a standard neuroscience resolution of 3 mm on a 3T MRI scanner. SMS factors 1, 2, 4, and 8 were used, spanning TRs of 2800 ms to 350 ms. Two data processing methods were used to equalize the number of samples over the SMS factors. BOLD sensitivity was assessed using g-factors maps, temporal SNR (tSNR), and t-score metrics. tSNR results show a dependence on SMS factor that is highly non-uniform over the brain, with outcomes driven by g-factor noise amplification and the presence of high frequency noise. The t-score metrics also show a high degree of spatial dependence: the lower g-factor noise area of V1 shows significant improvements at higher SMS factors; the moderate-level g-factor noise area of the parahippocampal place area shows only a trend of improvement; and the high g-factor noise area of the ventral-medial pre-frontal cortex shows a trend of declining t-scores at higher SMS factors. This spatial variability suggests that the optimal SMS factor for fMRI studies is region dependent. For task fMRI studies done with similar parameters as were used here (3T scanner, 32-channel RF head coil, whole brain coverage at 3 mm isotropic resolution), we recommend SMS accelerations of 4x (conservative) to 8x (aggressive) for most studies and a more conservative acceleration of 2x for studies interested in anterior midline regions.

Feasibility of accelerated simultaneous multislice diffusion-weighted MRI of the prostate.

To assess the feasibility of simultaneous multislice (SMS) single-shot echo-planar-imaging (EPI) for accelerated diffusion-weighted imaging (DWI) of the prostate. For phantom measurements a dedicated DWI phantom with different sucrose concentrations was used. In addition, 10 volunteers and 16 patients with suspected prostate cancer were examined for in vivo measurements. All examinations were performed with a 3T magnetic resonance imaging (MRI) system. A prototype simultaneous multislice EPI sequence (DW-EPISMS ; acquisition time 3:14 min) was acquired and compared to a single-shot EPI sequence (DW-EPISS ; acquisition time 6:12 min) serving as a standard of reference. Different image quality parameters of EPISMS were assessed qualitatively (overall image quality, anatomic differentiability, lesion conspicuity, image noise, distortion; two independent readers; 5-point Likert-scale [5 = excellent]) and quantitatively (ADC-values by calculating interclass correlation [ICC] and Bland-Altman limits of agreement [LoA] as measures for reproducibility) and compared to DW-EPISS . DW-EPISMS allowed for a substantially reduced acquisition time as compared to DW-EPISS (˜50%). Bland-Altman plots revealed robust measurement repeatability for DW-EPISMS in the phantom study. Overall image quality did not significantly differ between DW-EPISMS and DW-EPISS (b1500 images P = 0.5; ADC maps P = 0.7). Only in b1500 DW images was subjective image noise rated significantly higher in DW-EPISS than in DW-EPISMS (P = 0.006). Quantitative analysis of ADC-values revealed not significant differences between DW-EPISMS and DW-EPISS (P = 0.7) and high measures for reproducibility ICC ≥0.96. Simultaneous multislice DWI is feasible for accelerated prostate MRI allowing for a substantially reduced examination time with similar image quality and ADC-values as compared to a standard of reference DWI sequence. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1507-1515.

Estimating and eliminating the excitation errors in bipolar gradient composite excitations caused by radiofrequency-gradient delay: Example of bipolar spokes pulses in parallel transmission.

PurposeTo eliminate a slice‐position–dependent excitation error commonly observed in bipolar‐gradient composite excitations such as spokes pulses in parallel transmission.Theory and MethodsAn undesired timing delay between subpulses in the composite pulse and their bipolar slice‐selective gradient is hypothesized to cause the error. A mathematical model is presented here to relate this mismatch to an induced slice‐position–dependent phase difference between the subpulses. A new navigator method is proposed to measure the timing mismatch and eliminate the error. This is demonstrated at 7 Tesla with flip‐angle maps measured by a presaturation turbo‐flash sequence and in vivo images acquired by a simultaneous multislice/echo‐planar imaging (SMS‐EPI) sequence.ResultsError‐free flip‐angle maps were obtained in two ways: 1) by correcting the time delay directly and 2) by applying the corresponding slice‐position–dependent phase differences to the subpulses. This confirms the validity of the mathematical description. The radiofrequency (RF)‐gradient delay measured by the navigator method was of 6.3 μs, which agreed well with the estimate from flip‐angle maps at different delay times. By applying the timing correction, accurately excited EPI images were acquired with bipolar dual‐spokes SMS‐2 excitations.ConclusionAn effective correction is proposed to mitigate slice‐position–dependent errors in bipolar composite excitations caused by undesired RF‐gradient timing delays. Magn Reson Med 78:1883–1890, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

Simultaneous multi-slice (SMS) acquisition enhances the sensitivity of hemodynamic mapping using gas challenges.

Hemodynamic mapping using gas inhalation has received increasing interest in recent years. Cerebrovascular reactivity (CVR), which reflects the ability of the brain vasculature to dilate in response to a vasoactive stimulus, can be measured by CO2 inhalation with continuous acquisition of blood oxygen level-dependent (BOLD) magnetic resonance images. Cerebral blood volume (CBV) can be measured by O2 inhalation. These hemodynamic mapping methods are appealing because of their absence of gadolinium contrast agent, their ability to assess both baseline perfusion and vascular reserve, and their utility in calibrating the functional magnetic resonance imaging (fMRI) signal. However, like other functional and physiological indices, a major drawback of these measurements is their poor sensitivity and reliability. Simultaneous multi-slice echo planar imaging (SMS EPI) is a fast imaging technology that allows the excitation and acquisition of multiple two-dimensional slices simultaneously, and has been shown to enhance the sensitivity of several MRI applications. To our knowledge, the benefit of SMS in gas inhalation imaging has not been investigated. In this work, we compared the sensitivity of CO2 and O2 inhalation data collected using SMS factor 2 (SMS2) and SMS factor 3 (SMS3) with those collected using conventional EPI (SMS1). We showed that the sensitivity of SMS scans was significantly (p=0.01) higher than that of conventional EPI, although no difference was found between SMS2 and SMS3 (p=0.3). On a voxel-wise level, approximately 20-30% of voxels in the brain showed a significant enhancement in sensitivity when using SMS compared with conventional EPI, with other voxels showing an increase, but not reaching statistical significance. When using SMS, the scan duration can be reduced by half, whilst maintaining the sensitivity of conventional EPI. The availability of a sensitive acquisition technique can further enhance the potential of gas inhalation MRI in clinical applications.