Simultaneous Multi-slice Acquisition Research Articles

Non-Cartesian 3D-SPARKLING vs Cartesian 3D-EPI encoding schemes for functional Magnetic Resonance Imaging at 7 Tesla.

The quest for higher spatial and/or temporal resolution in functional MRI (fMRI) while preserving a sufficient temporal signal-to-noise ratio (tSNR) has generated a tremendous amount of methodological contributions in the last decade ranging from Cartesian vs. non-Cartesian readouts, 2D vs. 3D acquisition strategies, parallel imaging and/or compressed sensing (CS) accelerations and simultaneous multi-slice acquisitions to cite a few. In this paper, we investigate the use of a finely tuned version of 3D-SPARKLING. This is a non-Cartesian CS-based acquisition technique for high spatial resolution whole-brain fMRI. We compare it to state-of-the-art Cartesian 3D-EPI during both a retinotopic mapping paradigm and resting-state acquisitions at 1mm3 (isotropic spatial resolution). This study involves six healthy volunteers and both acquisition sequences were run on each individual in a randomly-balanced order across subjects. The performances of both acquisition techniques are compared to each other in regards to tSNR, sensitivity to the BOLD effect and spatial specificity. Our findings reveal that 3D-SPARKLING has a higher tSNR than 3D-EPI, an improved sensitivity to detect the BOLD contrast in the gray matter, and an improved spatial specificity. Compared to 3D-EPI, 3D-SPARKLING yields, on average, 7% more activated voxels in the gray matter relative to the total number of activated voxels.

Modern acceleration in musculoskeletal MRI: applications, implications, and challenges.

Magnetic resonance imaging (MRI) is crucial for accurately diagnosing a wide spectrum of musculoskeletal conditions due to its superior soft tissue contrast resolution. However, the long acquisition times of traditional two-dimensional (2D) and three-dimensional (3D) fast and turbo spin-echo (TSE) pulse sequences can limit patient access and comfort. Recent technical advancements have introduced acceleration techniques that significantly reduce MRI times for musculoskeletal examinations. Key acceleration methods include parallel imaging (PI), simultaneous multi-slice acquisition (SMS), and compressed sensing (CS), enabling up to eightfold faster scans while maintaining image quality, resolution, and safety standards. These innovations now allow for 3- to 6-fold accelerated clinical musculoskeletal MRI exams, reducing scan times to 4 to 6min for joints and spine imaging. Evolving deep learning-based image reconstruction promises even faster scans without compromising quality. Current research indicates that combining acceleration techniques, deep learning image reconstruction, and superresolution algorithms will eventually facilitate tenfold accelerated musculoskeletal MRI in routine clinical practice. Such rapid MRI protocols can drastically reduce scan times by 80-90% compared to conventional methods. Implementing these rapid imaging protocols does impact workflow, indirect costs, and workload for MRI technologists and radiologists, which requires careful management. However, the shift from conventional to accelerated, deep learning-based MRI enhances the value of musculoskeletal MRI by improving patient access and comfort and promoting sustainable imaging practices. This article offers a comprehensive overview of the technical aspects, benefits, and challenges of modern accelerated musculoskeletal MRI, guiding radiologists and researchers in this evolving field.

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.

Multiband acquisition sequences for fMRI: Proceed with caution

Multiband or simultaneous multi-slice acquisition sequences for fMRI have become popular over the last decade, partly because of the influence of the approach taken in large-scale studies such as the Human Connectome Project. However, applying this type of highly-accelerated, high-resolution sequence to smaller-scale projects may come with significant drawbacks in terms of signal to noise ratio, reliability, and experimental power. In particular, the use of smaller voxels, short repetition times, and high levels of multiband acceleration may have strong negative effects on signal to noise, image artefacts, and signal dropout in medial and ventral brain regions. Multiband sequences can be valuable tools, particularly for specialist applications, but should be applied in smaller-scale studies judiciously, with a focus on a particular project’s endpoints, and after appropriate testing and pilot work.

Evaluation of simultaneous multi-slice acquisition with advanced processing for free-breathing diffusion-weighted imaging in patients with liver metastasis

ObjectivesDiffusion-weighted imaging (DWI) with simultaneous multi-slice (SMS) acquisition and advanced processing can accelerate acquisition time and improve MR image quality. This study evaluated the image quality and apparent diffusion coefficient (ADC) measurements of free-breathing DWI acquired from patients with liver metastases using a prototype SMS-DWI acquisition (with/without an advanced processing option) and conventional DWI.MethodsFour DWI schemes were compared in a pilot 5-patient cohort; three DWI schemes were further assessed in a 24-patient cohort. Two readers scored image quality of all b-value images and ADC maps across the three methods. ADC measurements were performed, for all three methods, in left and right liver parenchyma, spleen, and liver metastases. The Friedman non-parametric test (post-hoc Wilcoxon test with Bonferroni correction) was used to compare image quality scoring; t-test was used for ADC comparisons.ResultsSMS-DWI was faster (by 24%) than conventional DWI. Both readers scored the SMS-DWI with advanced processing as having the best image quality for highest b-value images (b750) and ADC maps; Cohen’s kappa inter-reader agreement was 0.6 for b750 image and 0.56 for ADC maps. The prototype SMS-DWI sequence with advanced processing allowed a better visualization of the left lobe of the liver. ADC measured in liver parenchyma, spleen, and liver metastases using the SMS-DWI with advanced processing option showed lower values than those derived from the SMS-DWI method alone (t-test, p < 0.0001; p < 0.0001; p = 0.002).ConclusionsFree-breathing SMS-DWI with advanced processing was faster and demonstrated better image quality versus a conventional DWI protocol in liver patients.Clinical relevance statementFree-breathing simultaneous multi-slice- diffusion-weighted imaging (DWI) with advanced processing was faster and demonstrated better image quality versus a conventional DWI protocol in liver patients.Key Points• Diffusion-weighted imaging (DWI) with simultaneous multi-slice (SMS) can accelerate acquisition time and improve image quality.• Apparent diffusion coefficients (ADC) measured in liver parenchyma, spleen, and liver metastases using the simultaneous multi-slice DWI with advanced processing were significantly lower than those derived from the simultaneous multi-slice DWI method alone.• Simultaneous multi-slice DWI sequence with inline advanced processing was faster and demonstrated better image quality in liver patients.

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

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

Evaluation of simultaneous multi-slice readout-segmented diffusion-weighted MRI acquisition in human optic nerve measurements

Diffusion-weighted magnetic resonance imaging (dMRI) is the only available method to measure the tissue properties of white matter tracts in living human brains and has opened avenues for neuroscientific and clinical studies on human white matter. However, dMRI using conventional simultaneous multi-slice (SMS) single-shot echo planar imaging (ssEPI) still presents challenges in the analyses of some specific white matter tracts, such as the optic nerve, which are heavily affected by susceptibility-induced artifacts. In this study, we evaluated dMRI data acquired by using SMS readout-segmented EPI (rsEPI), which aims to reduce susceptibility-induced artifacts by dividing the acquisition space into multiple segments along the readout direction to reduce echo spacing. To this end, we acquired dMRI data from 11 healthy volunteers by using SMS ssEPI and SMS rsEPI, and then compared the dMRI data of the human optic nerve between the SMS ssEPI and SMS rsEPI datasets by visual inspection of the datasets and statistical comparisons of fractional anisotropy (FA) values. In comparison with the SMS ssEPI data, the SMS rsEPI data showed smaller susceptibility-induced distortion and exhibited a significantly higher FA along the optic nerve. In summary, this study demonstrates that despite its prolonged acquisition time, SMS rsEPI is a promising approach for measuring the tissue properties of the optic nerve in living humans and will be useful for future neuroscientific and clinical investigations of this pathway.

An Automatic Motion-Based Artifact Reduction Algorithm for fNIRS in Concurrent Functional Magnetic Resonance Imaging Studies (AMARA–fMRI)

Multimodal functional near-infrared spectroscopy–functional magnetic resonance imaging (fNIRS–fMRI) studies have been highly beneficial for both the fNIRS and fMRI field as, for example, they shed light on the underlying mechanism of each method. However, several noise sources exist in both methods. Motion artifact removal is an important preprocessing step in fNIRS analysis. Several manual motion–artifact removal methods have been developed which require time and are highly dependent on expertise. Only a few automatic methods have been proposed. AMARA (acceleration-based movement artifact reduction algorithm) is one of the most promising automatic methods and was originally tested in an fNIRS sleep study with long acquisition times (~8 h). However, it relies on accelerometry data, which is problematic when performing concurrent fNIRS–fMIRI experiments. Most accelerometers are not MR compatible, and in any case, existing datasets do not have this data. Here, we propose a new way to retrospectively determine acceleration data for motion correction methods, such as AMARA in multimodal fNIRS–fMRI studies. We do so by considering the individual slice stack acquisition times of simultaneous multislice (SMS) acquisition and reconstructing high-resolution motion traces from each slice stack time. We validated our method on 10 participants during a memory task (2- and 3-back) with 6 fNIRS channels over the prefrontal cortex (limited field of view with fMRI). We found that this motion correction significantly improved the detection of activation in deoxyhemoglobin and outperformed up-sampled motion traces. However, we found no improvement in oxyhemoglobin. Furthermore, our data show a high overlap with fMRI activation when considering activation in channels according to both deoxyhemoglobin and oxyhemoglobin.

Whole-body diffusion magnetic resonance imaging with simultaneous multi-slice excitation in children and adolescents

BackgroundWhole-body magnetic resonance imaging (WB-MRI) is an increasingly used guideline-based imaging modality for oncological and non-oncological pathologies during childhood and adolescence. While diffusion-weighted imaging (DWI), a part of WB-MRI, enhances image interpretation and improves sensitivity, it also requires the longest acquisition time during a typical WB-MRI scan protocol. Interleaved short tau inversion recovery (STIR) DWI with simultaneous multi-slice (SMS) acquisition is an effective way to speed up examinations.ObjectiveIn this study of children and adolescents, we compared the acquisition time, image quality, signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) values of an interleaved STIR SMS-DWI sequence with a standard non-accelerated DWI sequence for WB-MRI.Materials and methodsTwenty children and adolescents (mean age: 13.9 years) who received two WB-MRI scans at a maximum interval of 18 months, consisting of either standard DWI or SMS-DWI MRI, respectively, were included. For quantitative evaluation, the signal-to-noise ratio (SNR) was determined for b800 images and ADC maps of seven anatomical regions. Image quality evaluation was independently performed by two experienced paediatric radiologists using a 5-point Likert scale. The measurement time per slice stack, pause between measurements including shim and total measurement time of DWI for standard DWI and SMS-DWI were extracted directly from the scan data.ResultsWhen including the shim duration, the acquisition time for SMS-DWI was 43% faster than for standard DWI. Qualitatively, the scores of SMS-DWI were higher in six locations in the b800 images and four locations in the ADC maps. There was substantial agreement between both readers, with a Cohen’s kappa of 0.75. Quantitatively, the SNR in the b800 images and the ADC maps did not differ significantly from one another.ConclusionWhole body-MRI with SMS-DWI provided equivalent image quality and reduced the acquisition time almost by half compared to the standard WB-DWI protocol.

Image Quality of Lumbar Spine Imaging at 0.55T Low-Field MRI is Comparable to Conventional 1.5T MRI – Initial Observations in Healthy Volunteers

To assess the potential of 0.55T low-field MRI system in lumbar spine imaging with and without the use of additional advanced postprocessing techniques. The lumbar spine of 14 volunteers (32.9 ± 3.6 years) was imaged both at 0.55T and 1.5T using sequences from clinical routine. On the 0.55T scanner system, additional sequences with simultaneous multi-slice acquisition and artificial intelligence-based postprocessing techniques were acquired. Image quality of all 28 examinations was assessed by three musculoskeletal radiologists with respect to signal/contrast, resolution, and assessability of the spinal canal and neuroforamina using a 5-point Likert scale (1=non-diagnostic to 5=perfect quality). Interrater agreement was evaluated with the Intraclass Correlation Coefficient and the Mann-Whitney U test (significance level: p < 0.05). Image quality at 0.55T was rated lower on the 5-point Likert scale compared to 1.5T regarding signal/contrast (mean: 4.16 ± 0.29 vs. 4.54 ± 0.29; p < 0.001), resolution (4.07 ± 0.31 vs. 4.49 ± 0.30; p < 0.001), assessability of the spinal canal (4.28 ± 0.13 vs. 4.73 ± 0.26; p < 0.001) and the neuroforamina (4.14 ± 0.28 vs. 4.70 ± 0.27; p < 0.001). Image quality for the AI-processed sagittal T1 TSE and T2 TSE at 0.55T was also rated slightly lower, but still good to perfect with a concomitant reduction in measurement time. Interrater agreement was good to excellent (range: 0.60-0.91). While lumbar spine image quality at 0.55T is perceived inferior to imaging at 1.5T by musculoskeletal radiologists, good overall examination quality was observed with high interrater agreement. Advanced postprocessing techniques may accelerate intrinsically longer acquisition times at 0.55T.

Quantitative myocardial perfusion with a hybrid 2D simultaneous multi-slice sequence

PurposeTo evaluate a novel 2D simultaneous multi-slice (SMS) myocardial perfusion acquisition and compare directly to a published quantitative 3D stack-of-stars (SoS) acquisition. MethodsA hybrid saturation recovery radial 2D SMS sequence following a single saturation was created for the quantification of myocardial blood flow (MBF). This sequence acquired three slices simultaneously and generated an arterial input function (AIF) using the first 24 rays. Validation was done in a novel way by alternating heartbeats between the hybrid 2D SMS and the 3D SoS acquisitions. Initial studies were done to study the effects of using only every other beat for the 2D SMS in two subjects, and for the 3D SoS in four subjects. The proposed alternating acquisitions were then performed in ten dog studies at rest, four dog studies at adenosine stress, and two human resting studies. Quantitative MBF analysis was performed for 2D SMS and 3D SoS separately, using a compartment model. ResultsAcquiring every-other-beat data resulted in 6 ± 5% (“ideal”) and 11 ± 8% (“practical”) perfusion changes for both 2D SMS and 3D SoS methods. For alternating acquisitions, 2D SMS and 3D SoS quantitative perfusion values were comparable for both the twelve rest studies (2D SMS: 0.69 ± 0.16 vs 3D: 0.69 ± 0.15 ml/g/min, p = 0.55) and the four stress studies (2D SMS: 1.28 ± 0.22 vs 3D: 1.30 ± 0.24 ml/g/min, p = 0.61). ConclusionEvery-other-beat acquisition changed estimated perfusion values relatively little for both sequences. The quantitative hybrid radial 2D SMS myocardial first-pass perfusion imaging sequence gave results similar to 3D perfusion when compared directly with an alternating beat acquisition.

Measuring brain beats: Cardiac-aligned fast functional magnetic resonance imaging signals.

Blood and cerebrospinal fluid (CSF) pulse and flow throughout the brain, driven by the cardiac cycle. These fluid dynamics, which are essential to healthy brain function, are characterized by several noninvasive magnetic resonance imaging (MRI) methods. Recent developments in fast MRI, specifically simultaneous multislice acquisition methods, provide a new opportunity to rapidly and broadly assess cardiac-driven flow, including CSF spaces, surface vessels and parenchymal vessels. We use these techniques to assess blood and CSF flow dynamics in brief (3.5min) scans on a conventional 3T MRI scanner in five subjects. Cardiac pulses are measured with a photoplethysmography (PPG) on the index finger, along with functional MRI (fMRI) signals in the brain. We, retrospectively, align the fMRI signals to the heartbeat. Highly reliable cardiac-gated fMRI temporal signals are observed in CSF and blood on the timescale of one heartbeat (test-retest reliability within subjects R2 > 50%). In blood vessels, a local minimum is observed following systole. In CSF spaces, the ventricles and subarachnoid spaces have a local maximum following systole instead. Slower resting-state scans with slice timing, retrospectively, aligned to the cardiac pulse, reveal similar cardiac-gated responses. The cardiac-gated measurements estimate the amplitude and phase of fMRI pulsations in the CSF relative to those in the arteries, an estimate of the local intracranial impedance. Cardiac aligned fMRI signals can provide new insights about fluid dynamics or diagnostics for diseases where these dynamics are important.

Denoising diffusion weighted imaging data using convolutional neural networks.

Diffusion weighted imaging (DWI) with multiple, high b-values is critical for extracting tissue microstructure measurements; however, high b-value DWI images contain high noise levels that can overwhelm the signal of interest and bias microstructural measurements. Here, we propose a simple denoising method that can be applied to any dataset, provided a low-noise, single-subject dataset is acquired using the same DWI sequence. The denoising method uses a one-dimensional convolutional neural network (1D-CNN) and deep learning to learn from a low-noise dataset, voxel-by-voxel. The trained model can then be applied to high-noise datasets from other subjects. We validated the 1D-CNN denoising method by first demonstrating that 1D-CNN denoising resulted in DWI images that were more similar to the noise-free ground truth than comparable denoising methods, e.g., MP-PCA, using simulated DWI data. Using the same DWI acquisition but reconstructed with two common reconstruction methods, i.e. SENSE1 and sum-of-square, to generate a pair of low-noise and high-noise datasets, we then demonstrated that 1D-CNN denoising of high-noise DWI data collected from human subjects showed promising results in three domains: DWI images, diffusion metrics, and tractography. In particular, the denoised images were very similar to a low-noise reference image of that subject, more than the similarity between repeated low-noise images (i.e. computational reproducibility). Finally, we demonstrated the use of the 1D-CNN method in two practical examples to reduce noise from parallel imaging and simultaneous multi-slice acquisition. We conclude that the 1D-CNN denoising method is a simple, effective denoising method for DWI images that overcomes some of the limitations of current state-of-the-art denoising methods, such as the need for a large number of training subjects and the need to account for the rectified noise floor.

WHOCARES: WHOle-brain CArdiac signal REgression from highly accelerated simultaneous multi-Slice fMRI acquisitions

Objective. To spatio-temporally resolve cardiac signals in functional magnetic resonance imaging (fMRI) time-series of the human brain using neither external physiological measurements nor ad hoc modelling assumptions. Approach. Cardiac pulsation is a physiological confound of fMRI time-series that introduces spurious signal fluctuations in proximity to blood vessels. fMRI alone is not sufficiently fast to resolve cardiac pulsation. Depending on the ratio between the instantaneous heart-rate and the acquisition sampling frequency (, with TR being the repetition time), the cardiac signal may alias into the frequency band of neural activation so that its removal through spectral filtering techniques is generally not possible. In this paper, we show that it is feasible to temporally and spatially resolve cardiac signals throughout the brain even when cardiac aliasing occurs by combining fMRI hyper-sampling with simultaneous multislice (SMS) imaging. The technique, which we name WHOle-brain CArdiac signal REgression from highly accelerated simultaneous multi-Slice fMRI acquisitions (WHOCARES), was developed on 695 healthy subjects selected from the Human Connectome Project and its performance validated against the RETROICOR, HAPPY and the pulse oxymeter signal regression methods. Main results. WHOCARES is capable of retrieving voxel-wise cardiac signal regressors. This is achieved without employing external physiological recordings nor through ad hoc modelling assumptions. The performance of WHOCARES was, on average, superior to RETROICOR, HAPPY and the pulse oxymeter regression methods. Significance. WHOCARES holds basis for the reliable mapping of cardiac activity in fMRI time-series. WHOCARES can be employed for the retrospective removal of cardiac noise in publicly available fMRI datasets where physiological recordings are not available. WHOCARES is freely available at https://github.com/gferrazzi/WHOCARES.

Reducing Acquisition Time of Diffusion Weighted MR Imaging of the Rectum with Simultaneous Multi-Slice Acquisition: A Reader Study

To assess the acquisition time and image quality of simultaneous multislice-accelerated diffusion-weighted imaging (SMS-DWI) versus conventional DWI (C-DWI) of the rectum. In patients scheduled for a magnetic resonance imaging of the rectum, both SMS-DWI and C-DWI were performed on a 3T whole body magnetic resonance scanner. Image quality of the DWI sequences was reviewed by two independent radiologists who were blinded to the method of imaging using a five-point Likert scale: (score ranging from 1 (non-diagnostic) to 5 (excellent). The mean scores of SMS-DWI versus C-DWI were compared for the individual readers using a nonparametric test (Wilcoxon signed ranks). The SMS-DWI protocol acquisition time was 4:08 min vs. 7:24 min per patient, which led to a reduction of 44.1% for the C-DWI protocol, both excluding time for sequence specific adjustments (shimming). No statistical differences between the conventional-, and SMS- diffusion weighted images were seen for both readers. Mean overall image quality of the SMS-DWI TRACE images was 3.5 (SD: 1.3) and 3.3 (SD: 1.0) for reader 1 and reader 2, respectively. Mean overall image quality of the C-DWI TRACE images was 3.4 (SD: 1.3) and 3.2 (SD: 1.1) for reader 1 and reader 2, respectively. Optimized SMS-DWI compared to C-DWI in imaging of the rectum showed similar image quality while a significant acquisition time reduction was achieved.

Leveraging redundancy in simultaneous multislice acquisitions to improve spike detection.

To improve the performance of low-level spike noise artifact detection for daily quality assurance protocols by taking advantage of redundancy in simultaneous multislice (SMS) acquisitions. Magnitude images were transformed into pseudo k-space images. Time series at each pseudo k-space point were detrended. A slice was determined to contain spiking artifact if it exceeded an intensity threshold and if all simultaneously acquired slices contained outliers. A total of 401 112 slices were inspected. Of these, 42 showed a spike artifact, based on visual inspection of image data and k-space data. With an intensity threshold of 4.6 SDs over time for each pseudo k-space point, all slices containing artifact were correctly flagged, and only 30 slices were incorrectly flagged when using the SMS criterion. Without the SMS criterion, 12 908 slices were incorrectly flagged as containing artifact. Without the SMS criterion, sensitivity to artifact would have to be sacrificed to substantially reduce the number of incorrectly flagged slices. This study demonstrates that the SMS criterion reduced the number of outliers reported to a manageable level while accurately identifying low-level spike artifacts. Successfully identifying low-level spikes allows early detection of hardware problems that can be fixed before the problem becomes debilitating and corrupts data. As part of a daily quality assurance protocol, the method prevents the need to retrospectively carry out time-intensive despiking and reanalysis of data.

DEep learning-based rapid Spiral Image REconstruction (DESIRE) for high-resolution spiral first-pass myocardial perfusion imaging.

The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) technique for high-resolution spiral first-pass myocardial perfusion imaging with whole-heart coverage, to provide fast and accurate image reconstruction for both single-slice (SS) and simultaneous multislice (SMS) acquisitions. Three-dimensional U-Net-based image enhancement architectures were evaluated for high-resolution spiral perfusion imaging at 3T. The SS and SMS MB =2 networks were trained on SS perfusion images from 156 slices from 20 subjects. Structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and normalized root mean square error (NRMSE) were assessed, and prospective images were blindly graded by two experienced cardiologists (5: excellent; 1: poor). Excellent performance was demonstrated for the proposed technique. For SS, SSIM, PSNR, and NRMSE were 0.977 [0.972, 0.982], 42.113 [40.174, 43.493] dB, and 0.102 [0.080, 0.125], respectively, for the best network. For SMS MB =2 retrospective data, SSIM, PSNR, and NRMSE were 0.961 [0.950, 0.969], 40.834 [39.619, 42.004] dB, and 0.107 [0.086, 0.133], respectively, for the best network. The image quality scores were 4.5 [4.1, 4.8], 4.5 [4.3, 4.6], 3.5 [3.3, 4], and 3.5 [3.3, 3.8] for SS DESIRE, SS L1-SPIRiT, MB =2 DESIRE, and MB =2 SMS-slice-L1-SPIRiT, respectively, showing no statistically significant difference (p=1 and p= 1 for SS and SMS, respectively) between L1-SPIRiT and the proposed DESIRE technique. The network inference time was ~100 ms per dynamic perfusion series with DESIRE, while the reconstruction time of L1-SPIRiT with GPU acceleration was ~ 30 min. It was concluded that DESIRE enabled fast and high-quality image reconstruction for both SS and SMS MB =2 whole-heart high-resolution spiral perfusion imaging.

Concurrent CBF and BOLD fMRI with dual-echo spiral simultaneous multi-slice acquisitions at 7T

Measurement of cerebral blood flow (CBF) using the Arterial Spin Labeling (ASL) technique is a desirable fMRI approach due to the higher specificity of CBF to the site of neural activation. However, ASL has inherent limitations, such as a low signal-to-noise ratio (SNR) and low coverage/resolution due to the limited readout window following the labeling. Recently, ASL has been implemented at ultra-high field (UHF) strengths in an attempt to mitigate the SNR challenges. Even though ASL intrinsically allows concurrent acquisition of CBF and BOLD contrasts, a compromise in the echo time (TE) for either of the contrasts is inevitable with single-echo acquisitions. Long durations of the Cartesian EPI readout do not allow for multi-echo acquisitions for resolutions ≤2 mm where both contrasts can be acquired at their optimal TE at UHF. With its higher acquisition efficiency, single-shot spiral imaging provides a promising alternative to EPI, and with a dual-echo, out-in trajectory allows both CBF and BOLD contrasts to be acquired at their respective optimal TE. In this work, we implemented a dual-echo spiral out-in ASL sequence with simultaneous multi-slice (SMS) readout for increased coverage, and validated its application to fMRI with a visuomotor paradigm. Conventional Cartesian EPI acquisitions with matched parameters served as a reference. The dual-echo spiral ASL acquisitions resulted in robust CBF and BOLD activations maps. The absolute and relative CBF changes measured with the dual-echo spiral readout were in agreement with previous reports in the literature as well as the reference Cartesian acquisitions. The BOLD response amplitude was higher compared to the Cartesian acquisitions, attributable to a more optimal TE of the second echo. In conclusion, dual-echo spiral out-in SMS acquisition shows promise for concurrent acquisitions of BOLD and non-BOLD contrasts that require a short TE, with no loss in temporal resolution.

Super-Resolution Arterial Spin Labeling Using Slice-Dithered Enhanced Resolution and Simultaneous Multi-Slice Acquisition.

Purpose: To achieve high spatial resolution (isotropic-2 mm) perfusion imaging using 2D simultaneous multi-slice (SMS) pseudo-continuous arterial spin labeling (pCASL) and slice dithered enhanced resolution (SLIDER) technique for super-resolution reconstruction.Methods: The SLIDER-SMS pCASL with a multiband factor of 4 was implemented at 3T with three numbers of slice shift (2/3/4) for the slice thickness of 4/6/8 mm, respectively. Super-resolution reconstruction was performed with singular value decomposition and different levels of Tikhonov regularizations. Temporal and spatial signal-to-noise ratio (SNR) as well as spatial blurring effects of super-resolution ASL images were measured in five healthy subjects and compared with those of reference high-resolution ASL images.Results: Compared to conventional 2D SMS ASL, super-resolution ASL images with isotropic-2-mm resolution yielded 42, 61, and 88% higher spatial SNR, and 18, 55, and 105% higher temporal SNR with slice shift number of 2/3/4, respectively. Spatial blurring effect increased for SLIDER reconstruction from two to four slice shifts.Conclusion: The proposed SLIDER-SMS pCASL technique can achieve whole-brain high-resolution perfusion images with ∼15-min scan time and improved SNR compared to standard 2D SMS pCASL. Caution needs to be exercised on quantifying and controlling blurring effects of SLIDER reconstruction.

Optimized 64-channel array configurations for accelerated simultaneous multislice acquisitions in 3T cardiac MRI.

Three 64-channel cardiac coils with different detector array configurations were designed and constructed to evaluate acceleration capabilities in simultaneous multislice (SMS) imaging for 3T cardiac MRI. Three 64-channel coil array configurations obtained from a simulation-guided design approach were constructed and systematically evaluated regarding their encoding capabilities for accelerated SMS cardiac acquisitions at 3T. Array configuration AUni-sized consists of uniformly distributed equally sized loops in an overlapped arrangement, BGapped uses a gapped array design with symmetrically distributed equally sized loops, and CDense has non-uniform loop density and size, where smaller elements were centered over the heart and larger elements were placed surrounding the target region. To isolate the anatomic variation from differences in the coil configurations, all three array coils were built with identical semi-adjustable housing segments. The arrays' performance was compared using bench-level measurements and imaging performance tests, including signal-to-noise ratio (SNR) maps, array element noise correlation, and SMS acceleration capabilities. Additionally, all cardiac array coils were evaluated on a healthy volunteer. The array configuration CDense with the non-uniformly distributed loop density showed the best overall cardiac imaging performance in both SNR and SMS encoding power, when compared to the other constructed arrays. The diffusion weighted cardiac acquisitions on a healthy volunteer support the favorable accelerated SNR performance of this array configuration. Our results indicate that optimized highly parallel cardiac arrays, such as the 64-channel coil with a non-uniform loop size and density improve highly accelerated SMS cardiac MRI in comparison to symmetrically distributed loop array designs.