Optimizing diffusion MRI acquisition efficiency of rodent brain using simultaneous multislice EPI.

Phase-sensitive inversion recovery (PSIR) is a powerful cardiac MRI method to assess myocardial viability, which can eliminate the background phase and preserve the sign of the desired magnetization during inversion recovery. To shorten the acquisition time of myocardial viability imaging by introducing both simultaneous multislice (SMS) and parallel imaging (PI) into PSIR without additional acquisitions for calibration data. Prospective study. A high-resolution phantom and three vials with doped solutions matching typical postcontrast T1 and T2 values of scar, healthy myocardium, and blood; 18 patients (six with known myocardial infarction) were included in this study. 3T/segmented fast spoiled gradient echo pulse sequence. Phantom and in vivo experiments were performed to compare the performance of conventional PSIR, SMS accelerated PSIR (SMS-PSIR, 2× acceleration), and SMS as well as PI accelerated PSIR (SMS + PI-PSIR, 4× acceleration). In phantom experiments, the error maps, local signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated. In in vivo experiments, the image quality and artifact level of each study were qualitatively graded (by three radiologists). G-factor maps were calculated. The infarct size presented as a percentage of the left ventricle was measured (full-width half-maximum). Acquisition time of each study was recorded. One-way analysis of variance, Kruskal-Wallis test. In phantom experiments, SNR and CNR were well preserved for SMS-PSIR, while they dropped for SMS + PI-PSIR, as expected. In 15 subjects, the overall image quality scores were not significantly different among conventional PSIR (3.70 ± 1.06), SMS-PSIR (3.78 ± 0.99), and SMS + PI-PSIR (3.47 ± 0.94; P = 0.20). The artifact level scores were also comparable among conventional PSIR (3.67 ± 1.04), SMS-PSIR (3.77 ± 1.03), and SMS + PI-PSIR (3.45 ± 1.00; P = 0.22). SMS-PSIR achieved negligible g-factor noise amplification (1.04 ± 0.03) and SMS + PI-PSIR showed higher g-factors (2.83 ± 0.48). The infarct size was consistent among conventional PSIR (22.51 ± 25.05%) and SMS-PSIR (22.98 ± 26.19%), as well as SMS + PI-PSIR (22.93 ± 25.68%; P = 0.98). The acquisition time of two short-axis slices for SMS-PSIR (17.6 ± 1.7 sec, 16 heartbeats) and SMS + PI-PSIR (9.8 ± 1.9 sec, 8 heartbeats) was 30% and 17% of that for conventional PSIR (56.2 ± 8.5 sec, 32 heartbeats), respectively. SMS can be implemented in PSIR without additional reference scan. The image quality is comparable with conventional PSIR, while the acquisition time is much shorter. The proposed method is also compatible with PI to further reduce the scan time. 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1964-1972.

Background Simultaneous multi-slice (SMS) imaging is starting to be used in clinical situation, although evidence of clinical feasibility is scanty. Purpose To prospectively assess the clinical feasibility of SMS diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI) with blipped-controlled aliasing in parallel imaging for brain lesions. Material and Methods The institutional review board approved this study. This study included 156 hyperintense lesions on DWI from 32 patients. A slice acceleration factor of 2 was applied for SMS scans, which allowed shortening of the scan time by 41.3%. The signal-to-noise ratio (SNR) was calculated for brain tissue of a selected slice. The contrast-to-noise ratio (CNR), apparent diffusion coefficient (ADC), and fractional anisotropy (FA) were calculated in 36 hyperintense lesions with a diameter of three pixels or more. Visual assessment was performed for all 156 lesions. Tractography of the corticospinal tract of 29 patients was evaluated. The number of tracts and averaged tract length were used for quantitative analysis, and visual assessment was evaluated by grading. Results The SMS scan showed no bias and acceptable 95% limits of agreement compared to conventional scans in SNR, CNR, and ADC on Bland-Altman analyses. Only FA of the lesions was higher in the SMS scan by 9% ( P = 0.016), whereas FA of the surrounding tissues was similar. Quantitative analysis of tractography showed similar values. Visual assessment of DWI hyperintense lesions and tractography also resulted in comparable evaluation. Conclusion SMS imaging was clinically feasible for imaging quality and quantitative values compared with conventional DWI and DTI.

Simultaneous Multi-Slice (SMS) magnetic resonance imaging (MRI) is a rapidly evolving technique for increasing imaging speed. Controlled aliasing techniques utilize periodic undersampling patterns to help mitigate the loss in signal-to-noise ratio (SNR) in SMS MRI. To evaluate the performance of different undersampling patterns, a quantitative description of the image SNR loss is needed. Additionally, eddy current effects in echo planar imaging (EPI) lead to slice-specific Nyquist ghosting artifacts. These artifacts cannot be accurately corrected for each individual slice before or after slice-unaliasing. In this work, we propose a hybrid-space sensitivity encoding (SENSE) reconstruction framework for SMS MRI by adopting a three-dimensional representation of the SMS acquisition. Analytical SNR loss maps are derived for SMS acquisitions with arbitrary phase encoding undersampling patterns. Moreover, we propose a matrix-decoding correction method that corrects the slice-specific Nyquist ghosting artifacts in SMS EPI acquisitions. Brain images demonstrate that the proposed hybrid-space SENSE reconstruction generates images with comparable quality to commonly used split-slice-generalized autocalibrating partially parallel acquisition reconstruction. The analytical SNR loss maps agree with those calculated by a Monte Carlo based method, but require less computation time for high quality maps. The analytical maps enable a fair comparison between the performances of coherent and incoherent SMS undersampling patterns. Phantom and brain SMS EPI images show that the matrix-decoding method performs better than the single-slice and slice-averaged Nyquist ghosting correction methods under the hybrid-space SENSE reconstruction framework.

Deep Learning (DL) techniques have enabled up to 6-fold acceleration in musculoskeletal magnetic resonance imaging (MRI) while preserving diagnostic image quality. Further, improvements in acceleration and generalization require novel approaches. We propose a DL framework that integrates Simultaneous Multislice (SMS) imaging with Parallel Imaging (PI) to enhance current DL-based reconstruction. To advance musculoskeletal Magnetic Resonance Imaging (MRI), by developing a DL reconstruction framework that combines SMS and PI, enabling acceleration of up to 8-fold and beyond, while maintaining image quality suitable for clinicalinterpretation. End-to-End (E2E) DL framework for reconstructing Turbo Spin Echo (TSE) MRI data acquired with SMS and PI acceleration. The method unrolls a proximal gradient algorithm with Nesterov momentum and integrates a novel DL network for joint regularization across simultaneously acquired slices. Slice separation and k-space-to-image reconstruction are unified by embedding the full SMS forward model into the DL architecture. Data Consistency (DC) is modulated to enhance denoising, and a super-resolution module improves image sharpness. The robust DL model was trained on over 200000 slices from 1.5T to 3T scans with diverse acquisitionsettings. The proposed E2E DL model outperforms prior methods at 8-fold and 12-fold acceleration, as measured by PSNR (peak signal-to-noise ratio) and SSIM (structural similarity index measure) metrics. Evaluation on prospectively acquired clinical scans by two radiologists confirms, that image quality and abnormality detection are comparable to standard acquisitions at loweracceleration. We extend state-of-the-art DL reconstruction frameworks by integrating slice separation directly into the model for SMS acquisitions. Our E2E DL approach achieves clinical-grade image quality at 8-fold acceleration across 20 subjects, reducing acquisition time by 27%. Preliminary results suggest potential for further acceleration up to 12-fold, demonstrating significant advancement beyond existing DLtechniques.

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.

To compare integrated slice-specific dynamic shimming (iShim) and simultaneous multi-slice (SMS) readout-segmented echo-planar imaging (RESOLVE) for diffusion-weighted imaging (DWI) of malignant head and neck tumours. In this prospective study, 45 patients with malignant head and neck lesions underwent iShim- and SMS-RESOLVE imaging with two b-values (0, 800 s/mm2) at 3 T. Subjective image quality scores (lesion distortion, signal loss, fat saturation, and artefacts), quantitative lesion distortion, quantitative image quality [signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and SNR efficiency], ADC values, and total acquisition times of iShim- and SMS-RESOLVE imaging were evaluated and compared. iShim-RESOLVE (3 mins 7 s) had longer acquisition times than SMS-RESOLVE (2 min 1 s). iShim-RESOLVE images had much better overall image quality, geometric distortion, fat saturation, and signal loss than SMS-RESOLVE (P < .05). The quantitative tumour distortion in iShim-RESOLVE images was significantly smaller than those of SMS-RESOLVE, measured either with b = 0 s/mm2 or b = 800 s/mm2 (P < .05). Using the iShim technique, the SNR, CNR of high b-value images, and SNR efficiency were significantly higher than those of SMS-RESOLVE (P < .001). The ADC measurements with excellent agreement of iShim-RESOLVE images were higher than those of SMS-RESOLVE. iShim-RESOLVE can decrease lesion distortion and improve overall image quality compared with SMS-RESOLVE in head and neck region. iShim-RESOLVE DWI may serve as a promising technique for reducing distortion and assessing head and neck lesions in clinical practice.

Parallel magnetic resonance imaging (MRI) techniques use spatial information from arrays of radiofrequency (RF) detector coils to accelerate imaging. A number of parallel MRI techniques have been described in recent years, and numerous clinical applications are currently being explored. The advent of practical parallel imaging presents various challenges for image reconstruction and RF system design. Recent advances in tailored SiMultaneous Acquisition of Spatial Harmonics (SMASH) image reconstructions are summarized. These advances enable robust SMASH imaging in arbitrary image planes with a wide range of coil array geometries. A generalized formalism is described which may be used to understand the relations between SMASH and SENSE, to derive typical implementations of each as special cases, and to form hybrid techniques combining some of the advantages of both. Accurate knowledge of coil sensitivities is crucial for parallel MRI, and errors in calibration represent one of the most common and the most pernicious sources of error in parallel image reconstructions. As one example, motion of the patient and/or the coil array between the sensitivity reference scan and the accelerated acquisition can lead to calibration errors and reconstruction artifacts. Self-calibrating parallel MRI approaches that address this problem by eliminating the need for external sensitivity references are reviewed. The ultimate achievable signal-to-noise ratio (SNR) for parallel MRI studies is closely tied to the geometry and sensitivity patterns of the coil arrays used for spatial encoding. Several parallel imaging array designs that depart from the traditional model of overlapped adjacent loop elements are described.

Sensitivity encoding (SENSE) with a receiver coil array is typically used as a means of reducing the scan time in MRI. The speed benefit usually comes at some expense in terms of the signal-to-noise ratio (SNR) efficiency, which has been notorious as the main downside of SENSE and parallel MRI in general. In this work it is shown that in steady-state gradient-echo imaging the parallel approach may as well be used to increase the SNR efficiency. The basic idea is to balance reduced phase encoding by increasing the repetition time. In this fashion both the acquisition duty cycle and the steady-state magnetization can be enhanced, resulting in considerable net gains in SNR yield. It is argued that the reduction factor in parallel imaging is essentially an additional degree of freedom in optimizing the SNR. The optimal SENSE factor depends on scan, tissue, and hardware parameters, assuming values up to 3.0 and higher. The achievable SNR benefit also depends on the spoiling regime and is most pronounced for RF-spoiled techniques. The proposed mechanism is demonstrated by simulations and phantom experiments, as well as by contrast-enhanced angiography in vivo, achieving an approximate doubling of the SNR efficiency.

Functional cerebral blood volume mapping with simultaneous multi-slice acquisition

Simultaneous multi-slice (SMS) bSSFP imaging enables stress myocardial perfusion imaging with high spatial resolution and increased spatial coverage. Standard parallel imaging techniques (e.g., TGRAPPA) can be used for image reconstruction but result in high noise level. Alternatively, iterative reconstruction techniques based on temporal regularization (ITER) improve image quality but are associated with reduced temporal signal fidelity and long computation time limiting their online use. The aim is to develop an image reconstruction technique for SMS-bSSFP myocardial perfusion imaging combining parallel imaging and image-based denoising using a novel noise map estimation network (NoiseMapNet), which preserves both sharpness and temporal signal profiles and that has low computational cost. The proposed reconstruction of SMS images consists of a standard temporal parallel imaging reconstruction (TGRAPPA) with motion correction (MOCO) followed by image denoising using NoiseMapNet. NoiseMapNet is a deep learning network based on a 2D Unet architecture and aims to predict a noise map from an input noisy image, which is then subtracted from the noisy image to generate the denoised image. This approach was evaluated in 17 patients who underwent stress perfusion imaging using a SMS-bSSFP sequence. Images were reconstructed with (a) TGRAPPA with MOCO (thereafter referred to as TGRAPPA), (b) iterative reconstruction with integrated motion compensation (ITER), and (c) proposed NoiseMapNet-based reconstruction. Normalized mean squared error (NMSE) with respect to TGRAPPA, myocardial sharpness, image quality, perceived SNR (pSNR), and number of diagnostic segments were evaluated. NMSE of NoiseMapNet was lower than using ITER for both myocardium (0.045 ± 0.021 vs. 0.172 ± 0.041, p < 0.001) and left ventricular blood pool (0.025 ± 0.014 vs. 0.069 ± 0.020, p < 0.001). There were no significant differences between all methods for myocardial sharpness (p = 0.77) and number of diagnostic segments (p = 0.36). ITER led to higher image quality than NoiseMapNet/TGRAPPA (2.7 ± 0.4 vs. 1.8 ± 0.4/1.3 ± 0.6, p < 0.001) and higher pSNR than NoiseMapNet/TGRAPPA (3.0 ± 0.0 vs. 2.0 ± 0.0/1.3 ± 0.6, p < 0.001). Importantly, NoiseMapNet yielded higher pSNR (p < 0.001) and image quality (p < 0.008) than TGRAPPA. Computation time of NoiseMapNet was only 20s for one entire dataset. NoiseMapNet-based reconstruction enables fast SMS image reconstruction for stress myocardial perfusion imaging while preserving sharpness and temporal signal profiles.

Parallel imaging is a robust method for accelerating the acquisition of magnetic resonance imaging (MRI) data, and has made possible many new applications of MR imaging. Parallel imaging works by acquiring a reduced amount of k-space data with an array of receiver coils. These undersampled data can be acquired more quickly, but the undersampling leads to aliased images. One of several parallel imaging algorithms can then be used to reconstruct artifact-free images from either the aliased images (SENSE-type reconstruction) or from the undersampled data (GRAPPA-type reconstruction). The advantages of parallel imaging in a clinical setting include faster image acquisition, which can be used, for instance, to shorten breath-hold times resulting in fewer motion-corrupted examinations. In this article the basic concepts behind parallel imaging are introduced. The relationship between undersampling and aliasing is discussed and two commonly used parallel imaging methods, SENSE and GRAPPA, are explained in detail. Examples of artifacts arising from parallel imaging are shown and ways to detect and mitigate these artifacts are described. Finally, several current applications of parallel imaging are presented and recent advancements and promising research in parallel imaging are briefly reviewed.

Diffusion tensor imaging of cerebral white matter integrity in cognitive aging

To evaluate the clinical feasibility of diffusion tensor imaging (DTI) of the kidney in volunteers and patients with renal diseases. Ten volunteers and 22 patients (mean age, 56 +/- 14.3) with renal masses and renal artery stenosis underwent breath-hold coronal fat-saturated echo-planar DTI (as provided by the manufacturer, 6 diffusion directions, diffusion weightings b = 0 and 300 s/mm2, repetition time 730 ms/echo time 72 ms; 5 slices; slice thickness, 6 mm; inplane resolution, 2.1 x 2.1 mm2; acquisition time, 26 seconds) of the kidneys at 1.5 T (MAGNETOM Avanto, Siemens Medical Solutions, Erlangen, Germany). The parallel imaging technique, generalized autocalibrating partially parallel acquisitions with an acceleration factor 2, was applied. Using the commercially available Syngo DTI task card software, regions of interests were placed in the cortex, medulla, and in renal masses if present. Fractional anisotropy (FA) and apparent diffusion coefficients (ADC) were determined, and tractography was used to visualize the renal diffusion properties. Statistical analysis was performed using the Wilcoxon signed-rank sum test and paired t tests. In all volunteers, FA was significantly (P < 0.01) higher in the medulla (0.36 +/- 0.03) than in the cortex (0.21 +/- 0.02), whereas the ADC was significantly (P < 0.01) higher in the cortex (2.43 +/- 0.19) than in the medulla (2.16 +/- 0.22). Tractography typically revealed a radial preferred direction of medullary diffusion basically reflecting medullary flow.FA/ADC of simple renal cysts (n = 8) was 0.14 +/- 0.05/2.86 +/- 0.15. Renal cell carcinoma (n = 10) showed a wide FA range from 0.11 to 0.56. Using tractography, the structural organization of renal cell carcinoma such as pseudocapsules could be visualized.In 1 patient with unilateral high-grade renal artery stenosis, the cortical ADC of the affected kidney was lower than on the contralateral side (1.77/2.27) and the FA was increased (0.33/0.18). The FA of the medulla was increased (0.70/0.41) and the ADC decreased (1.43/1.90). Using parallel imaging, DTI measurements of the kidneys are feasible within a single breath-hold with good discrimination between cortex and medulla. Parallel imaging allows more slices and a superior resolution. DTI measurements of the kidney allows visualization of medullary flow, in pathology ADC and FA were altered. Further investigations will be required to evaluate the role of DTI for studying and monitoring renal ultrastructure.

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.

Obese adults have been shown to have poorer white brain matter integrity relative to normal-weight peers, but few studies have tested whether white matter integrity is compromised in overweight and obese adolescents. Also, it is unclear if age interacts with body mass to affect white matter integrity in adolescents. We used Automated Fiber Quantification, a tractography method, to compare fractional anisotropy between normal-weight and overweight/obese adolescents in the corpus callosum, corticospinal tract, cingulum, inferior fronto-occipital fasciculus, and uncinate fasciculus. Further, we tested whether any differences were moderated by age. Forty-seven normal-weight and forty overweight/obese adolescents were scanned using a diffusion tensor imaging (DTI) scan sequence. Overweight/obese compared to normal-weight adolescents had decreased white matter integrity in the superior frontal corpus callosum, left and right uncinate fasciculi, left inferior fronto-occipital fasciculus, and left corticospinal tract, which may be related to heightened reward processing. Overweight/obese compared to normal-weight adolescents had increased white matter integrity in the orbital and anterior frontal corpus callosum, right inferior fronto-occipital fasciculus, left cingulum, and left corticospinal tract, which may be related to heightened attentional processing. As age increased, six tracts showed poorer white matter integrity as body mass index percentile (BMI%) increased, but three tracts showed greater white matter integrity as BMI% increased. Future research examining associations between white matter integrity and neural indices of food-related reward and attention are needed to clarify the functional significance of white matter integrity discrepancies between normal-weight and overweight/obese adolescents.