Feasibility study of highly accelerated phase-sensitive inversion recovery myocardial viability imaging using simultaneous multislice and parallel imaging techniques.

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.

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.

Myocardial motion-corrected phase-sensitive inversion recovery late gadolinium enhancement in free breathing paediatric patients: a comparison with single-shot coherent gradient echo (“TrueFISP”) phase-sensitive inversion recovery

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.

Diffusion tensor imaging (DTI) of the brain provides essential information on the white matter integrity and structural connectivity. However, it suffers from a low signal-to-noise ratio (SNR) and requires a long scan time to achieve high spatial and/or diffusion resolution and wide brain coverage. With recent advances in parallel and simultaneous multislice (multiband) imaging, the SNR efficiency has been improved by reducing the repetition time (TR ). However, due to the limited number of RF coil channels available on preclinical MRI scanners, simultaneous multislice acquisition has not been practical. In this study, we demonstrate the ability of multiband DTI to acquire high-resolution data of the mouse brain with 84 slices covering the whole brain in 0.2 mm isotropic resolution without a coil array at 9.4 T. Hadamard-encoding four-band pulses were used to acquire four slices simultaneously, with the reduction in the TR maximizing the SNR efficiency. To overcome shot-to-shot phase variations, Hadamard decoding with a self-calibrated phase was developed. Compared with single-band DTI acquired with the same scan time, the multiband DTI leads to significantly increased SNR by 40% in the white matter. This SNR gain resulted in reduced variations in fractional anisotropy, mean diffusivity, and eigenvector orientation. Furthermore, the cerebrospinal fluid signal was attenuated, leading to reduced free-water contamination. Without the need for a high-density coil array or parallel imaging, this technique enables highly efficient preclinical DTI that will facilitate connectome studies.

Simultaneous multislice (SMS) imaging is a useful way to accelerate functional magnetic resonance imaging (fMRI). As acceleration becomes more aggressive, an increasingly larger number of receive coils are required to separate the slices, which significantly increases the computational burden. We propose a coil compression method that works with concentric ring non-Cartesian SMS imaging and should work with Cartesian SMS as well. We evaluate the method on fMRI scans of several subjects and compare it to standard coil compression methods. The proposed method uses a slice-separation k-space kernel to simultaneously compress coil data into a set of virtual coils. Five subjects were scanned using both non-SMS fMRI and SMS fMRI with three simultaneous slices. The SMS fMRI scans were processed using the proposed method, along with other conventional methods. Code is available at https://github.com/alcu/sms. The proposed method maintained functional activation with a fewer number of virtual coils than standard SMS coil compression methods. Compression of non-SMS fMRI maintained activation with a slightly lower number of virtual coils than the proposed method, but does not have the acceleration advantages of SMS fMRI. The proposed method is a practical way to compress and reconstruct concentric ring SMS data and improves the preservation of functional activation over standard coil compression methods in fMRI. Magn Reson Med 76:1196-1209, 2016. © 2015 Wiley Periodicals, Inc.

Motivation: Current clinically available DL image reconstruction techniques can reconstruct 6-fold accelerated knee MRI with excellent image quality. However, higher acceleration factors reduced image quality, requiring novel image reconstruction approaches. Goal(s): To evaluate a novel end-to-end DL image reconstruction method for 8-fold combined simultaneous multislice (SMS) and parallel imaging (PI) acceleration of TSE MRI. Approach: Twenty 8-fold accelerated knee MRI studies were acquired and reconstructed using a novel end-to-end DL-based reconstruction network that jointly handles SMS and Pl acceleration. Results: Image quality and detection rates of abnormalities were comparable to the clinical standard with lower acceleration factors. Impact: First clinical results for 8-fold accelerated knee MRI using a dedicated end-to-end DL reconstruction approach for combined SMS and PI acceleration demonstrate image quality comparable to slower standard-of-care MRI, holding promise for significantly faster clinical TSE MRI in the future.

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.

In this work, we aimed to develop and evaluate multi-band outer volume suppression pulses for increased acceleration rates in simultaneous multi-slice accelerated cardiac MRI. MB-OVS pulses were constructed from a multi-band combination of two slab-selective saturation pulses and tested for various pulse shapes using Bloch simulation and phantom experiment. The MB-OVS pulses were interleaved between imaging pulses to ensure homogeneous suppression throughout the cardiac cycle/imaging window in vivo. Simultaneous multi-slice (SMS) CINE and first-pass myocardial perfusion scans with and without the proposed MB-OVS pulses were compared in terms of residual artifacts at high acceleration rates. Among the tested pulses, both Bloch simulation and phantom experiments showed that amplitude-optimized sinc pulses provided the best trade-off in suppression efficiency, the required B1+, SAR, and slab profile. CINE imaging with 5-fold SMS-OVS acceleration significantly outperformed imaging without MB-OVS, maintaining leakage-free image quality, even when adding 2-fold in-plane acceleration. SMS-OVS also enabled perfusion imaging in 9 slices with 1.7 × 1.7 mm2 resolution, achieving a 16-fold spatial-only acceleration while ensuring accurate contrast dynamics without leakage artifacts. Interleaved MB-OVS modules enabled thorough leakage artifact suppression in cardiac SMS-accelerated CINE and perfusion imaging, particularly at high acceleration rates. The proposed approach may be promising for unlocking further acceleration potential of SMS in cardiac imaging.

Effectiveness of simultaneous multislice accelerated readout-segmented echo planar imaging for the assessment of rectal cancer

The depth of myometrial invasion in patients with endometrial carcinoma is recognized as an important factor that closely correlates with prognosis. Preoperative assessment of myometrial invasion is essential for planning surgery. To enhance the contrast between myometrium and endometrium including myometrial invasion with endometrial carcinoma, we optimized the sequence parameter with phase-sensitive inversion-recovery (PSIR) in gadolinium dynamic study of uterine corpus. On a 1.5-T magnetic resonance imaging (MRI), images were acquired by three-dimensional (3D) T1 -turbo field echo (TFE) with PSIR sequence and gadolinium-diethylenetriamine pentaacetic acid( Gd-DTPA) diluted phantom (0-5 mmol/L) and myometrium model (manganese chloride tetrahydrate+agar). We calculated the null point and the contrast-to-noise ratio (CNR) at multiple TFE inversion delay times, 200 ms-maximum in each combination; flip angles (FAs), 5-35 degrees; TFE factor, 20-40; and shot interval (SI), 500-1000 ms. We assumed that dynamic scanning time was 30 seconds when the sensitivity encoding factor was 2, namely, in this study, the scanning time was 1 minute with no sensitivity encoding. In addition, we compared CNR between optimized PSIR sequence ande-Thrive. We recognized a successful CNR of the 3D PSIR parameter was TFE inversion delay times, 335 ms; FA, 25 degrees; TFE factor, 20; and SI, 500 ms. In each gadolinium-DTPA diluted phantom, the average CNR of the optimized PSIR sequence was approximately 1.7 times (maximum: 3 times) higher than e-Thrive. Optimizing sequence parameter of PSIR is applicable in gadolinium dynamic study of uterine corpus.

Readout-segmented echo-planar imaging (rs-EPI) with simultaneous multislice (SMS) technology has been successfully applied to tumor research in many organs, but no feasibility study in rectal cancer has been reported, and the optimal acceleration of SMS with rs-EPI in rectal cancer has not been well determined yet. To investigate the feasibility of SMS rs-EPI of rectal cancer with different acceleration factors (AFs) and its influence on image quality, acquisition time and apparent diffusion coefficients (ADCs) in comparison to conventional sequences. All patients underwent rs-EPI and SMS rs-EPI with AFs of 2 and 3 (2 × SMS rs-EPI and 3 × SMS rs-EPI, respectively) using a 3T scanner. Acquisition times of the three rs-EPI sequences were measured. Image qualitative parameters (5-point Likert scale), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), geometric distortion, and apparent diffusion coefficient (ADC) values of the three sequences were compared. A total of eighty-three patients were enrolled in our study. rs-EPI and 2 × SMS rs-EPI offered equivalently high overall image quality with a scan time reduction to nearly half (rs-EPI: 137 s, 2 × SM rs-EPI: 60 s). 3 × SMS rs-EPI showed significantly poorer image quality (p < 0.05). ADC values were significantly lower in 3 × SMS rs-EPI compared to rs-EPI in rectal tumors and normal tissue (tumor tissue: rs-EPI 1.19 ± 0.21 × 10-3 mm2/s, 3 × SMS rs-EPI 1.10 ± 0.26 × 10-3 mm2/s, p < 0.001; normal tissue: rs-EPI 1.68 ± 0.13 × 10-3 mm2/s, 3 × SMS rs-EPI 1.54 ± 0.20 × 10-3 mm2/s, p < 0.001). SMS rs-EPI using an AF of 2 is feasible for rectal MRI resulting in substantial reductions in acquisition time while maintaining diagnostic image quality and similar ADC values to those of rs-EPI when the slice distance and number of shots are the same among three rs-EPI sequences.

To accelerate data acquisition speed in magnetic resonance imaging (MRI), multiple slices are simultaneously acquired using multiband pulses. Simultaneous multislice (SMS) imaging typically unfolds slice aliasing from the acquired collapsed slices. In this study, we extended the SMS framework to accelerated MR parameter quantification such as T1 mapping. Assuming that the slice-specific null space and signal subspace are invariant along the parameter dimension, we formulated the SMS framework as a constrained optimization problem under a joint reconstruction framework such that the noise and signal subspaces are used for slice separation and recovery, respectively. The proposed method was validated on 3T MR human brain scans. We successfully demonstrated that the proposed method outperforms competing methods in suppressing aliasing artifacts and noise at high SMS accelerations, thus leading to accurate T1 maps.

Simultaneous multi-slice (SMS) echo-planar imaging has had a huge impact on the acceleration and routine use of diffusion-weighted MRI (DWI) in neuroimaging studies in particular the human connectome project; but also holds the potential to facilitate DWI of moving subjects, as proposed by the new technique developed in this paper. We present a novel registration-based motion tracking technique that takes advantage of the multi-plane coverage of the anatomy by simultaneously acquired slices to enable robust reconstruction of neural microstructure from SMS DWI of moving subjects. Our technique constitutes three main components: 1) motion tracking and estimation using SMS registration, 2) detection and rejection of intra-slice motion, and 3) robust reconstruction. Quantitative results from 14 volunteer subject experiments and the analysis of motion-corrupted SMS DWI of 6 children indicate robust reconstruction in the presence of continuous motion and the potential to extend the use of SMS DWI in very challenging populations.

To develop an efficient acquisition for high-resolution diffusion imaging and allow in vivo whole-brain acquisitions at 600- to 700-μm isotropic resolution. We combine blipped-controlled aliasing in parallel imaging simultaneous multislice (SMS) with a novel slab radiofrequency (RF) encoding gSlider (generalized slice-dithered enhanced resolution) to form a signal-to-noise ratio-efficient volumetric simultaneous multislab acquisition. Here, multiple thin slabs are acquired simultaneously with controlled aliasing, and unaliased with parallel imaging. To achieve high resolution in the slice direction, the slab is volumetrically encoded using RF encoding with a scheme similar to Hadamard encoding. However, with gSlider, the RF-encoding bases are specifically designed to be highly independent and provide high image signal-to-noise ratio in each slab acquisition to enable self-navigation of the diffusion's phase corruption. Finally, the method is combined with zoomed imaging (while retaining whole-brain coverage) to facilitate low-distortion single-shot in-plane encoding with echo-planar imaging at high resolution. A 10-slices-per-shot gSlider-SMS acquisition was used to acquire whole-brain data at 660 and 760 μm isotropic resolution with b-values of 1500 and 1800 s/mm2 , respectively. Data were acquired on the Connectome 3 Tesla scanner with 64-channel head coil. High-quality data with excellent contrast were achieved at these resolutions, which enable the visualization of fine-scale structures. The gSlider-SMS approach provides a new, efficient way to acquire high-resolution diffusion data. Magn Reson Med 79:141-151, 2018. © 2017 International Society for Magnetic Resonance in Medicine.