Simultaneous Multislice Imaging Research Articles

Diffusion-weighted imaging of the head and neck: comparison between integrated slice-specific dynamic shimming and simultaneous multi-slice readout-segmented echo-planar sequences.

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.

Acceleration of Simultaneous Multislice Magnetic Resonance Fingerprinting With Spatiotemporal Convolutional Neural Network.

Magnetic Resonance Fingerprinting (MRF) can be accelerated with simultaneous multislice (SMS) imaging for joint T1 and T2 quantification. However, the high inter-slice and in-plane acceleration in SMS-MRF causes severe aliasing artifacts, limiting the multiband (MB) factors to typically 2 or 3. Deep learning has demonstrated superior performance compared to the conventional dictionary matching approach for single-slice MRF, but its effectiveness in SMS-MRF remains unexplored. In this paper, we introduced a new deep learning approach with decoupled spatiotemporal feature learning for SMS-MRF to achieve high MB factors for accurate and volumetric T1 and T2 quantification in neuroimaging. The proposed method leverages information from both spatial and temporal domains to mitigate the significant aliasing in SMS-MRF. Neural networks, trained using either acquired SMS-MRF data or simulated data generated from single-slice MRF acquisitions, were evaluated. The performance was further compared with both dictionary matching and a deep learning approach based on residual channel attention U-Net. Experimental results demonstrated that the proposed method, trained with acquired SMS-MRF data, achieves the best performance in brain T1 and T2 quantification, outperforming dictionary matching and residual channel attention U-Net. With a MB factor of 4, rapid T1 and T2 mapping was achieved with 1.5 s per slice for quantitative brain imaging.

Diagnostic performance of simultaneous multislice diffusion-weighted imaging in differentiating breast lesions: a systematic review and meta-analysis.

To investigate the diagnostic performance of simultaneous multislice diffusion-weighted imaging (SMS-DWI) in differentiating malignant and benign breast lesions, and compare it with conventional single shot and readout segmented echo planar imaging without the SMS technique. The literature search was performed in PubMed, Embase, and Web of Science to identify comparative studies reporting the diagnostic performance of SMS-DWI and conventional DWI in patients with breast lesions. Histopathological analysis was used as a reference standard for malignant breast lesions. The methodological quality was evaluated using QUADAS-2 scale. The summary sensitivity, summary specificity, and area under the curve (AUC) of the summarized receiver operating characteristic curve were calculated and compared between SMS-DWI and conventional DWI using a bivariate random-effects model. Heterogeneity was explored with meta-regression and subgroup analyses. Six studies with 626 patients and 649 breast lesions (benign: 222, malignant: 427) were included. The summary sensitivity, summary specificity, and AUC for SMS-DWI were 0.89 (95% CI: 0.78-0.95), 0.94 (95% CI: 0.81-0.98), and 0.96 (95% CI: 0.94-0.98), respectively, and those for conventional DWI were 0.90 (0.95 CI: 0.84-0.94), 0.87 (95% CI: 0.80-0.92), and 0.94 (95% CI: 0.92-0.96), respectively. The diagnostic performance was not significantly different between SMS-DWI and conventional DWI (P = .337). SMS-DWI has high diagnostic performance in differentiating breast lesions, which is not significantly different from the conventional DWI. There is no significant difference between SMS-DWI and conventional DWI in differentiating breast lesions, suggesting SMS-DWI may be a potential alternative to conventional DWI in breast imaging.

Simultaneous multislice echo-planar diffusion-weighted imaging (DWI) in patients with focal liver lesions: a comparative study with conventional DWI.

Simultaneous multislice (SMS) technology improves acquisition efficiency of diffusion-weighted imaging (DWI). This study aimed to evaluate the performance of SMS-DWI in image quality and apparent diffusion coefficient (ADC) measurements for focal liver lesions (FLLs) as compared with that of conventional DWI (CON-DWI). The institutional ethics committee of West China Hospital, Sichuan University approved this single-center, prospective study conducted from February 2021 to March 2022. Free-breathing SMS-DWI and CON-DWI examinations were acquired on a 3-T scanner with b-values of 50, 400, and 800 s/mm2. Qualitative image quality and quantitative measurements of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC were compared between SMS-DWI and CON-DWI. The ADC values for FLLs were further compared between SMS-DWI and CON-DWI in different patient subgroups. The intra- and interreader agreements were assessed. Significance was set at P<0.05. This study included 116 patients (96 males, 20 females; mean age 52.0±10.7 years) with 119 FLLs. No significant differences were observed between SMS-DWI and CON-DWI regarding overall image quality in any b-value DWIs, and there were also no differences observed between SMS-DWI and CON-DWI (b=800 s/mm2) for either SNR or CNR (both P values >0.05). ADC values obtained from CON-DWI were higher than those from SMS-DWI in all FLLs [(1.31±0.47)×10-3 vs. (1.26±0.46)×10-3 mm2/s; P=0.004], and similar findings were observed across the different patient subgroups. The consistency analysis showed intrareader intraclass correlation coefficient (ICC) values of 0.792-0.944 and interreader ICC values of 0.758-0.861 for quantitative measurements (SNR, CNR, and ADC) and kappa values of 0.609-0.878 for qualitative image quality. SMS-DWI achieved a 37% reduction in scan time compared to CON-DWI while maintaining comparable overall image quality. Notably, the ADC values for FLLs were observed to be quantitatively lower with SMS-DWI.

Multiphoton simultaneous multislice imaging.

To develop multiphoton excitation techniques for simultaneous multislice (SMS) imaging and evaluate their performance and specific absorption rate (SAR) benefit. To improve multiphoton SMS reconstruction quality with a novel CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) design. When a conventional single-slice RF field is applied together with an oscillating gradient field, the two can combine to generate multiphoton excitation at multiple discrete spatial locations. Because the conventional RF is reused at multiple spatial locations, multiphoton excitation offers reduced SAR for SMS applications. CAIPIRINHA shifts are often used to improve parallel-imaging acceleration. Interestingly, CAIPIRINHA-type shifts can be obtained for multiphoton SMS by updating the oscillating gradient phase at every phase encode. In this work, both a gradient-echo and a spin-echo sequence with multiphoton CAIPIRINHA-SMS excitation pulses are implemented for in vivo human imaging at 3 T. For three slices, multiphoton SMS provides a 51% reduction in SAR compared with conventional superposition SMS, whereas for five slices, SAR is reduced by 66%. Multiphoton SMS outperforms PINS (power independent of number of slices) and MultiPINS in terms of SAR reduction especially when the pulse duration is short, slices are thin, and/or the slice spacing is large. A custom CAIPIRINHA phase-encoding design for multiphoton SMS significantly improves reconstruction quality. Multiphoton SMS excitation can be obtained by combining conventional single-slice RF pulses with an oscillating gradient and offers significant SAR benefits compared with conventional superposition SMS. A novel CAIPIRINHA design allows higher multiband factors for multiphoton SMS imaging.

Bayesian optimization of gradient trajectory for parallel-transmit pulse design.

Spoke pulses improve excitation homogeneity in parallel-transmit MRI. We propose an efficient global optimization algorithm, Bayesian optimization of gradient trajectory (BOGAT), for single-slice and simultaneous multislice imaging. BOGAT adds an outer loop to optimize kT-space positions. For each position, the RF coefficients are optimized (e.g., with magnitude least squares) and the cost function evaluated. Bayesian optimization progressively estimates the cost function. It automatically chooses the kT-space positions to sample, to achieve fast convergence, often coming close to the globally optimal spoke positions. We investigated the typical features of spokes cost functions by a grid search with field maps comprising 85 slabs from 14 volunteers. We tested BOGAT in this database, and prospectively in a phantom and in vivo. We compared the vendor-provided Fourier transform approach with the same magnitude least squares RF optimizer. The cost function is nonconvex and seen empirically to be piecewise smooth with discontinuities where the underlying RF optimum changes sharply. BOGAT converged to within 10% of the global minimum cost within 30 iterations in 93% of slices in our database. BOGAT achieved up to 56% lower flip angle RMS error (RMSE) or 55% lower pulse energy in phantoms versus the Fourier transform approach, and up to 30% lower RMSE and 29% lower energy in vivo with 7.8 s extra computation. BOGAT efficiently estimated near-global optimum spoke positions for the two-spoke tests, reducing flip-angle RMSE and/or pulse energy in a computation time (˜10 s), which is suitable for online optimization.

Data- and Physics-driven Deep Learning Based Reconstruction for Fast MRI: Fundamentals and Methodologies.

Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric, temporal and quantitative scans. This review elucidates recent advances in MRI acceleration via data and physics-driven models, leveraging techniques from algorithm unrolling models, enhancement-based methods, and plug-and-play models to the emerging full spectrum of generative model-based methods. We also explore the synergistic integration of data models with physics-based insights, encompassing the advancements in multi-coil hardware accelerations like parallel imaging and simultaneous multi-slice imaging, and the optimization of sampling patterns. We then focus on domain-specific challenges and opportunities, including image redundancy exploitation, image integrity, evaluation metrics, data heterogeneity, and model generalization. This work also discusses potential solutions and future research directions, with an emphasis on the role of data harmonization and federated learning for further improving the general applicability and performance of these methods in MRI reconstruction.

Kiosk 11R-TB-05 - Evaluation of Accelerated FBee-breathing Motion Corrected and Averaged Late Gadolinium Enhancement Using Simultaneous Multi-slice Imaging

Kiosk 11R-TB-05 - Evaluation of Accelerated FBee-breathing Motion Corrected and Averaged Late Gadolinium Enhancement Using Simultaneous Multi-slice Imaging

Feasibility study of dual-accelerated simultaneous multi-slice imaging in diffusion tensor imaging of glioma.

To explore the value of dual-accelerated simultaneous multi-slice (SMS) imaging in diffusion tensor imaging (DTI) of glioma. Thirty-four patients with glioma who underwent magnetic resonance imaging (MRI) in our hospital from January 2022 to March 2023 were randomly selected. The results of dual-accelerated SMS-DTI and conventional DTI were retrospectively analyzed. All patients were scanned using a uMR790 3.0T MRI scanner, and the scanning technicians followed a predefined sequence to ensure consistency in scan parameters. The images were subjectively evaluated using a Likert 5-point scoring system. Objective evaluation was performed by measuring the required values of the images with b-value = 1000 s/mm2, primarily measuring the signal intensity in the tumor region and the contralateral normal brain white matter region. The standard deviation values were used to calculate the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in the same encoding direction as the background noise. The number of generated fiber pathways, fractional anisotropy (FA), and mean diffusivity (MD) were measured and analyzed using post-processing software. The relative FA (rFA) and relative MD (rMD) were calculated. The results of conventional DTI and SMS-accelerated DTI were compared. In terms of subjective evaluation, including overall image quality, tumor edge clarity, and magnetic sensitivity artifacts, both techniques showed no significant differences, indicating comparable diagnostic performance in anatomical visualization. In terms of objective evaluation and quantitative parameter measurement, there were statistically significant differences in SNR and CNR values, with slightly lower values in the dual-accelerated SMS-DTI compared with conventional DTI, a significant reduction in scanning time can be achieved through a slight loss in image quality. The number of fiber pathways and the rFA and rMD values did not show typical differences between the two techniques. The correlation between these measures was highly similar, with no significant differences observed. The application of dual-accelerated simultaneous multi-slice imaging in DTI of glioma is feasible.

Fast reconstruction of SMS bSSFP myocardial perfusion images using noise map estimation network (NoiseMapNet): a head-to-head comparison with parallel imaging and iterative reconstruction.

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.

Effect of simultaneous multislice imaging, slice properties, and repetition time on the measured magnetic resonance biexponential intravoxel incoherent motion in the liver.

This study aims to investigate the previously reported dependency of intravoxel incoherent motion (IVIM) parameters on simultaneous multislice (SMS) acquisition and repetition time (TR). This includes the influence of slice thickness, slice gaps, and slice order on measured IVIM parameters. Diffusion-weighted imaging (DWI) of the liver was performed on 10 healthy volunteers (aged 20-30 years) at 3T with a slice thickness of 5 mm, a slice gap of 5 mm, and a linear slice order. Diffusion-weighted images were acquired with 19 b-values (0-800 s/mm2) using both conventional slice excitation with an acceleration factor of one (AF1) and SMS excitation with an acceleration factor of three (AF3). Each of these measurements were carried out with two repetition times (TRs)- 1,300 ms (prefix s) and 4,500 ms (prefix l)-resulting in four different combinations: sAF1, sAF3, lAF1, and lAF3. Five volunteers underwent additional measurements using a 10 mm slice thickness and with AF1. Median signal values in the liver were used to determine the biexponential IVIM parameters. Statistical significances were assessed using the Kruskal-Wallis test, Wilcoxon signed-rank test, and Student's t-test. In-silico investigations were also used to interpret the data. There were no significant differences between the biexponential IVIM parameters acquired from sAF1, sAF3, lAF1, and lAF3. Median values of the perfusion fraction f were as follows: 29.9% (sAF1), 26.9% (sAF3), 28.1% (lAF1), and 27.5% (lAF3). In the 10 mm-thick slices, f decreased from 31.3% (lAF1) to 27.4% (sAF1) (p = 0.141). The slice excitation mode did not appear to have any significant influence on the biexponential IVIM parameters. However, our simulations, as well as values reported from previous publications, show that slice thickness, slice gaps, and slice order are relevant and should thus be reported in IVIM studies.

High sensitivity mapping of brain-wide functional networks in awake mice using simultaneous multi-slice fUS imaging

Abstract Functional ultrasound (fUS) has received growing attention in preclinical research in the past decade, providing a new tool to measure functional connectivity (FC) and brain task-evoked responses with single-trial detection capability in both anesthetized and awake conditions. Most fUS studies rely on 2D linear arrays to acquire one slice of the brain. Volumetric fUS using 2D matrix or row-column arrays has recently been demonstrated in rats and mice but requires invasive craniotomy to expose the brain due to a lack of sensitivity. In a previous study, we proposed the use of motorized linear arrays, allowing imaging through the skull in mice for multiple slices with high sensitivity. However, the tradeoff between the field of view and temporal resolution introduced by motorized scanning prevents acquiring brain-wide resting-state FC data with a sufficient volume rate for resting-state FC analysis. Here, we propose a new hybrid solution optimized and dedicated to brain-wide transcranial FC studies in mice, based on a newly developed multi-array transducer allowing simultaneous multi-slicing of the entire mouse cerebrum. We first demonstrate that our approach provides a better imaging quality compared to other existing methods. Then, we show the ability to image the whole mouse brain non-invasively through the intact skin and skull during visual stimulation under light anesthesia to validate this new approach. Significant activation was detected along the whole visual pathway, at both single and group levels, with more than 10% of augmentation of the cerebral blood volume (CBV) signal during the visual stimulation compared to baseline. Finally, we assessed resting-state FC in awake head-fixed animals. Several robust and long-ranged FC patterns were identified in both cortical and sub-cortical brain areas, corresponding to functional networks already described in previous fMRI studies. Together, these results show that the multi-array probe is a valuable approach to measure brain-wide hemodynamic activity in mice with an intact skull. Most importantly, its ability to identify robust resting-state networks is paving the way towards a better understanding of the mouse brain functional organization and its breakdown in genetic models of neuropsychiatric diseases.

4 Resting State Functional Connectivity Impairments Implicate CNS Mechanisms Underlying Chronic Pain and Depression in Gulf War Veterans’ Illness

Objective:Around 200,000 veterans (up to 32% of those deployed) of the 1991 Gulf War (GW) suffer from GW veterans’ illness (GWVI). GWVI is a poorly understood chronic medical condition, characterized by symptoms indicative of brain function deficits in multiple domains. Among the symptoms of brain impairment GWVI-related chronic headaches and body muscle and joint pain conditions (GWVI-HAP) are the most debilitating, affecting around 64% of the GWVI veterans. Further, depression carries a very high co-morbid rate (&gt;50%) in patients with chronic pain, including GWVI-HAP. In this preliminary study, we examined the integrity of brain function networks in a group of GWI-HAP veterans, with resting state fMRI (rsfMRI).Participants and Methods:Data from the first twenty-two GWVI-HAP veterans from two ongoing parallel clinical trials was examined. Of these 14 subjects (GWVI-HAP-DM) had mild depression (Hamilton Rating Scale for Depression (HSRD &lt; 13); and 8 subjects (GWVI-HAP-DS) had moderate to severe depression (HSRD &gt; 14). Written informed consent was obtained from all participants in the protocol approved by the local Institutional Review Board. RsfMRI data was acquired on a Siemens 3T Prisma-Fit MRI scanner using a 10-minute whole-brain high resolution simultaneous multi-slice (SMS) gradient echo echo-planar imaging (EPI) sequence: TR/TE/FA = 2.2 sec/ 27 msec/80°, and analyzed with well-established image processing pipelines. Functional connectivity (FC) to different regions implicated in depression and chronic pain was assessed with seed-based correlation analysis. Between group differences in FC were obtained with 2-sample t-tests.Results:GWVI-HAP-DS group exhibited significantly (p &lt; 0.05) reduced FC compared to GWVI-HAP-DM between frontal lobe (medial (mPFC), and dorsolateral (dlPFC) prefrontal cortex) and the striatum. This indicates that malfunction of fronto-striatal circuits could be a source of the increased chronic pain and depression seen in veterans with GWVI- HAP-DS. Dysregulation of fronto-striatal networks has been implicated in major depressive disorder as well as many chronic pain conditions. In addition, FC between mPFC, and salience network (SN; anterior insula and dorsal anterior cingulate) and limbic (subgenual and ventral anterior cingulate) regions were also reduced in GWVI-HAP-DS. Similarly, mPFC and SN also exhibited reduced FC to pain processing regions (posterior insula, centromedian thalamus and cerebellum). These FC impairments could reflect greater deficits in regulation of and salience attribution to emotions and nociception in the GWVI-HAP-DS group. Finally, GWVI-HAP-DS also exhibited reduced FC between nodes of the default mode network. DMN impairments also have been observed in many depressive and chronic pain conditions.Conclusions:The results of this preliminary analysis implicate impairments in cognitive control of emotion and nociception as a mechanism underlying the enhanced chronic pain and depression observed in GWVI-HAP veterans, especially those with moderate to severe depression. A fuller picture of deficits in FC in brain function networks is expected to emerge as more GWI-HAP subjects of both groups along with age matched healthy controls are examined in this ongoing project. Better understanding of impairments in these networks in GWI-HAP will benefit the rehabilitation of veterans with GWI-HAP.

Aberrant spontaneous static and dynamic amplitude of low-frequency fluctuations in cerebral small vessel disease with or without mild cognitive impairment.

Cerebral small vessel disease (CSVD) is considered an age-related degenerative neurological disorder and the most common risk factor for vascular cognitive impairment (VCI). The amplitude of fluctuation of low frequency (ALFF) can detect altered intrinsic brain activity in CSVD. This study explored the static and dynamic ALFFs in the early stage of CSVD with (CSVD-M) or without (CSVD-W) mild cognitive impairment (MCI) in these patients and how these changes contribute to cognitive deterioration. Thirty consecutive CSVD cases and 18 healthy controls (HC) were included in this study. All the participants underwent a 3D magnetization-prepared rapid gradient-echo (MPRAGE) sequence to obtain structural T1-weighted images. Simultaneous multislice imaging 5(SMS5) was used for resting-state functional MRI (rs-fMRI), and Data Processing and Analysis of Brain Imaging software helped determine static ALFF (sALFF). The dynamic ALFF (dALFF) was calculated using the sliding window method of DynamicBC software. Analysis of Covariance (ANCOVA) and two-sample t-test were used to evaluate the sALFF and temporal variability of dALFF among the three groups. The subjects were rated on a broad standard neuropsychological scale. Partial correlation analysis was used to evaluate the correlation between sALFF and dALFF variability and cognition (Bonferroni correction, statistical threshold set at p<.05). Compared with HCs, the CSVD-M group indicated decreased sALFF values in the bilateral cerebellum posterior lobe (CPL) and the left inferior Parietal Lobule (IPL), with increased sALFF values in the right SFG. For dALFF analysis, the CSVD-W group had significant dALFF variability in the right fusiform gyrus compared with HC. Moreover, the postcentral gyrus (PoCG) was significantly high in the CSVD-W group. While in the CSVD-M group, the bilateral paracentral lobules (PL) revealed significantly elevated dALFF variability and low dALFF variability in the left CPL and right IPL compared with HCs. The CSVD-M group had high dALFF variability in the bilateral PL but low dALFF variability in the left middle temporal gyrus (MTG) and right PoCG compared with the CSVD-W group. The partial correlation analysis indicated that dALFF variability in the left MTG was positively associated with EM (r=0.713, p=.002) in CSVD-W and CSVD-M groups. In the groups with CSVD-M and HC, altered dALFF variability in the bilateral PL was negatively correlated with EM (r=-0.560, p=.002). There were significant changes in sALFF and dALFF variability in CSVD patients. Abnormal spontaneous static and dynamic ALFFs may provide new insights into cognitive dysfunction in CSVD with MCI and may be valuable biomarkers for early diagnosis.

Improved Simultaneous Multi-slice imaging with Composition of k-space Interpolations (SMS-COOKIE) for myocardial T1 mapping.

The aim of this study is to develop and evaluate a regularized Simultaneous Multi-Slice (SMS) reconstruction method for improved Cardiac Magnetic Resonance Imaging (CMR). The proposed reconstruction method, SMS with COmpOsition of k-space IntErpolations (SMS-COOKIE) combines the advantages of Iterative Self-consistent Parallel Imaging Reconstruction (SPIRiT) and split slice-Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA), while allowing regularization for further noise reduction. The proposed SMS-COOKIE was implemented with and without regularization, and validated using a Saturation Pulse-Prepared Heart rate Independent inversion REcovery (SAPPHIRE) myocardial T1 mapping sequence. The performance of the proposed reconstruction method was compared to ReadOut (RO)-SENSE-GRAPPA and split slice-GRAPPA, on both retrospectively and prospectively three-fold SMS-accelerated data with an additional two-fold in-plane acceleration. All SMS reconstruction methods yielded similar T1 values compared to single band imaging. SMS-COOKIE showed lower spatial variability in myocardial T1 with significant improvement over RO-SENSE-GRAPPA and split slice-GRAPPA (P < 10-4). The proposed method with additional locally low rank (LLR) regularization reduced the spatial variability, again with significant improvement over RO-SENSE-GRAPPA and split slice-GRAPPA (P < 10-4). In conclusion, improved reconstruction quality was achieved with the proposed SMS-COOKIE, which also provided lower spatial variability with significant improvement over split slice-GRAPPA.

Reconstruction and completion of high-resolution 3D cardiac shapes using anisotropic CMRI segmentations and continuous implicit neural representations

Since the onset of computer-aided diagnosis in medical imaging, voxel-based segmentation has emerged as the primary methodology for automatic analysis of left ventricle (LV) function and morphology in cardiac magnetic resonance images (CMRI). In standard clinical practice, simultaneous multi-slice 2D cine short-axis MR imaging is performed under multiple breath-holds resulting in highly anisotropic 3D images. Furthermore, sparse-view CMRI often lacks whole heart coverage caused by large slice thickness and often suffers from inter-slice misalignment induced by respiratory motion. Therefore, these volumes only provide limited information about the true 3D cardiac anatomy which may hamper highly accurate assessment of functional and anatomical abnormalities. To address this, we propose a method that learns a continuous implicit function representing 3D LV shapes by training an auto-decoder. For training, high-resolution segmentations from cardiac CT angiography are used. The ability of our approach to reconstruct and complete high-resolution shapes from manually or automatically obtained sparse-view cardiac shape information is evaluated by using paired high- and low-resolution CMRI LV segmentations. The results show that the reconstructed LV shapes have an unconstrained subvoxel resolution and appear smooth and plausible in through-plane direction. Furthermore, Bland-Altman analysis reveals that reconstructed high-resolution ventricle volumes are closer to the corresponding reference volumes than reference low-resolution volumes with bias of [limits of agreement] −3.51 [−18.87, 11.85] mL, and 12.96 [−10.01, 35.92] mL respectively. Finally, the results demonstrate that the proposed approach allows recovering missing shape information and can indirectly correct for limited motion-induced artifacts.

Resting-state functional connectivity-based parcellation of the human dentate nucleus: new findings and clinical relevance.

For years, the cerebellum was left out of functional magnetic resonance imaging (fMRI) studies due to technological limitations. The advent of novel data acquisition and reconstruction strategies (e.g., whole-brain simultaneous multi-slice imaging) employing multi-channel array coils has overcome such limitations, ushering unprecedented improvements in temporal signal-to-noise ratio and spatiotemporal resolution. Here, we aim to provide a brief report on the deep cerebellar nuclei, specifically focusing on the dentate nuclei, the primary output nuclei, situated within both cognitive and motor cerebello-cerebral circuits. We highlight the importance of functional parcellation in refining our understanding of broad resting-state functional connectivity (RSFC) in both health and disease. First, we review work relevant to the functional topography of the dentate nuclei, including recent advances in functional parcellation. Next, we review RSFC studies using the dentate nuclei as seed regions of interest in neurological and psychiatric populations and discuss the potential benefits of applying functionally defined subdivisions. Finally, we discuss recent technological advances and underscore ultrahigh-field neuroimaging as a tool to potentiate functionally parcellated RSFC analyses in clinical populations.

Abdominal Diffusion-Weighted MRI With Simultaneous Multi-Slice Acquisition: Agreement and Reproducibility of Apparent Diffusion Coefficients Measurements.

Simultaneous multi-slice diffusion-weighted imaging (SMS-DWI) can shorten acquisition time in abdominal imaging. To investigate the agreement and reproducibility of apparent diffusion coefficient (ADC) from abdominal SMS-DWI acquired with different vendors and different breathing schemes. Prospective. Twenty volunteers and 10 patients. 3.0 T, SMS-DWI with a diffusion-weighted echo-planar imaging sequence. SMS-DWI was acquired using breath-hold and free-breathing techniques in scanners from two vendors, yielding four scans in each participant. Average ADC values were measured in the liver, pancreas, spleen, and both kidneys. Non-normalized ADC and ADCs normalized to the spleen were compared between vendors and breathing schemes. Paired t-test or Wilcoxon signed rank test; intraclass correlation coefficient (ICC); Bland-Altman method; coefficient of variation (CV) analysis; significance level: P < 0.05. Non-normalized ADCs from the four SMS-DWI scans did not differ significantly in the spleen (P = 0.262, 0.330, 0.166, 0.122), right kidney (P = 0.167, 0.538, 0.957, 0.086), and left kidney (P = 0.182, 0.281, 0.504, 0.405), but there were significant differences in the liver and pancreas. For normalized ADCs, there were no significant differences in the liver (P = 0.315, 0.915, 0.198, 0.799), spleen (P = 0.815, 0.689, 0.347, 0.423), pancreas (P = 0.165, 0.336, 0.304, 0.584), right kidney (P = 0.165, 0.336, 0.304, 0.584), and left kidney (P = 0.496, 0.304, 0.443, 0.371). Inter-reader agreements of non-normalized ADCs were good to excellent (ICCs ranged from 0.861 to 0.983), and agreement and reproducibility were good to excellent depending on anatomic location (CVs ranged from 3.55% to 13.98%). Overall CVs for abdominal ADCs from the four scans were 6.25%, 7.62%, 7.08, and 7.60%. The normalized ADCs from abdominal SMS-DWI may be comparable between different vendors and breathing schemes, showing good agreement and reproducibility. ADC changes above approximately 8% may potentially be considered as a reliable quantitative biomarker to assess disease or treatment-related changes. 2 TECHNICAL EFFICACY: Stage 2.

Feasibility of high-resolution readout-segmented echo-planar imaging with simultaneous multislice imaging in assessing rectal cancer.

To investigate the feasibility of high-resolution readout-segmented echo-planar imaging (rs-EPI) with simultaneous multislice (SMS) imaging to predict well-differentiated rectal cancer.Kindly check and confirm whether the Author Name 'Hongyun Huang ' is correctly identified.confirm METHODS: A total of eighty-three patients with nonmucinous rectal adenocarcinoma received both prototype SMS high-spatial-resolution and conventional rs-EPI sequences. Image quality was subjectively assessed by two experienced radiologists using a 4-point Likert scale (1 = poor, 4 = excellent). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and apparent diffusion coefficient (ADC) of the lesion were measured by two experienced radiologists in the objective assessment. Paired t tests or Mann‒Whitney U tests were used to compare the two groups. The areas under the receiver operating characteristic (ROC) curves (AUCs) were used to determine the predictive value of the ADCs in discriminating well-differentiated rectal cancer in the two groups. A two-sided p value < 0.05 represented statistical significance.Please check and confirm if the authors and affiliation details have been correctly identified. Amend if necessary.confirm RESULTS: In the subjective assessment, high-resolution rs-EPI had better image quality than conventional rs-EPI (p < 0.001). High-resolution rs-EPI also had a significantly higher SNR and CNR (p < 0.001). The T stage of rectal cancer was inversely correlated with the ADCs measured on high-resolution rs-EPI (r = -0.622, p < 0.001) and rs-EPI (r = -0.567, p < 0.001). The AUC of high-resolution rs-EPI in predicting well-differentiated rectal cancer was 0.768. High-resolution rs-EPI with SMS imaging provided significantly higher image quality, SNRs, and CNRs and more stable ADC measurements than conventional rs-EPI. Additionally, the pretreatment ADC on high-resolution rs-EPI could discriminate well-differentiated rectal cancer.

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.