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Purpose: To evaluate the feasibility and utility of a deep learning (DL)-based reconstruction for improving the SNR of hyperpolarized 129 Xe lung ventilation MRI., Methods: 129 Xe lung ventilation MRI data acquired from patients with asthma and/or chronic obstructive pulmonary disease (COPD) were retrospectively reconstructed with a commercial DL reconstruction pipeline at five different denoising levels. Quantitative imaging metrics of lung ventilation including ventilation defect percentage (VDP) and ventilation heterogeneity index (VH I ) were compared between each set of DL-reconstructed images and alternative denoising strategies including: filtering, total variation denoising and higher-order singular value decomposition. Structural similarity between the denoised and original images was assessed. In a prospective study, the feasibility of using SNR gains from DL reconstruction to allow natural-abundance xenon MRI was evaluated in healthy volunteers., Results: 129 Xe ventilation image SNR was improved with DL reconstruction when compared with conventionally reconstructed images. In patients with asthma and/or COPD, DL-reconstructed images exhibited a slight positive bias in ventilation defect percentage (1.3% at 75% denoising) and ventilation heterogeneity index (˜1.4) when compared with conventionally reconstructed images. Additionally, DL-reconstructed images preserved structural similarity more effectively than data denoised using alternative approaches. DL reconstruction greatly improved image SNR (greater than threefold), to a level that 129 Xe ventilation imaging using natural-abundance xenon appears feasible., Conclusion: DL-based image reconstruction significantly improves 129 Xe ventilation image SNR, preserves structural similarity, and leads to a minor bias in ventilation metrics that can be attributed to differences in the image sharpness. This tool should help facilitate cost-effective 129 Xe ventilation imaging with natural-abundance xenon in the future., (© 2024 GE Healthcare and The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Deep learning (DL) reconstruction techniques to improve MR image quality are becoming commercially available with the hope that they will be applicable to multiple imaging application sites and acquisition protocols. However, before clinical implementation, these methods must be validated for specific use cases. In this work, the quality of standard-of-care (SOC) T2w and a high-spatial-resolution (HR) imaging of the breast were assessed both with and without prototype DL reconstruction. Studies were performed using data collected from phantoms, 20 retrospectively collected SOC patient exams, and 56 prospectively acquired SOC and HR patient exams. Image quality was quantitatively assessed via signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and edge sharpness. Qualitatively, all in vivo images were scored by either two or four radiologist readers using 5-point Likert scales in the following categories: artifacts, perceived sharpness, perceived SNR, and overall quality. Differences in reader scores were tested for significance. Reader preference and perception of signal intensity changes were also assessed. Application of the DL resulted in higher average SNR (1.2-2.8 times), CNR (1.0-1.8 times), and image sharpness (1.2-1.7 times). Qualitatively, the SOC acquisition with DL resulted in significantly improved image quality scores in all categories compared to non-DL images. HR acquisition with DL significantly increased SNR, sharpness, and overall quality compared to both the non-DL SOC and the non-DL HR images. The acquisition time for the HR data only required a 20% increase compared to the SOC acquisition and readers typically preferred DL images over non-DL counterparts. Overall, the DL reconstruction demonstrated improved T2w image quality in clinical breast MRI.

BOLD sensitivity to baseline perfusion and blood volume is a well-acknowledged fMRI confound. Vascular correction techniques based on cerebrovascular reactivity (CVR) might reduce variance due to baseline cerebral blood volume, however this is predicated on an invariant linear relationship between CVR and BOLD signal magnitude. Cognitive paradigms have relatively low signal, high variance and involve spatially heterogenous cortical regions; it is therefore unclear whether the BOLD response magnitude to complex paradigms can be predicted by CVR. The feasibility of predicting BOLD signal magnitude from CVR was explored in the present work across two experiments using different CVR approaches. The first utilized a large database containing breath-hold BOLD responses and 3 different cognitive tasks. The second experiment, in an independent sample, calculated CVR using the delivery of a fixed concentration of carbon dioxide and a different cognitive task. An atlas-based regression approach was implemented for both experiments to evaluate the shared variance between task-invoked BOLD responses and CVR across the cerebral cortex. Both experiments found significant relationships between CVR and task-based BOLD magnitude, with activation in the right cuneus ( R 2 = 0.64) and paracentral gyrus ( R 2 = 0.71), and the left pars opercularis ( R 2 = 0.67), superior frontal gyrus ( R 2 = 0.62) and inferior parietal cortex ( R 2 = 0.63) strongly predicted by CVR. The parietal regions bilaterally were highly consistent, with linear regressions significant in these regions for all four tasks. Group analyses showed that CVR correction increased BOLD sensitivity. Overall, this work suggests that BOLD signal response magnitudes to cognitive tasks are predicted by CVR across different regions of the cerebral cortex, providing support for the use of correction based on baseline vascular physiology., Competing Interests: RL was employed by GE Healthcare. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Williams, Specht, Mazerolle, Lebel, MacDonald and Pike.)

Objectives: To compare interobserver agreement and image quality of 3D T2-weighted fast spin echo (T2w-FSE) L-spine MRI images processed with a deep learning reconstruction (DLRecon) against standard-of-care (SOC) reconstruction, as well as against 2D T2w-FSE images. The hypothesis was that DLRecon 3D T2w-FSE would afford improved image quality and similar interobserver agreement compared to both SOC 3D and 2D T2w-FSE., Methods: Under IRB approval, patients who underwent routine 3-T lumbar spine (L-spine) MRI from August 17 to September 17, 2020, with both isotropic 3D and 2D T2w-FSE sequences, were retrospectively included. A DLRecon algorithm, with denoising and sharpening properties was applied to SOC 3D k-space to generate 3D DLRecon images. Four musculoskeletal radiologists blinded to reconstruction status evaluated randomized images for motion artifact, image quality, central/foraminal stenosis, disc degeneration, annular fissure, disc herniation, and presence of facet joint cysts. Inter-rater agreement for each graded variable was evaluated using Conger's kappa (κ)., Results: Thirty-five patients (mean age 58 ± 19, 26 female) were evaluated. 3D DLRecon demonstrated statistically significant higher median image quality score (2.0/2) when compared to SOC 3D (1.0/2, p < 0.001), 2D axial (1.0/2, p < 0.001), and 2D sagittal sequences (1.0/2, p value < 0.001). κ ranges (and 95% CI) for foraminal stenosis were 0.55-0.76 (0.32-0.86) for 3D DLRecon, 0.56-0.73 (0.35-0.84) for SOC 3D, and 0.58-0.71 (0.33-0.84) for 2D. Mean κ (and 95% CI) for central stenosis at L4-5 were 0.98 (0.96-0.99), 0.97 (0.95-0.99), and 0.98 (0.96-0.99) for 3D DLRecon, 3D SOC and 2D, respectively., Conclusions: DLRecon 3D T2w-FSE L-spine MRI demonstrated higher image quality and similar interobserver agreement for graded variables of interest when compared to 3D SOC and 2D imaging., Key Points: • 3D DLRecon T2w-FSE isotropic lumbar spine MRI provides improved image quality when compared to 2D MRI, with similar interobserver agreement for clinical evaluation of pathology. • 3D DLRecon images demonstrated better image quality score (2.0/2) when compared to standard-of-care (SOC) 3D (1.0/2), p value < 0.001; 2D axial (1.0/2), p value < 0.001; and 2D sagittal sequences (1.0/2), p value < 0.001. • Interobserver agreement for major variables of interest was similar among all sequences and reconstruction types. For foraminal stenosis, κ ranged from 0.55 to 0.76 (95% CI 0.32-0.86) for 3D DLRecon, 0.56-0.73 (95% CI 0.35-0.84) for standard-of-care (SOC) 3D, and 0.58-0.71 (95% CI 0.33-0.84) for 2D., (© 2022. The Author(s), under exclusive licence to European Society of Radiology.)

Purpose: To develop a deep-learning model that leverages the spatial and temporal information from dynamic contrast-enhanced magnetic resonance (DCE MR) brain imaging in order to automatically estimate a vascular function (VF) for quantitative pharmacokinetic (PK) modeling., Methods: Patients with glioblastoma multiforme were scanned post-resection approximately every 2 months using a high spatial and temporal resolution DCE MR imaging sequence ( ≈ 5 s and ≈ 2 cm 3 ). A region over the transverse sinus was manually drawn in the dynamic T1-weighted images to provide a ground truth VF. The manual regions and their resulting VF curves were used to train a deep-learning model based on a 3D U-net architecture. The model concurrently utilized the spatial and temporal information in DCE MR images to predict the VF. In order to analyze the contribution of the spatial and temporal terms, different weighted combinations were examined. The manual and deep-learning predicted regions and VF curves were compared., Results: Forty-three patients were enrolled in this study and 155 DCE MR scans were processed. The 3D U-net was trained using a loss function that combined the spatial and temporal information with different weightings. The best VF curves were obtained when both spatial and temporal information were considered. The predicted VF curve was similar to the manual ground truth VF curves., Conclusion: The use of spatial and temporal information improved VF curve prediction relative to when only the spatial information is used. The method generalized well for unseen data and can be used to automatically estimate a VF curve suitable for quantitative PK modeling. This method allows for a more efficient clinical pipeline and may improve automation of permeability mapping., (© 2021 International Society for Magnetic Resonance in Medicine.)

Objective: To assess a new deep learning-based MR reconstruction method, "DLRecon," for clinical evaluation of peripheral nerves., Methods: Sixty peripheral nerves were prospectively evaluated in 29 patients (mean age: 49 ± 16 years, 17 female) undergoing standard-of-care (SOC) MR neurography for clinically suspected neuropathy. SOC-MRIs and DLRecon-MRIs were obtained through conventional and DLRecon reconstruction methods, respectively. Two radiologists randomly evaluated blinded images for outer epineurium conspicuity, fascicular architecture visualization, pulsation artifact, ghosting artifact, and bulk motion., Results: DLRecon-MRIs were likely to score better than SOC-MRIs for outer epineurium conspicuity (OR = 1.9, p = 0.007) and visualization of fascicular architecture (OR = 1.8, p < 0.001) and were likely to score worse for ghosting (OR = 2.8, p = 0.004) and pulsation artifacts (OR = 1.6, p = 0.004). There was substantial to almost-perfect inter-reconstruction method agreement (AC = 0.73-1.00) and fair to almost-perfect interrater agreement (AC = 0.34-0.86) for all features evaluated. DLRecon-MRI had improved interrater agreement for outer epineurium conspicuity (AC = 0.71, substantial agreement) compared to SOC-MRIs (AC = 0.34, fair agreement). In >80% of images, the radiologist correctly identified an image as SOC- or DLRecon-MRI., Discussion: Outer epineurium and fascicular architecture conspicuity, two key morphological features critical to evaluating a nerve injury, were improved in DLRecon-MRIs compared to SOC-MRIs. Although pulsation and ghosting artifacts increased in DLRecon images, image interpretation was unaffected., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Purpose: To develop and evaluate an efficient precontrast T 1 mapping technique suitable for quantitative high-resolution whole-brain dynamic contrast-enhanced-magnetic resonance imaging (DCE-MRI)., Methods: Variable flip angle (VFA) T 1 mapping was considered that provides 1 × 1 × 2 mm 3 resolution to match a recent high-resolution whole-brain DCE-MRI protocol. Seven FAs were logarithmically spaced from 1.5° to 15°. T 1 and M 0 maps were estimated using model-based reconstruction. This approach was evaluated using an anatomically realistic brain tumor digital reference object (DRO) with noise-mimicking 3T neuroimaging and fully sampled data acquired from one healthy volunteer. Methods were also applied on fourfold prospectively undersampled VFA data from 13 patients with high-grade gliomas., Results: T 1 -mapping precision decreased with undersampling factor R, althoughwhereas bias remained small before a critical R. In the noiseless DRO, T 1 bias was <25 ms in white matter (WM) and <11 ms in brain tumor (BT). T 1 standard deviation (SD) was <119.5 ms in WM (coefficient of variation [COV] ~11.0%) and <253.2 ms in BT (COV ~12.7%). In the noisy DRO, T 1 bias was <50 ms in WM and <30 ms in BT. For R ≤ 10, T 1 SD was <107.1 ms in WM (COV ~9.9%) and <240.9 ms in BT (COV ~12.1%). In the healthy subject, T 1 bias was <30 ms for R ≤ 16. At R = 4, T 1 SD was 171.4 ms (COV ~13.0%). In the prospective brain tumor study, T 1 values were consistent with literature values in WM and BT., Conclusion: High-resolution whole-brain VFA T 1 mapping is feasible with sparse sampling, supporting its use for quantitative DCE-MRI., (© 2021 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background: Deep learning-based methods have been used to denoise magnetic resonance imaging., Purpose: The purpose of this study was to evaluate a deep learning reconstruction (DL Recon) in cardiovascular black-blood T2-weighted images and compare with intensity filtered images., Material and Methods: Forty-five DL Recon images were compared with intensity filtered and the original images. For quantitative image analysis, the signal to noise ratio (SNR) of the septum, contrast ratio (CR) of the septum to lumen, and sharpness of the endocardial border were calculated in each image. For qualitative image quality assessment, a 4-point subjective scale was assigned to each image (1 = poor, 2 = fair, 3 = good, 4 = excellent)., Results: The SNR and CR were significantly higher in the DL Recon images than in the intensity filtered and the original images ( p < .05 in each). Sharpness of the endocardial border was significantly higher in the DL Recon and intensity filtered images than in the original images ( p < .05 in each). The image quality of the DL Recon images was significantly better than that of intensity filtered and original images ( p < .001 in each)., Conclusions: DL Recon reduced image noise while improving image contrast and sharpness in the cardiovascular black-blood T2-weight sequence., Competing Interests: Declarations of conflicting interest: Atsushi Nozaki and R. Marc Lebel are employed by GE Healthcare. All other authors declare that they do not have competing interests., (© The Author(s) 2021.)

Purpose: To evaluate two settings (noise reduction of 50% or 75%) of a deep learning (DL) reconstruction model relative to each other and to conventional MR image reconstructions on clinical orthopedic MRI datasets., Materials and Methods: This retrospective study included 54 patients who underwent two-dimensional fast spin-echo MRI for hip ( n = 22; mean age, 44 years ± 13 [standard deviation]; nine men) or shoulder ( n = 32; mean age, 56 years ± 17; 17 men) conditions between March 2019 and June 2020. MR images were reconstructed with conventional methods and the vendor-provided and commercially available DL model applied with 50% and 75% noise reduction settings (DL 50 and DL 75, respectively). Quantitative analytics, including relative anatomic edge sharpness, relative signal-to-noise ratio (rSNR), and relative contrast-to-noise ratio (rCNR) were computed for each dataset. In addition, the image sets were randomized, blinded, and presented to three board-certified musculoskeletal radiologists for ranking based on overall image quality and diagnostic confidence. Statistical analysis was performed with a nonparametric hypothesis comparing derived quantitative metrics from each reconstruction approach. In addition, inter- and intrarater agreement analysis was performed on the radiologists' rankings., Results: Both denoising settings of the DL reconstruction showed improved edge sharpness, rSNR, and rCNR relative to the conventional reconstructions. The reader rankings demonstrated strong agreement, with both DL reconstructions outperforming the conventional approach (Gwet agreement coefficient = 0.98). However, there was lower agreement between the readers on which DL reconstruction denoising setting produced higher-quality images (Gwet agreement coefficient = 0.31 for DL 50 and 0.35 for DL 75)., Conclusion: The vendor-provided DL MRI reconstruction showed higher edge sharpness, rSNR, and rCNR in comparison with conventional methods; however, optimal levels of denoising may need to be further assessed. Keywords: MRI Reconstruction Method, Deep Learning, Image Analysis, Signal-to-Noise Ratio, MR-Imaging, Neural Networks, Hip, Shoulder, Physics, Observer Performance, Technology Assessment Supplemental material is available for this article. © RSNA, 2021., Competing Interests: Disclosures of Conflicts of Interest: K.M.K. institution received a grant from GE Healthcare. M.S. disclosed no relevant relationships. V.E.A. disclosed no relevant relationships. S.B. disclosed no relevant relationships. R.A. disclosed no relevant relationships. A.S.N. institution received funding from GE Healthcare for work in neuroimaging MRI technology development and dissemination; is an inventor on patents including MRI technology focusing on multispectral imaging and magnetic field measurement and modulation; is a scientific advisor for and holds stock in Vasognosis, a start-up company focused on neurovascular imaging applications. R.M.L. is employed by and holds stock options in GE Healthcare; GE Healthcare has patents pending on the algorithms used in this work, but no money has been received. G.M. is employed by GE Healthcare; has been issued U.S. patent no. US10635943B1. S.S.K. is employed by GE Healthcare; received royalties from the Medical College of Wisconsin for a licensed patent unrelated to this work that was filed in 2015. D.V. disclosed no relevant relationships. M.R.S. disclosed no relevant relationships. S.F. disclosed no relevant relationships. R.M. disclosed no relevant relationships., (2021 by the Radiological Society of North America, Inc.)

Background Advances in sub-Nyquist-sampled dynamic contrast-enhanced (DCE) MRI enable monitoring of brain tumors with millimeter resolution and whole-brain coverage. Such undersampled quantitative methods need careful characterization regarding achievable test-retest reproducibility. Purpose To demonstrate a fully automated high-resolution whole-brain DCE MRI pipeline with 30-fold sparse undersampling and estimate its reproducibility on the basis of reference regions of stable tissue types during multiple posttreatment time points by using longitudinal clinical images of high-grade glioma. Materials and Methods Two methods for sub-Nyquist-sampled DCE MRI were extended with automatic estimation of vascular input functions. Continuously acquired three-dimensional k-space data with ramped-up flip angles were partitioned to yield high-resolution, whole-brain tracer kinetic parameter maps with matched precontrast-agent T1 and M 0 maps. Reproducibility was estimated in a retrospective study in participants with high-grade glioma, who underwent three consecutive standard-of-care examinations between December 2016 and April 2019. Coefficients of variation and reproducibility coefficients were reported for histogram statistics of the tracer kinetic parameters plasma volume fraction and volume transfer constant (K trans ) on five healthy tissue types. Results The images from 13 participants (mean age ± standard deviation, 61 years ± 10; nine women) with high-grade glioma were evaluated. In healthy tissues, the protocol achieved a coefficient of variation less than 57% for median K trans , if K trans was estimated consecutively. The maximum reproducibility coefficient for median K trans was estimated to be at 0.06 min -1 for large or low-enhancing tissues and to be as high as 0.48 min -1 in smaller or strongly enhancing tissues. Conclusion A fully automated, sparsely sampled DCE MRI reconstruction with patient-specific vascular input function offered high spatial and temporal resolution and whole-brain coverage; in healthy tissues, the protocol estimated median volume transfer constant with maximum reproducibility coefficient of 0.06 min -1 in large, low-enhancing tissue regions and maximum reproducibility coefficient of less than 0.48 min -1 in smaller or more strongly enhancing tissue regions. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Lenkinski in this issue.

Objectives: The aim of this study was to assess the effect of a deep learning (DL)-based reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to evaluate its influence on scar quantification., Methods: Sixty patients (46 ± 17 years, 50% male) with suspected or known cardiomyopathy underwent CMR. Short-axis LGE images were reconstructed using the conventional reconstruction and a DL network (DLRecon) with tunable noise reduction (NR) levels from 0 to 100%. Image quality of standard LGE images and DLRecon images with 75% NR was scored using a 5-point scale (poor to excellent). In 30 patients with LGE, scar size was quantified using thresholding techniques with different standard deviations (SD) above remote myocardium, and using full width at half maximum (FWHM) technique in images with varying NR levels., Results: DLRecon images were of higher quality than standard LGE images (subjective quality score 3.3 ± 0.5 vs. 3.6 ± 0.7, p < 0.001). Scar size increased with increasing NR levels using the SD methods. With 100% NR level, scar size increased 36%, 87%, and 138% using 2SD, 4SD, and 6SD quantification method, respectively, compared to standard LGE images (all p values < 0.001). However, with the FWHM method, no differences in scar size were found (p = 0.06)., Conclusions: LGE image quality improved significantly using a DL-based reconstruction algorithm. However, this algorithm has an important impact on scar quantification depending on which quantification technique is used. The FWHM method is preferred because of its independency of NR. Clinicians should be aware of this impact on scar quantification, as DL-based reconstruction algorithms are being used., Key Points: • The image quality based on (subjective) visual assessment and image sharpness of late gadolinium enhancement images improved significantly using a deep learning-based reconstruction algorithm that aims to reconstruct high signal-to-noise images using a denoising technique. • Special care should be taken when scar size is quantified using thresholding techniques with different standard deviations above remote myocardium because of the large impact of these advanced image enhancement algorithms. • The full width at half maximum method is recommended to quantify scar size when deep learning algorithms based on noise reduction are used, as this method is the least sensitive to the level of noise and showed the best agreement with visual late gadolinium enhancement assessment.

In vivo quantification of glutamate (Glu) and γ-aminobutyric acid (GABA) using MRS is often achieved using two separate sequences: a short-echo point resolved spectroscopy (PRESS) acquisition for Glu and a Mescher-Garwood PRESS (MEGA-PRESS) acquisition for GABA. The purpose of this study was to examine the agreement of Glu and Glx (the combined signal of glutamate + glutamine) quantified from two different GABA-edited MEGA-PRESS acquisitions (GABA plus macromolecules, GABA+, T E = 68 ms, and macromolecule suppressed, MMSup, T E = 80 ms) with Glu and Glx quantified from a short-echo PRESS (PRESS-35, T E = 35 ms) acquisition. Fifteen healthy male volunteers underwent a single scan session, in which data were acquired using the three acquisitions (GABA+, MMSup and PRESS-35) in both the sensorimotor and anterior cingulate cortices using a voxel size of 3 × 3 × 3 cm 3 . Glx and Glu were quantified from the MEGA-PRESS data using both the OFF sub-spectra and the difference (DIFF) spectra. Agreement was assessed using correlation analyses, Bland-Altman plots and intraclass correlation coefficients. Glx quantified from the OFF sub-spectra from both the GABA+ and MMSup acquisitions showed poor agreement with PRESS-35 in both brain regions. In the sensorimotor cortex, Glu quantified from the OFF sub-spectra of GABA+ showed moderate agreement with PRESS-35 data, but this finding was not replicated in the anterior cingulate cortex. Glx and Glu quantified using the DIFF spectra of either MEGA-PRESS sequence were in poor agreement with the PRESS-35 data in both brain regions. In conclusion, Glx and Glu measured from MEGA-PRESS data generally showed poor agreement with Glx and Glu measured using PRESS-35., (© 2020 John Wiley & Sons, Ltd.)

Purpose: To demonstrate the feasibility of integrating the magnetization transfer (MT) preparations required for inhomogeneous MT (ihMT) within an MPRAGE-style acquisition. Such a sequence allows for reduced power deposition and easy inclusion of other modules., Methods: An ihMT MPRAGE-style sequence (ihMTRAGE) was initially simulated to investigate acquisition of the 3D ihMT data sequentially, or in an interleaved manner. The ihMTRAGE sequence was implemented on a 3T clinical scanner to acquire ihMT data from the brain and spine., Results: Both simulations and in vivo data provided an ihMT signal that was significantly greater using a sequential ihMTRAGE acquisition, compared with an interleaved implementation. Comparison with a steady-state ihMT acquisition (defined as having one MT RF pulse between successive acquisition modules) demonstrated how ihMTRAGE allows for a reduction in average power deposition, or greater ihMT signal at equal average power deposition. Inclusion of a prospective motion-correction module did not significantly affect the ihMT signal obtained from regions of interest in the brain. The ihMTRAGE acquisition allowed combination with a spatial saturation module to reduce phase wrap artifacts in a cervical spinal cord acquisition., Conclusions: Use of preparations necessary for ihMT experiments within an MPRAGE-style sequence provides a useful alternative for acquiring 3D ihMT data. Compared with our steady-state implementation, ihMTRAGE provided reduced power deposition, while allowing use of the maximum intensity from off-resonance RF pulses. The 3D ihMTRAGE acquisition allowed combination of other modules with the preparation necessary for ihMT experiments, specifically motion compensation and spatial saturation modules., (© 2020 International Society for Magnetic Resonance in Medicine.)

Background: Arterial Spin Labeling (ASL) MRI can provide quantitative images that are sensitive to both time averaged blood flow and its temporal fluctuations. 3D image acquisitions for ASL are desirable because they are more readily compatible with background suppression to reduce noise, can reduce signal loss and distortion, and provide uniform flow sensitivity across the brain. However, single-shot 3D acquisition for maximal temporal resolution typically involves degradation of image quality through blurring or noise amplification by parallel imaging. Here, we report a new approach to accelerate a common stack of spirals 3D image acquisition by pseudo golden-angle rotation and compressed sensing reconstruction without any degradation of time averaged blood flow images., Methods: 28 healthy volunteers were imaged at 3T with background-suppressed unbalanced pseudo-continuous ASL combined with a pseudo golden-angle Stack-of-Spirals 3D RARE readout. A fully-sampled perfusion-weighted volume was reconstructed by 3D non-uniform Fast Fourier Transform (nuFFT) followed by sum-of-squares combination of the 32 individual channels. Coil sensitivities were estimated followed by reconstruction of the 39 single-shot volumes using an L 1 -wavelet Compressed-Sensing reconstruction. Finally, brain connectivity analyses were performed in regions where BOLD signal suffers from low signal-to-noise ratio and susceptibility artifacts., Results: Image quality, assessed with a non-reference 3D blurring metric, of full time averaged blood flow was comparable to a conventional interleaved acquisition. The temporal resolution provided by the acceleration enabled identification and quantification of resting-state networks even in inferior regions such as the amygdala and inferior frontal lobes, where susceptibility artifacts can degrade conventional resting-state fMRI acquisitions., Conclusion: This approach can provide measures of blood flow modulations and resting-state networks for free within any research or clinical protocol employing ASL for resting blood flow., Competing Interests: Declaration of Competing Interest D.C.A. receives research support from GE Healthcare. Additionally, he receives postmarket royalties through his institution from GE Healthcare, Siemens Healthineers, Philips Medical, Hitachi, and Animage LLC for patents related to the PCASL technique used in this study. R.M.L. and A.G. work for GE Healthcare., (Copyright © 2020. Published by Elsevier Inc.)

The U-net is a deep-learning network model that has been used to solve a number of inverse problems. In this work, the concatenation of two-element U-nets, termed the W-net, operating in k-space (K) and image (I) domains, were evaluated for multi-channel magnetic resonance (MR) image reconstruction. The two-element network combinations were evaluated for the four possible image-k-space domain configurations: a) W-net II, b) W-net KK, c) W-net IK, and d) W-net KI. Selected four element (WW-nets) and six element (WWW-nets) networks were also examined. Two configurations of each network were compared: 1) each coil channel was processed independently, and 2) all channels were processed simultaneously. One hundred and eleven volumetric, T1-weighted, 12-channel coil k-space datasets were used in the experiments. Normalized root mean squared error, peak signal-to-noise ratio and visual information fidelity were used to assess the reconstructed images against the fully sampled reference images. Our results indicated that networks that operate solely in the image domain were better when independently processing individual channels of multi-channel data. Dual-domain methods were better when simultaneously reconstructing all channels of multi-channel data. In addition, the best cascade of U-nets performed better (p < 0.01) than the previously published, state-of-the-art Deep Cascade and Hybrid Cascade models in three out of four experiments., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The role of white matter in reading has been established by diffusion tensor imaging (DTI), but DTI cannot identify specific microstructural features driving these relationships. Neurite orientation dispersion and density imaging (NODDI), inhomogeneous magnetization transfer (ihMT) and multicomponent driven equilibrium single-pulse observation of T1/T2 (mcDESPOT) can be used to link more specific aspects of white matter microstructure and reading due to their sensitivity to axonal packing and fiber coherence (NODDI) and myelin (ihMT and mcDESPOT). We applied principal component analysis (PCA) to combine DTI, NODDI, ihMT and mcDESPOT measures (10 in total), identify major features of white matter structure, and link these features to both reading and age. Analysis was performed for nine reading-related tracts in 46 neurotypical 6-16 year olds. We identified three principal components (PCs) which explained 79.5% of variance in our dataset. PC1 probed tissue complexity, PC2 described myelin and axonal packing, while PC3 was related to axonal diameter. Mixed effects regression models did not identify any significant relationships between principal components and reading skill. Bayes factor analysis revealed that the absence of relationships was not due to low power. Increasing PC1 in the left arcuate fasciculus with age suggest increases in tissue complexity, while increases of PC2 in the bilateral arcuate, inferior longitudinal, inferior fronto-occipital fasciculi, and splenium suggest increases in myelin and axonal packing with age. Multimodal white matter imaging and PCA provide microstructurally informative, powerful principal components which can be used by future studies of development and cognition. Our findings suggest major features of white matter undergo development during childhood and adolescence, but changes are not linked to reading during this period in our typically-developing sample., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: Author RML is an employee of GE Healthcare. The funder provided support in the form of salaries for author RML, but played no other role in this study. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Arterial spin labeling (ASL) MRI can provide seizure onset zone (SOZ) localizing information in up to 80% of patients. Clinical implementation of this technique is limited by the need to obtain two scans per patient: a postictal scan that is subtracted from an interictal scan. We aimed to determine whether it is possible to limit the number of ASL scans to one per patient by comparing patient postictal ASL scans to baseline scans of 100 healthy controls. Eighteen patients aged 20-55 years underwent ASL MRI <90 min after a seizure and during the interictal period. Each postictal cerebral blood flow (CBF) map was statistically compared to average baseline CBF maps from 100 healthy controls (pvcASL; patient postictal CBF vs. control baseline CBF). The pvcASL maps were compared to subtraction ASL maps (sASL; patient baseline CBF minus patient postictal CBF). Postictal CBF reductions from pvcASL and sASL maps were seen in 17 of 18 (94.4%) and 14 of 18 (77.8%) patients, respectively. Maximal postictal hypoperfusion seen in pvcASL and sASL maps was concordant with the SOZ in 10 of 17 (59%) and 12 of 14 (86%) patients, respectively. In seven patients, both pvcASL and sASL maps showed similar results. In two patients, sASL showed no significant hypoperfusion, while pvcASL showed significant hypoperfusion concordant with the SOZ. We conclude that pvcASL is clinically useful and although it may have a lower overall concordance rate than sASL, pvcASL does provide localizing or lateralizing information for specific cases that would be otherwise missed through sASL., (© 2020 Wiley Periodicals LLC.)

Primary Objective: The neurophysiological effects of pediatric concussion several years after injury remain inadequately characterized. The objective of this study was to determine if a history of concussion was associated with BOLD response differences during an n-back working memory task in youth., Research Design: Observational, cross-sectional., Methods and Procedures: Participants include 52 children and adolescents (M = 15.1 years, 95%CI = 14.4-15.8, range = 9-19) with past concussion (n = 33) or orthopedic injury (OI; n = 19). Mean time since injury was 2.5 years (95%CI = 2.0-3.0). Measures included postconcussion symptom ratings, neuropsychological testing, and blood-oxygen-dependent-level (BOLD) functional magnetic resonance imaging (fMRI) during an n-back working memory task., Main Outcomes and Results: Groups did not differ on accuracy or speed during the three n-back conditions. They also did not differ in BOLD signal change for the 1- vs. 0-back or 2- vs. 0-back contrasts (controlling for task performance)., Conclusions: This study does not support group differences in BOLD response during an n-back working memory task in youth who are on average 2.5 years post-concussion. The findings are encouraging from the perspective of understanding recovery after pediatric concussion.

Background: Arterial spin labeling (ASL) can be confounded by varying arterial transit times (ATT) across the brain and with disease. Hadamard encoding schemes can be applied to 3D pseudocontinuous ASL (pCASL) to acquire ASL data with multiple postlabeling delays (PLDs) to estimate ATT and then correct cerebral blood flow (CBF)., Purpose: To assess the longitudinal reproducibility of 3D pCASL with Hadamard-encoded multiple PLDs., Study Type: Prospective, longitudinal., Population: Fifty-two healthy, right-handed male subjects who underwent imaging at four timepoints over 45 days., Field Strength/sequence: A Hadamard-encoded 3D pCASL sequence was acquired at 3.0T with seven PLDs from 1.0-3.7 sec., Assessment: ATT and corrected CBF (cCBF) were computed. Conventional uncorrected CBF (unCBF) was also estimated. Within- and between-subject coefficient of variation (wCV and bCV, respectively) and intraclass correlation coefficient (ICC) were evaluated across four time intervals: 7, 14, 30, and 45 days, in gray matter and 17 independent regions of interest (ROIs). A power analysis was also conducted., Statistical Tests: A repeated-measures analysis of variance (ANOVA) was used to compare ATT, cCBF, and unCBF across the four scan sessions. A paired two-sample t-test was used to compare cCBF and unCBF. Pearson's correlation was used to examine the relationship between the cCBF and unCBF difference and ATT. Power calculations were completed using both the cCBF and unCBF variances., Results: ATT showed the lowest wCV and bCV (3.3-4.4% and 6.0-6.3%, respectively) compared to both cCBF (10.5-11.7% and 20.6-22.2%, respectively) and unCBF (12.0-13.6% and 22.7-23.7%, respectively). wCV and bCV were lower for cCBF vs. unCBF. A significant difference between cCBF and unCBF was found in most regions (P = 5.5 × 10 -5 -3.8 × 10 -4 in gray matter) that was highly correlated with ATT (R 2 = 0.79-0.86). A power analysis yielded acceptable power at feasible sample sizes using cCBF., Data Conclusion: ATT and ATT-corrected CBF were longitudinally stable, indicating that ATT and CBF changes can be reliably evaluated with Hadamard-encoded 3D pCASL with multiple PLDs., Level of Evidence: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1846-1853., (© 2019 International Society for Magnetic Resonance in Medicine.)

Background The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brain was disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linear mixed-effects models (denoted P boot ). Results In total, 296 participants (mean age, 26 years ± 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N -acetylaspartate (range, 4.4-5.0 Hz), signal-to-noise ratio (range, 174-289), and low Cramér-Rao lower bounds (≤5%) for all of the major metabolites. Among the major metabolites, no vendor effects were found for levels of myo-inositol ( P boot > .90), N -acetylaspartate and N -acetylaspartylglutamate ( P boot = .13), or glutamate and glutamine ( P boot = .11). Among the smaller resonances, no vendor effects were found for ascorbate ( P boot = .08), aspartate ( P boot > .90), glutathione ( P boot > .90), or lactate ( P boot = .28). Conclusion Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coherent across vendors, provided that vendor differences in pulse sequence implementation are accounted for in data analysis. However, the site-related effects on variability were more profound and suggest the need for further standardization of spectroscopic protocols. © RSNA, 2020 Online supplemental material is available for this article.

Objectives: We attempted to demonstrate the clinical applicability and utility of a three-dimensional multidelay arterial spin labeling magnetic resonance imaging technique in pediatric neuroimaging through a series of case studies., Methods: Whole-brain three-dimensional multidelay arterial spin labeling data were acquired in five pediatric patients with different neurological conditions using 3 mm to 4 mm slices and a scan time of six to seven minutes., Results: Three-dimensional multidelay arterial spin labeling provided complementary diagnostic information via quantitative cerebral blood flow and arterial transit time maps., Conclusions: Three-dimensional multidelay arterial spin labeling sequence provides simultaneous quantification of cerebral blood flow and arterial transit time and is feasible for pediatric patients., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Adequate cerebral blood flow (CBF) is essential to proper brain development and function. Detailed characterization of CBF developmental trajectories will lead to better understanding of the development of cognitive, motor, and sensory functions, as well as behaviour in children. Previous studies have shown CBF increases during infancy and decreases during adolescence; however, the trajectories during childhood, and in particular the timing of peak CBF, remain unclear. Here, we used arterial spin labeling to map age-related changes of CBF across a large longitudinal sample that included 279 scans on 96 participants (46 girls and 50 boys) aged 2-7 years. CBF maps were analyzed using hierarchical linear regression for every voxel inside the grey matter mask, controlling for multiple comparisons. The results revealed a significant positive linear association between CBF and age in distributed brain regions including prefrontal, temporal, parietal, and occipital cortex, and in the cerebellum. There were no differences in developmental trajectories between males and females. Our findings show that CBF continues to increase until the age of 7 years, likely supporting ongoing improvements in behaviour, cognition, motor, and sensory functions in early childhood., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Purpose: To apply tracer kinetic models as temporal constraints during reconstruction of under-sampled brain tumor dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI)., Methods: A library of concentration vs time profiles is simulated for a range of physiological kinetic parameters. The library is reduced to a dictionary of temporal bases, where each profile is approximated by a sparse linear combination of the bases. Image reconstruction is formulated as estimation of concentration profiles and sparse model coefficients with a fixed sparsity level. Simulations are performed to evaluate modeling error, and error statistics in kinetic parameter estimation in presence of noise. Retrospective under-sampling experiments are performed on a brain tumor DCE digital reference object (DRO), and 12 brain tumor in-vivo 3T datasets. The performances of the proposed under-sampled reconstruction scheme and an existing compressed sensing-based temporal finite-difference (tFD) under-sampled reconstruction were compared against the fully sampled inverse Fourier Transform-based reconstruction., Results: Simulations demonstrate that sparsity levels of 2 and 3 model the library profiles from the Patlak and extended Tofts-Kety (ETK) models, respectively. Noise sensitivity analysis showed equivalent kinetic parameter estimation error statistics from noisy concentration profiles, and model approximated profiles. DRO-based experiments showed good fidelity in recovery of kinetic maps from 20-fold under-sampled data. In-vivo experiments demonstrated reduced bias and uncertainty in kinetic mapping with the proposed approach compared to tFD at under-sampled reduction factors >= 20., Conclusions: Tracer kinetic models can be applied as temporal constraints during brain tumor DCE-MRI reconstruction. The proposed under-sampled scheme resulted in model parameter estimates less biased with respect to conventional fully sampled DCE MRI reconstructions and parameter estimation. The approach is flexible, can use nonlinear kinetic models, and does not require tuning of regularization parameters., (© 2019 American Association of Physicists in Medicine.)

Objective: Purely exponential decay is rarely observed in conventional mono-exponential T 2 mapping due to transmit field inhomogeneity and calibration errors, which collectively introduce stimulated and indirect echo pathways. Stimulated echo correction (SEC) requires an additional fit parameter for the transmit field, resulting in greater uncertainty in T 2 relative to mono-exponential fitting. The aim of this study was to develop an accurate and precise method for T 2 mapping using SEC., Methods: The proposed method, called two-step SEC (tSEC), leverages spatial correlations in the transmit field to reduce the number of fully independent fitting parameters from three to two. The method involves a two-pass fit: the first pass involves a fast but standard SEC fit. The initially estimated transmit field is smoothed and provided as a fixed input to the second pass., Results: Simulations and in vivo experiments demonstrated up to 38% and 27% decreases in relative T 2 variance with tSEC relative to SEC. Average T 2 values were unchanged between tSEC and SEC fits. The proposed method uses the same input data as SEC and exponential fits, so it is applicable to existing data., Discussion: The proposed method generates reliable and reproducible quantitative T 2 maps and should be considered for future relaxometry studies.

White matter development has been well described using diffusion tensor imaging (DTI), but the microstructural processes driving development remain unclear due to methodological limitations. Here, using neurite orientation dispersion and density imaging (NODDI), inhomogeneous magnetization transfer (ihMT), and multicomponent driven equilibrium single-pulse observation of T1/T2 (mcDESPOT), we describe white matter development at the microstructural level in a longitudinal cohort of healthy 6-15 year olds. We evaluated age and gender-related trends in fractional anisotropy (FA), mean diffusivity (MD), neurite density index (NDI), orientation dispersion index (ODI), quantitative ihMT (qihMT), myelin volume fraction (VF m ), and g-ratio. We found age-related increases of VF m in most regions, showing ongoing myelination in vivo during late childhood and adolescence for the first time. No relationship was observed between qihMT and age, suggesting myelin volume increases are driven by increased water content. Age-related increases were observed for NDI, suggesting axonal packing is also occurring during this time. g-ratio decreased with age in the uncinate fasciculus, implying changes in communication efficiency are ongoing in this region. FA increased and MD decreased with age in most regions. Gender effects were present in the left cingulum for FA, and an age-by-gender interaction was found for MD in the left uncinate fasciculus. These findings suggest that FA and MD remain useful markers of gender-related processes, and gender differences are likely driven by factors other than myelin. We conclude that white matter development during late childhood and adolescence is driven by a combination of axonal packing and myelin volume increases., (© 2019 Wiley Periodicals, Inc.)

Accurate and reliable quantification of brain metabolites measured in vivo using 1 H magnetic resonance spectroscopy (MRS) is a topic of continued interest. Aside from differences in the basic approach to quantification, the quantification of metabolite data acquired at different sites and on different platforms poses an additional methodological challenge. In this study, spectrally edited γ-aminobutyric acid (GABA) MRS data were analyzed and GABA levels were quantified relative to an internal tissue water reference. Data from 284 volunteers scanned across 25 research sites were collected using GABA+ (GABA + co-edited macromolecules (MM)) and MM-suppressed GABA editing. The unsuppressed water signal from the volume of interest was acquired for concentration referencing. Whole-brain T 1 -weighted structural images were acquired and segmented to determine gray matter, white matter and cerebrospinal fluid voxel tissue fractions. Water-referenced GABA measurements were fully corrected for tissue-dependent signal relaxation and water visibility effects. The cohort-wide coefficient of variation was 17% for the GABA + data and 29% for the MM-suppressed GABA data. The mean within-site coefficient of variation was 10% for the GABA + data and 19% for the MM-suppressed GABA data. Vendor differences contributed 53% to the total variance in the GABA + data, while the remaining variance was attributed to site- (11%) and participant-level (36%) effects. For the MM-suppressed data, 54% of the variance was attributed to site differences, while the remaining 46% was attributed to participant differences. Results from an exploratory analysis suggested that the vendor differences were related to the unsuppressed water signal acquisition. Discounting the observed vendor-specific effects, water-referenced GABA measurements exhibit similar levels of variance to creatine-referenced GABA measurements. It is concluded that quantification using internal tissue water referencing is a viable and reliable method for the quantification of in vivo GABA levels., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objective: To construct a clinical diagnostic biomarker using state-of-the-art microstructural MRI in the motor cortex of people with amyotrophic lateral sclerosis (ALS)., Methods: Clinical and MRI data were obtained from 21 ALS patients (aged 54 ± 14 years, 33% female) and 63 age- and gender-matched controls (aged 48 ± 18 years, 43% female). MRI was acquired at 3T and included T1-weighted scan (for volumetrics), arterial spin labelling (for cerebral blood flow), susceptibility-weighted angiography (for iron deposition) and multiband diffusion kurtosis imaging (for tissue microstructure). Group differences in imaging measures in the motor cortex were tested by general linear model and relationships to clinical variables by linear regression., Results: The ALS group had mild-to-moderate impairment (disease duration: 1.8 ± 0.8 years; ALS functional rating scale 40.2 ± 6.0; forced vital capacity 83% ± 22%). No age or gender differences were present between groups. We found significant group differences in diffusion kurtosis metrics (apparent, mean, radial and axial kurtosis: p < .01) and iron deposition in the motor cortex (p = .03). Within the ALS group, we found significant relationships between motor cortex volume, apparent diffusion and disease duration (adjusted R 2  = 0.27, p = .011); and between the apparent and radial kurtosis metrics and ALS functional rating scale (adjusted R 2  = 0.25, p = .033). A composite imaging biomarker comprising kurtosis and iron deposition measures yielded a maximal diagnostic accuracy of 83% (81% sensitivity, 85% specificity) and an area-under-the-curve of 0.86., Conclusion: Diffusion kurtosis is sensitive to early changes present in the motor region in ALS. We propose a composite imaging biomarker reflecting tissue microstructural changes in early ALS that may provide clinically valuable diagnostic information., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: The long-term effects of concussion in youth remain poorly understood. The objective of this study was to determine the association between history of concussion and cerebral blood flow (CBF) in youth., Methods: A total of 53 children and adolescents with a history of concussion (n = 37) or orthopaedic injury (OI; n = 16) were considered. Measures included pseudo-continuous arterial spin labelling magnetic resonance imaging to quantify CBF, post-concussion symptoms, psychological symptoms, and cognitive testing., Results: Participants (mean age: 14.4 years, 95% CI = 13.8-15.4, range = 8-19) were on average 2.7 years (95% CI = 2.2-3.1) post-injury. Youth with a history of concussion had higher parent-reported physical, cognitive, anxiety, and depression symptoms than children with OI, but the groups did not differ on self-reported symptoms (post-concussive or psychological) or cognitive testing. Global CBF did not differ between groups. Regional CBF analyses suggested that youth with a history of concussion had hypoperfusion in posterior and inferior regions and hyperperfusion in anterior/frontal/temporal regions as compared to those with OI. However, neither global nor regional CBF were significantly associated with demographics, pre-injury functioning, number of concussions, time since injury, post-concussive symptoms, psychological symptoms, or cognitive abilities., Conclusions: Youth with a history of concussion demonstrate differences in regional CBF (not global CBF), but without clear clinical expression.

Sensitive and specific biomarkers of myelin can help define baseline brain health and development, identify and monitor disease pathology, and evaluate response to treatment where myelin content is affected. Diffusion measures such as radial diffusivity (RD) are commonly used to assess myelin content, but are not specific to myelin. Inhomogeneous magnetization transfer (ihMT) and multicomponent driven equilibrium single-pulse observation of T1 and T2 (mcDESPOT) offer quantitative parameters (qihMT and myelin volume fraction/VF m , respectively) which are suggested to have improved sensitivity to myelin. We compared RD, qihMT, and VF m in a cohort of 23 healthy children aged 8-13 years to evaluate the similarities and differences across these measures. All 3 measures were significantly related across brain voxels, but VF m and qihMT were significantly more strongly correlated (qihMT-VF m r = 0.89) than either measure was with RD (RD-qihMT r = -0.66, RD-VF m r = -0.74; all p < 0.001). Mean parameters differed in several regions, especially in subcortical gray matter. These differences can likely be explained by unique sensitivities of each measure to non-myelin factors, such as crossing fiber geometry, axonal packing, fiber orientation, glial density, or magnetization transfer effects in a voxel. We also observed an orientation dependence of qihMT in white matter, such that qihMT decreased as fiber orientation went from parallel to perpendicular to B 0 . All measures appear to be sensitive to myelin content, though qihMT and VF m appear to be more specific to it than RD. Scan time, noise tolerance, and resolution requirements may inform researchers of the appropriate measure to choose for a specific application., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background and Purpose: Multidelay arterial spin-labeling is a promising emerging method in clinical practice. The effect of imaging parameters in multidelay arterial spin-labeling on estimated cerebral blood flow measurements remains unknown. We directly compared 3-delay versus 7-delay sequences, assessing the difference in the estimated transit time and blood flow., Materials and Methods: This study included 87 cognitively healthy controls (78.7 ± 3.8 years of age; 49 women). We assessed delay and transit time-uncorrected and transit time-corrected CBF maps. Data analysis included voxelwise permutation-based between-sequence comparisons of 3-delay versus 7-delay, within-sequence comparison of transit time-uncorrected versus transit time-corrected maps, and average CBF calculations in regions that have been shown to differ., Results: The 7-delay sequence estimated a higher CBF value than the 3-delay for the transit time-uncorrected and transit time-corrected maps in regions corresponding to the watershed areas (transit time-uncorrected = 27.62 ± 12.23 versus 24.58 ± 11.70 mL/min/100 g, Cohen's d = 0.25; transit time-corrected = 33.48 ± 14.92 versus 30.16 ± 14.32 mL/min/100 g, Cohen's d = 0.23). In the peripheral regions of the brain, the estimated delay was found to be longer for the 3-delay sequence (1.52408 ± 0.25236 seconds versus 1.47755 ± 0.24242 seconds, Cohen's d = 0.19), while the inverse was found in the center of the brain (1.39388 ± 0.22056 seconds versus 1.42565 ± 0.21872 seconds, Cohen's d = 0.14). Moreover, 7-delay had lower hemispheric asymmetry., Conclusions: The results of this study support the necessity of standardizing acquisition parameters in multidelay arterial spin-labeling and identifying basic parameters as a confounding factor in CBF quantification studies. Our findings conclude that multidelay arterial spin-labeling sequences with a high number of delays estimate higher CBF values than those with a lower number of delays., (© 2018 by American Journal of Neuroradiology.)

Purpose: To develop and evaluate a model-based reconstruction framework for joint arterial input function (AIF) and kinetic parameter estimation from undersampled brain tumor dynamic contrast-enhanced MRI (DCE-MRI) data., Methods: The proposed method poses the tracer-kinetic (TK) model as a model consistency constraint, enabling the flexible inclusion of different TK models and TK solvers, and the joint estimation of the AIF. The proposed method is evaluated using an anatomic realistic digital reference object (DRO), and nine retrospectively down-sampled brain tumor DCE-MRI datasets. We also demonstrate application to 30-fold prospectively undersampled brain tumor DCE-MRI., Results: In DRO studies with up to 60-fold undersampling, the proposed method provided TK maps with low error that were comparable to fully sampled data and were demonstrated to be compatible with a third-party TK solver. In retrospective undersampling studies, this method provided patient-specific AIF with normalized root mean-squared-error (normalized by the 90th percentile value) less than 8% at up to 100-fold undersampling. In the 30-fold undersampled prospective study, the proposed method provided high-resolution whole-brain TK maps and patient-specific AIF., Conclusion: The proposed model-based DCE-MRI reconstruction enables the use of different TK solvers with a model consistency constraint and enables joint estimation of patient-specific AIF. TK maps and patient-specific AIF with high fidelity can be reconstructed at up to 100-fold undersampling in k,t-space. Magn Reson Med 79:2804-2815, 2018. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Purpose: This study aimed to evaluate the usefulness of transit time corrected cerebral blood flow (CBF) maps based on multi-phase arterial spin labeling MR perfusion imaging (ASL-MRP)., Methods: The Institutional Review Board of our hospital approved this retrospective study. Written informed consent was waived. Conventional and multi-phase ASL-MRPs and dynamic susceptibility contrast MR perfusion imaging (DSC-MRP) were acquired for 108 consecutive patients. Vascular territory-based volumes of interest were applied to CBF and time to peak (TTP) maps obtained from DSC-MRP and CBF maps obtained from conventional and multi-phase ASL-MRPs. The concordances between normalized CBF (nCBF) from DSC-MRP and nCBF from conventional and transition time corrected CBF maps from multi-phase ASL-MRP were evaluated using Bland-Altman analysis. In addition, the dependence of difference between nCBF (ΔnCBF) values obtained from DSC-MRP and conventional ASL-MRP (or multi-phase ASL-MRP) on TTP obtained from DSC-MRP was also analyzed using regression analysis., Results: The values of nCBFs from conventional and multi-phase ASL-MRPs had lower values than nCBF based on DSC-MRP (mean differences, 0.08 and 0.07, respectively). The values of ΔnCBF were dependent on TTP values from conventional ASL-MRP technique (F = 5.5679, P = 0.0384). No dependency of ΔnCBF on TTP values from multi-phase ASL-MRP technique was revealed (F = 0.1433, P > 0.05)., Conclusion: The use of transit time corrected CBF maps based on multi-phase ASL-MRP technique can overcome the effect of delayed transit time on perfusion maps based on conventional ASL-MRP.

Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study's protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Purpose: The purpose of this work was to develop and evaluate a T 1 -weighted dynamic contrast enhanced (DCE) MRI methodology where tracer-kinetic (TK) parameter maps are directly estimated from undersampled (k,t)-space data., Theory and Methods: The proposed reconstruction involves solving a nonlinear least squares optimization problem that includes explicit use of a full forward model to convert parameter maps to (k,t)-space, utilizing the Patlak TK model. The proposed scheme is compared against an indirect method that creates intermediate images by parallel imaging and compressed sensing before to TK modeling. Thirteen fully sampled brain tumor DCE-MRI scans with 5-second temporal resolution are retrospectively undersampled at rates R = 20, 40, 60, 80, and 100 for each dynamic frame. TK maps are quantitatively compared based on root mean-squared-error (rMSE) and Bland-Altman analysis. The approach is also applied to four prospectively R = 30 undersampled whole-brain DCE-MRI data sets., Results: In the retrospective study, the proposed method performed statistically better than indirect method at R ≥ 80 for all 13 cases. This approach provided restoration of TK parameter values with less errors in tumor regions of interest, an improvement compared to a state-of-the-art indirect method. Applied prospectively, the proposed method provided whole-brain, high-resolution TK maps with good image quality., Conclusion: Model-based direct estimation of TK maps from k,t-space DCE-MRI data is feasible and is compatible up to 100-fold undersampling. Magn Reson Med 78:1566-1578, 2017. © 2016 International Society for Magnetic Resonance in Medicine., (© 2016 International Society for Magnetic Resonance in Medicine.)

A novel sequence has been introduced that combines multiband imaging with a multi-echo acquisition for simultaneous high spatial resolution pseudo-continuous arterial spin labeling (ASL) and blood-oxygenation-level dependent (BOLD) echo-planar imaging (MBME ASL/BOLD). Resting-state connectivity in healthy adult subjects was assessed using this sequence. Four echoes were acquired with a multiband acceleration of four, in order to increase spatial resolution, shorten repetition time, and reduce slice-timing effects on the ASL signal. In addition, by acquiring four echoes, advanced multi-echo independent component analysis (ME-ICA) denoising could be employed to increase the signal-to-noise ratio (SNR) and BOLD sensitivity. Seed-based and dual-regression approaches were utilized to analyze functional connectivity. Cerebral blood flow (CBF) and BOLD coupling was also evaluated by correlating the perfusion-weighted timeseries with the BOLD timeseries. These metrics were compared between single echo (E2), multi-echo combined (MEC), multi-echo combined and denoised (MECDN), and perfusion-weighted (PW) timeseries. Temporal SNR increased for the MECDN data compared to the MEC and E2 data. Connectivity also increased, in terms of correlation strength and network size, for the MECDN compared to the MEC and E2 datasets. CBF and BOLD coupling was increased in major resting-state networks, and that correlation was strongest for the MECDN datasets. These results indicate our novel MBME ASL/BOLD sequence, which collects simultaneous high-resolution ASL/BOLD data, could be a powerful tool for detecting functional connectivity and dynamic neurovascular coupling during the resting state. The collection of more than two echoes facilitates the use of ME-ICA denoising to greatly improve the quality of resting state functional connectivity MRI.

The biology of post-concussive symptoms is unclear. Symptoms are often increased during activities, and have been linked to decreased cerebrovascular reactivity and perfusion. The aim of this study was to examine cerebral blood flow (CBF) in children with different clinical recovery patterns following mild traumatic brain injury (mTBI). This was a prospective controlled cohort study of children with mTBI (ages 8 to 18 years) who were symptomatic with post-concussive symptoms at one month post-injury (symptomatic, n = 27) and children who had recovered quickly (asymptomatic, n = 24). Pseudo continuous arterial spin labeling magnetic resonance imaging (MRI) was used to quantify CBF. The mTBI groups were imaged at 40 days post-injury. Global and regional CBF were compared with healthy controls of similar age and sex but without a history of mTBI (n = 21). Seventy-two participants (mean age: 14.1 years) underwent neuroimaging. Significant differences in CBF were found: global CBF was higher in the symptomatic group and lower in the asymptomatic group compared with controls, (F(2,69) 9.734; p < 0.001). Post-injury symptom score could be predicted by pre-injury symptoms and CBF in presence of mTBI (adjusted R 2  = 0.424; p < 0.001). Altered patterns of cerebral perfusion are seen following mTBI and are associated with the recovery trajectory. Symptomatic children have higher CBF. Children who "recovered" quickly, have decreased CBF suggesting that clinical recovery precedes the cerebral recovery. Further longitudinal studies are required to determine if these perfusion patterns continue to change over time.

Background: Smaller hippocampal volumes, as assessed by magnetic resonance imaging (MRI), and proton magnetic resonance spectroscopy ( 1 H-MRS) indexed alterations in brain metabolites have been identified in adults with major depressive disorder (MDD). Our group has found similar effects in MDD youth. However, this has not been studied in youth with treatment resistant MDD (TRD), nor has the interaction between regional N-acetyl-aspartate and volume deficits. N-acetyl-aspartate is an amino acid in the synthesis pathway of glutamate, and serves a marker of neuronal viability/number., Methods: Fifteen typically developing youth (16-22 years of age; 7 males, 8 females) and eighteen youth with TRD (14-22 years of age; 8 males, 10 females) underwent 1 H-MRS and MRI on a 3T scanner. A short echo PRESS protocol was used with voxels in the right and left hippocampi (6mL each). Hippocampal volume was evaluated using FreeSurfer., Results: Compared with the typically developing group, youth with TRD had lower concentrations of N-acetyl-aspartate in the left hippocampus (p=0.004), and a trend for smaller left hippocampal volume (p=0.067). In TRD subjects, hippocampal N-acetyl-aspartate was inversely correlated with left (r=-0.68, p=0.003) but not right hippocampal volume. Right hippocampal glutamate+glutamine was greater in TRD youth compared to typically developing controls (p=0.007)., Conclusions: These results suggest a neurochemical and structural deficit in the hippocampi of youth with TRD. These findings fit with the role of N-acetyl-aspartate in glutamate neurotransmission and the effect of glutamate on brain morphology., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Purpose: To develop and evaluate a novel 3D Cartesian sampling scheme which is well suited for time-resolved 3D MRI using parallel imaging and compressed sensing., Methods: The proposed sampling scheme, termed GOlden-angle CArtesian Randomized Time-resolved (GOCART) 3D MRI, is based on golden angle (GA) Cartesian sampling, with random sampling of the ky-kz phase encode locations along each Cartesian radial spoke. This method was evaluated in conjunction with constrained reconstruction of retrospectively and prospectively undersampled in-vivo dynamic contrast enhanced (DCE) MRI data and simulated phantom data., Results: In in-vivo retrospective studies and phantom simulations, images reconstructed from phase encodes defined by GOCART were equal to or superior to those with Poisson disc or GA sampling schemes. Typical GOCART sampling tables were generated in <100ms. GOCART has also been successfully utilized prospectively to produce clinically valuable whole-brain DCE-MRI images., Conclusion: GOCART is a practical and efficient sampling scheme for time-resolved 3D MRI. It shows great potential for highly accelerated DCE-MRI and is well suited to modern reconstruction methods such as parallel imaging and compressed sensing., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Deep gray matter (DGM) is affected in relapsing-remitting multiple sclerosis (RRMS) and may be studied using short-term longitudinal MRI., Objective: To investigate two-year changes in spin-echo transverse relaxation rate (R2) and atrophy in DGM, and its relationship with disease severity in RRMS patients., Methods: Twenty six RRMS patients and 26 matched controls were imaged at 4.7 T. Multiecho spin-echo R2 maps and atrophy measurements were obtained in DGM at baseline and two-year follow-up. Differences between MRI measures and correlations to disease severity were examined., Results: After two years, mean R2 values in the globus pallidus and pulvinar increased by ~4% (p<0.001) in patients and <1.7% in controls. Two-year changes in R2 showed significant correlation to disease severity in the globus pallidus, pulvinar, substantia nigra, and thalamus. Multiple regression of the two-year R2 difference using these four DGM structures as variables, yielded high correlation with disease severity (r=0.83, p<0.001). Two-year changes in volume and R2 showed significant correlation only for the globus pallidus in multiple sclerosis (MS) (p<0.05)., Conclusions: Two-year difference R2 measurements in DGM correlate to disease severity in MS. R2 mapping and atrophy measurements over two years can be used to identify changes in DGM in MS., (© The Author(s), 2015.)

Aim: Structural, functional, and metabolic changes in the dorsolateral prefrontal cortex (DLPFC) are implicated in the pathogenesis of major depressive disorder (MDD). We used proton magnetic resonance spectroscopy ((1) H-MRS) to examine the metabolite choline (glycerophosphocholine plus phosphocholine), which is used as an index of membrane integrity in the left DLPFC, in adolescents and young adults with MDD who were treatment-resistant and had a positive family history compared to healthy controls. Differences in the choline resonance indicate an imbalance between synthesis and degradation activity of neuronal and glia membrane phospholipids., Methods: Seventeen adolescents with MDD and 11 healthy controls underwent (1) H-MRS. A short echo point-resolved spectroscopy (echo time = 30 ms, repetition time = 2000 ms) protocol was used with a voxel (4.5cm(3) , 128 averages) placed within the left DLPFC., Results: There were significantly increased choline (P = 0.04) and creatine concentrations (P = 0.005) in the left DLPFC of the MDD group compared to controls. In MDD participants, choline concentration correlated with scores on the Beck Depression Inventory (r = 0.41, P = 0.03)., Conclusion: Increased left DLPFC choline and creatine levels in depressed adolescents may be biomarkers for the disorder. The increased choline levels may indicate abnormalities in neuronal membrane integrity, and the increased creatine could be reflective of altered energy demands and metabolism., (© 2016 The Authors. Psychiatry and Clinical Neurosciences © 2016 Japanese Society of Psychiatry and Neurology.)

Purpose: To clinically evaluate a highly accelerated T1-weighted dynamic contrast-enhanced (DCE) MRI technique that provides high spatial resolution and whole-brain coverage via undersampling and constrained reconstruction with multiple sparsity constraints., Methods: Conventional (rate-2 SENSE) and experimental DCE-MRI (rate-30) scans were performed 20 minutes apart in 15 brain tumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm(3), FOV 22 × 22 × 4.2 cm(3), and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm(3), and broader coverage 22 × 22 × 19 cm(3). Temporal resolution was 5 s for both protocols. Time-resolved images and blood-brain barrier permeability maps were qualitatively evaluated by two radiologists., Results: The experimental DCE-MRI scans showed no loss of qualitative information in any of the cases, while achieving substantially higher spatial resolution and whole-brain spatial coverage. Average qualitative scores (from 0 to 3) were 2.1 for the experimental scans and 1.1 for the conventional clinical scans., Conclusions: The proposed DCE-MRI approach provides clinically superior image quality with higher spatial resolution and coverage than currently available approaches. These advantages may allow comprehensive permeability mapping in the brain, which is especially valuable in the setting of large lesions or multiple lesions spread throughout the brain.

Purpose: To investigate the brain iron dependence of transverse relaxation rate difference methods derived from spin echo and gradient echo measurements from two field strengths., Methods: Transverse relaxation rates R2 and R2(⁎) were measured in human brain in 17 healthy subjects at 1.5T and 4.7T using multi-slice, multiecho spin echo and gradient echo sequences. R2 quantification used stimulated echo compensation and R2(⁎) quantification used linear background gradient correction at 4.7T only. Subtraction of R2 from R2(⁎) within each field strength yielded R2('), and R2 subtraction across fields yielded Field Dependent R2 Increase (FDRI). All transverse relaxation measures were then correlated with published post-mortem iron concentrations using linear regression analysis. Regional differences were tested using paired t-tests. Phantom measurements of FDRI were also performed., Results: In deep grey matter, all transverse relaxation rates (R2, R2(⁎), R2(')) at both 1.5T and 4.7T, and FDRI had moderate to strong correlations (r>0.71, p<0.0001) with estimated non-heme iron. The 4.7T methods and FDRI had higher correlations (r>0.9) than 1.5T measures. R2, R2(⁎), R2' at 4.7T and FDRI had slopes 0.49, 1.96, 1.48 and 0.33 [s(-1)/mg Fe/100g wt. tissue] and intercepts 14.40, 16.87, 2.47 and 3.21 [s(-1)] respectively. Even though FDRI yielded a zero intercept in phantom, in vivo FDRI was found to be ineffective at fully removing non-iron contributions and yielded a large intercept. The slope for R2(') was 3.4 times greater at 4.7T than 1.5T. For white matter fiber tracts oriented predominantly perpendicular versus parallel to B0, R2(') increased by ~50% at 4.7T and ~30% at 1.5T, while R2 and FDRI in white matter was insensitive to its orientation with respect to B0., Conclusion: The transverse relaxation difference methods FDRI and R2(') at 4.7T had high correlations to predicted iron content similar to R2 and R2(⁎) at 4.7T. Although R2(') had smaller y-intercept with estimated iron concentration than FDRI, in white matter R2(') demonstrated strongest dependence on fiber orientation with respect to B0. These results suggest that for brain iron correlation, there is minimal value of transverse difference methods over a single R2(⁎) measurement at highest available field, which was 4.7T., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: To investigate subcortical gray matter segmentation using transverse relaxation rate (R2 *) and quantitative susceptibility mapping (QSM) and apply it to voxel-based analysis in multiple sclerosis (MS)., Materials and Methods: Voxel-based variation in R2 * and QSM within deep gray matter was examined and compared to standard whole-structure analysis using 37 MS subjects and 37 matched controls. Deep gray matter nuclei (caudate, putamen, globus pallidus, and thalamus) were automatically segmented and morphed onto a custom atlas based on QSM and standard T1 -weighted images. Segmentation accuracy and scan-rescan reliability were tested., Results: When considering only significant regions as returned by the multivariate voxel-based analysis, increased R2 * and QSM was found in MS subjects compared to controls in portions of all four nuclei studied (P < 0.002). For R2 *, regional analysis yielded at least 66-fold improved P-value significance in all nuclei over standard whole-structure analysis, while for QSM only thalamus benefited, with 5-fold improvement in significance. Improved segmentation over standard methods, particularly for globus pallidus (2.8 times higher Dice score), was achieved by incorporating high-contrast QSM into the atlas. Voxel-based reliability was highest for QSM (<1% variation)., Conclusion: Automatic segmentation of iron-rich deep gray matter can be improved by incorporating QSM. Voxel-based evaluation yielded increased R2 * and QSM in MS subjects in all four nuclei studied with R2 *, benefiting the most from localized analysis over whole-structure measures., (© 2015 Wiley Periodicals, Inc.)

Purpose: We propose the use of a retrospectively gated cine fast spin echo (FSE) sequence for characterization of carotid artery dynamics. The aim of this study was to compare cine FSE measures of carotid dynamics with measures obtained on prospectively gated FSE images., Methods: The common carotid arteries in 10 volunteers were imaged using two temporally resolved sequences: (i) cine FSE and (ii) prospectively gated FSE. Three raters manually traced a common carotid artery area for all cardiac phases on both sequences. Measured areas and systolic-diastolic area changes were calculated and compared. Inter- and intra-rater reliability were assessed for both sequences., Results: No significant difference between cine FSE and prospectively gated FSE areas were observed (P = 0.36). Both sequences produced repeatable cross-sectional area measurements: inter-rater intraclass correlation coefficient (ICC) = 0.88 on cine FSE images and 0.87 on prospectively gated FSE images. Minimum detectable difference (MDD) in systolic-diastolic area was 4.9 mm(2) with cine FSE and 6.4 mm(2) with prospectively gated FSE., Conclusion: This cine FSE method produced repeatable dynamic carotid artery measurements with less artifact and greater temporal efficiency compared with prospectively gated FSE., (© 2014 Wiley Periodicals, Inc.)

Improved neuroscientific understanding of high-risk behaviors such as alcohol binging, drug use, and unsafe sex will lead to therapeutic advances for high-risk groups. High-risk behavior often occurs in an emotionally-charged context, and behavioral inhibition and emotion regulation play important roles in risk-related decision making. High impulsivity is an important potential contributor to high-risk behavior tendencies. We explored the relationships between high-risk behavior tendencies, impulsivity, and fMRI brain activations in an emotional Go/NoGo task. This task presented emotional distractor pictures (aversive vs. neutral) simultaneously with Go/NoGo stimuli (square vs. circle) that required a button press or withholding of the press, respectively. Participants' risk behavior tendencies were assessed with the Cognitive Appraisal of Risky Events (CARE) scale. The Barratt Impulsivity Scale 11 (BIS) was used to assess participant impulsivity. Individuals with higher CARE risk scores exhibited reduced activation related to response inhibition (NoGo-Go) in right orbital frontal cortex (OFC) and ventromedial prefrontal cortex. These regions did not show a significant relationship with impulsivity scores. Conversely, more impulsive individuals showed reduced emotion-related activity (aversive-neutral distractors) in dorsomedial prefrontal cortex, perigenual anterior cingulate cortex, and right posterior OFC. There were distinct neural correlates of high-risk behavior tendency and impulsivity in terms of brain activity in the emotional Go/NoGo task. This dissociation supports the conception of high-risk behavior tendency as a distinct construct from that of impulsivity. Our results suggest that treatment for high-risk behavior may be more effective with a nuanced approach that does not conflate high impulsivity necessarily with high-risk behavior tendencies.

Quantitative susceptibility mapping (QSM) measures bulk susceptibilities in the brain, which can arise from many sources. In iron-rich subcortical gray matter (GM), non-heme iron is a dominant susceptibility source. We evaluated the use of QSM for iron mapping in subcortical GM by direct comparison to tissue iron staining. We performed in situ or in vivo QSM at 4.7 T combined with Perls' ferric iron staining on the corresponding extracted subcortical GM regions. This histochemical process enabled examination of ferric iron in complete slices that could be related to susceptibility measurements. Correlation analyses were performed on an individual-by-individual basis and high linear correlations between susceptibility and Perls' iron stain were found for the three multiple sclerosis (MS) subjects studied (R(2) = 0.75, 0.62, 0.86). In addition, high linear correlations between susceptibility and transverse relaxation rate (R2*) were found (R(2) = 0.88, 0.88, 0.87) which matched in vivo healthy subjects (R(2) = 0.87). This work validates the accuracy of QSM for brain iron mapping and also confirms ferric iron as the dominant susceptibility source in subcortical GM, by demonstrating high linear correlation of QSM to Perls' ferric iron staining., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Objective: We hypothesized an increase in dorsolateral prefrontal cortex (DLPFC) glutamate levels would occur after 3 weeks of repetitive transcranial magnetic stimulation (rTMS) treatment and a decrease in major depressive disorder (MDD) symptoms., Methods: We report 6 patients (4 females) 15 to 21 years of age with treatment-resistant MDD. Participants had a mean (SD) age of 18.7 (1.95) years and a mean (SD) IQ of 102.3 (3.39). Short echo proton magnetic resonance spectroscopy (¹H-MRS) was used to quantify glutamate levels in the left DLPFC (4.5 cc) before and after rTMS treatment. Repetitive transcranial magnetic stimulation was localized to the left DLPFC and applied for 15 consecutive weekdays (120% resting motor threshold; 40 pulses over 4 seconds [10 Hz]; intertrain interval, 26 seconds; 75 trains; 3000 pulses). Treatment response was defined as a greater than 50% reduction in Hamilton Depression Rating Scale scores. Short echo proton magnetic resonance spectroscopy data were analyzed with LCModel to determine glutamate concentration., Results: After rTMS, treatment responders (n = 4) showed an increase (relative to baseline) in left DLPFC glutamate levels (11%), which corresponded to an improvement in depressive symptom severity (68% Hamilton Depression Rating Scale score reduction). Treatment nonresponders (n = 2) had elevated baseline glutamate levels compared to responders in that same region, which decreased with rTMS (-10%). Procedures were generally well tolerated with no adverse events., Conclusions: Repetitive transcranial magnetic stimulation is feasible and possibly efficacious in adolescents with MDD. In responders, rTMS may act by induced elevations in elevating DFPLC glutamate levels in the left DLPFC, thereby leading to symptom improvement.

Purpose: To investigate the feasibility of real-time 3D magnetic resonance imaging (MRI) with simultaneous recording of physiological signals for identifying sites of airway obstruction during natural sleep in pediatric patients with sleep-disordered breathing., Methods: Experiments were performed using a three-dimensional Fourier transformation (3DFT) gradient echo sequence with prospective undersampling based on golden-angle radial spokes, and L1-norm regularized iterative self-consistent parallel imaging (L1-SPIRiT) reconstruction. This technique was demonstrated in three healthy adult volunteers and five pediatric patients with sleep-disordered breathing. External airway occlusion was used to induce partial collapse of the upper airway on inspiration and test the effectiveness of the proposed imaging method. Apneic events were identified using information available from synchronized recording of mask pressure and respiratory effort., Results: Acceptable image quality was obtained in seven of eight subjects. Temporary airway collapse induced via inspiratory loading was successfully imaged in all three volunteers, with average airway volume reductions of 63.3%, 52.5%, and 33.7%. Central apneic events and associated airway narrowing/closure were identified in two pediatric patients. During central apneic events, airway obstruction was observed in the retropalatal region in one pediatric patient., Conclusion: Real-time 3D MRI of the pharyngeal airway with synchronized recording of physiological signals is feasible and may provide valuable information about the sites and nature of airway narrowing/collapse during natural sleep., (Copyright © 2013 Wiley Periodicals, Inc.)

Purpose: Dynamic contrast-enhanced imaging provides unique physiological information, notably the endothelial permeability (K(trans)), and may improve the diagnosis and management of multiple pathologies. Current acquisition methods provide limited spatial-temporal resolution and field-of-view, often preventing characterization of the entire pathology and precluding measurement of the arterial input function. We present a method for highly accelerated dynamic imaging and demonstrate its utility for dynamic contrast-enhanced modeling., Methods: We propose a novel Poisson ellipsoid sampling scheme and enforce multiple spatial and temporal l1-norm constraints during image reconstruction. Retrospective and prospective analyses were performed to validate the approach., Results: Retrospectively, no mean bias or diverging trend was observed as the acceleration rate was increased from 3× to 18×; less than 10% error was measured in K(trans) at any individual rates in this range. Prospectively accelerated images at a rate of 36× enabled full brain coverage with 0.94 × 0.94 × 1.9 mm(3) spatial and 4.1 s temporal resolutions. Images showed no visible degradation and provided accurate K(trans) values when compared to a clinical population., Conclusion: Highly accelerated dynamic MRI using compressed sensing and parallel imaging provides accurate permeability modeling and enables full brain, high resolution acquisitions., (Copyright © 2013 Wiley Periodicals, Inc.)