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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 cm3 ). 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.

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 p values 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.

PURPOSE To develop and evaluate an efficient precontrast T1 mapping technique suitable for quantitative high-resolution whole-brain dynamic contrast-enhanced-magnetic resonance imaging (DCE-MRI). METHODS Variable flip angle (VFA) T1 mapping was considered that provides 1 × 1 × 2 mm3 resolution to match a recent high-resolution whole-brain DCE-MRI protocol. Seven FAs were logarithmically spaced from 1.5° to 15°. T1 and M0 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 T1 -mapping precision decreased with undersampling factor R, althoughwhereas bias remained small before a critical R. In the noiseless DRO, T1 bias was

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

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

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 L1-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.

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.Observational, cross-sectional.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.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).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 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 Pboot). 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 (Pboot > .90), N-acetylaspartate and N-acetylaspartylglutamate (Pboot = .13), or glutamate and glutamine (Pboot = .11). Among the smaller resonances, no vendor effects were found for ascorbate (Pboot = .08), aspartate (Pboot > .90), glutathione (Pboot > .90), or lactate (Pboot = .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. ispartof: RADIOLOGY vol:295 issue:1 pages:171-180 ispartof: location:United States status: published

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.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.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.Youth with a history of concussion demonstrate differences in regional CBF (not global CBF), but without clear clinical expression.

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.

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). 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. 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). 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.

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, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Intraspinal microstimulation (ISMS) is currently under investigation for its ability to restore function following spinal cord injury and aid in addressing basic investigations of the spinal cord in feline and murine (rat) models. In this report we describe the procedures for fabricating and implanting intraspinal microwires, with special emphasis on the rat model. We also report our results on targeting success and long-term stability and functionality of the implants. Early targeting with implants fabricated based on general “average” dimensions of the spinal cord was approximately 50% successful in reaching the proper targets within the ventral grey matter in cats. Improvements in insertion technique and the use of multiple contact electrodes have raised the targeting success to 100%. Furthermore, the manufacturing of ISMS arrays has been improved by the use of magnetic resonance imaging to create subject-specific implants for cats and track the location of the arrays post-implant. In the rat, our procedures have produced desirable targeting of all recovered microwires. We speculate this is due to the different targeting parameters and the shorter depth of insertion in the rat spinal cord. Although there is a heightened mechanical mismatch between the $30~\mu \mathrm {m}$ -diameter microwires and the small rat spinal cord, chronic implantation and stimulation produce limited histological damage and do not compromise function. Furthermore, despite the increased difficulties of implanting into the smaller rat spinal cord, ISMS is effective in activating spinal cord networks in the lumbosacral enlargement in a manner that is safe, stable and reproducible.

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

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.

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.

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 suggest that CBF continues to increase at least until the age of 7 years, likely supporting the ongoing improvements in behaviour, cognition, motor, and sensory functions of the children in early childhood.Highlights*We mapped cerebral blood flow development longitudinally in 96 typically developing children aged 2-7 years*Cerebral blood flow increased over the full age range*No significant differences between males and females were foundConflicting of InterestR.M.L. is an employee of GE.

Purpose The purpose of this work was to develop and evaluate a T1-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.

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.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.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 in100ms. GOCART has also been successfully utilized prospectively to produce clinically valuable whole-brain DCE-MRI images.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.

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% ( p2 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, p2 showed significant correlation only for the globus pallidus in multiple sclerosis (MS) ( pConclusions: 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.

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 braintumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm3, FOV 22 × 22 × 4.2 cm3, and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm3, and broader coverage 22 × 22 × 19 cm3. Temporal resolution was 5 s for both protocols. Time-resolvedimages 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.

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, Highlights • A biomarker based on diffusion kurtosis imaging achieved an accuracy of 83%. • Kurtosis-based measures were more abnormal in ALS than tensor-based measures. • Motor cortex in the symptomatic hemisphere was smaller and had greater iron concentration. • There was a 1 mL volume loss per year in ALS motor cortex.

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.

Purpose To investigate subcortical gray matter segmentation using transverse relaxation rate (R) and quantitative susceptibility mapping (QSM) and apply it to voxel-based analysis in multiple sclerosis (MS). Materials and Methods Voxel-based variation in R∗ 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 T-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 R∗ and QSM was found in MS subjects compared to controls in portions of all four nuclei studied (P < 0.002). For R, 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 (

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 mm2 with cine FSE and 6.4 mm2 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. Magn Reson Med 74:1103–1109, 2015. © 2014 Wiley Periodicals, Inc.

Obstructive sleep apnea (OSA) is the most common type of sleep apnea and is characterized by repetitive episodes of airflow cessation during sleep as a result of the collapse of the pharyngeal airway (1). The prevalence of OSA syndrome has been estimated at 2% of the general population of children (2), 13–66% of obese children (3), and 4–9% of adults (2). Airway collapse during sleep is caused by a combination of anatomical and functional factors. Anatomical factors include inherently narrow upper airway resulting from 1) enlarged adenoids or tonsils, 2) a large soft palate, and 3) a large tongue. Functional factors include decrease in the activation of pharyngeal dilator muscles with sleep onset. Obesity contributes to a narrow airway and airway collapsibility (4), and the prevalence of obesity is on the rise. Despite breathing efforts, airway obstruction results in no gas exchange leading to oxygen desaturation and frequent arousals during sleep. Pathologic central sleep apnea (CSA) is relatively rare when compared with OSA and is characterized by absent respiratory effort as well as airflow cessation during sleep, accompanied by arousal and/or hypoxemia. Airway narrowing and/or closure occur during CSA (5). CSAs have been reported in obese children and adolescents with sleep-disordered breathing (3). Complex sleep apnea is a combination of OSA and CSA, and patients with complex sleep apnea exhibit CSAs even during a continuous positive airway pressure treatment of airway obstruction (6). Knowledge of obstruction sites with an imaging tool has been of great interest to researchers because direct inspection of the airway may facilitate treatment planning and may have the potential to improve treatment outcome (7–9). Imaging techniques including endoscopy, fluoroscopy, computed tomography, and magnetic resonance imaging (MRI) have been applied to subjects with OSA, and each approach has its own unique limitations (10). MRI is noninvasive, involves no ionizing radiation, and has provided valuable insights into understanding upper airway anatomy and function in patients with OSA syndrome. In prior studies, static 3D MRI revealed narrowed airway volume in patients with OSA when compared with age-matched controls without OSA (11). Respiratory-gated dynamic 2D (12) and 3D (13,14) MRI have been proposed to measure the changes in the upper airway caliber in relation to the respiratory cycle during tidal breathing and compare them between subjects with and without OSA syndrome. Real-time MRI (i.e., MRI using an acquisition time per frame that is short relative to the dynamic process of interest) has been used to demonstrate airway collapse in OSA patients during sleep with (15,16) and without sedation (17–19), but has been limited to a 2D slice of axial or mid-sagittal orientation. Recently, Shin et al. (18,19) demonstrated visualization of airway collapse in adult patients with OSA using real-time interactive multislice MRI, in which slice prescriptions were made in axial, mid-sagittal, and coronal slices. The most common approach is 2D mid-sagittal MRI, which provides only partial coverage of a narrowed upper airway and is very sensitive to imperfect localization and to patient head motion. Similarly, 2D axial MRI can reveal temporal changes in airway cross-sectional area, but it is easy to miss the actual site of collapse. Real-time 3D MRI would be desirable, because it provides complete coverage of the airway and does not require prior knowledge of the location of collapse. In this work, we propose a real-time 3D MRI acquisition using a novel temporal view order and a reconstruction technique that provides high spatial and temporal resolution with the combined use of parallel imaging and constrained reconstruction. We demonstrate its effectiveness in visualizing marked reduction of the pharyngeal airway during inspiratory loading in volunteers and identifying locations of airway narrowing and/or collapse in pediatric subjects with sleep-disordered breathing during natural sleep.

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.

Background: In addition to neuronal injury, inflammatory, and demyelinating processes, evidence suggests multiple sclerosis (MS) is also associated with increased iron deposition in the basal ganglia. Magnetic resonance imaging (MRI), particularly at very high field strengths, is sensitive to iron accumulation and may enable visualization and quantification of iron associated with MS. Objectives: To investigate the sub-cortical gray matter in patients with early-stage relapsing–remitting MS using multiple, and novel, quantitative MRI measures at very high field. Methods: In total, 22 patients with relapsing–remitting MS and 22 control subjects were imaged at 4.7 Tesla. Transverse relaxation rates (R2 and R2*) and susceptibility phase were quantified in four basal ganglia nuclei, the thalamus, and the red nuclei. Parameters in patients with MS were compared with those in healthy subjects and correlated with clinical scores. Results: Significant abnormalities were observed in most structures, most notably in the pulvinar sub-nucleus. Significant correlations with disability were observed in the pulvinar; marginally significant correlations were also observed in the thalamus and red nucleus. No significant correlations were observed with duration since index relapse. Conclusions: Widespread abnormalities are present in the deep gray matter nuclei of patients recently diagnosed with MS; these abnormalities can be detected via multi-modal high-field MRI. Imaging metrics, particularly R2*, relate to disease severity in the pulvinar and other gray matter regions.

Presented is a fitting model for transverse relaxometry data acquired with the multiple-refocused spin-echo sequence. The proposed model, requiring no additional data input or pulse sequence modifications, compensates for imperfections in the transmit field and radiofrequency (RF) profiles. Exploiting oscillatory echo behavior to estimate alternate coherence pathways, the model compensates for prolonged signal decay from stimulated echo pathways yielding precise monoexponential T(2) quantification. Verified numerically and experimentally at 4.7 T in phantoms and the human brain, over 95% accuracy is readily attainable in realistic imaging situations without sacrificing multislice capabilities or requiring composite or adiabatic RF pulses. The proposed model allows T(2) quantitation in heterogeneous transmit fields and permits thin refocusing widths for efficient multislice imaging.

An implementation of fast spin echo at 4.7 T designed for versatile and time-efficient T(2)-weighted imaging of the human brain is presented. Reduced refocusing angles (alpha < 180 degrees) were employed to overcome specific absorption rate (SAR) constraints and their effects on image quality assessed. Image intensity and tissue contrast variations from heterogeneous RF transmit fields and incidental magnetization transfer effects were investigated at reduced refocusing angles. We found that intraslice signal variations are minimized with refocusing angles near 180 degrees, but apparent gray/white matter contrast is independent of refocusing angle. Incidental magnetization transfer effects from multislice acquisitions were shown to attenuate white matter intensity by 25% and gray matter intensity by 15% at 180 degrees; less than 5% attenuation was seen in all tissues at flip angles below 60 degrees. We present multislice images acquired without excess delay time for SAR mitigation using a variety of protocols. Subsecond half Fourier acquisition single-shot turbo spin echo (HASTE) images were obtained with a novel variable refocusing angle echo train (20 degrees < alpha < 58 degrees) and high-resolution scans with a voxel volume of 0.18 mm(3) were acquired in 6.5 min with refocusing angles of 100 degrees.

To investigate the relationship between magnetic resonance (MR) imaging markers of iron content and disease severity in patients with multiple sclerosis (MS) over a 2-year period.This prospective study was approved by the local ethics committee, and written informed consent was obtained from all participants. Seventeen patients with MS and 17 control subjects were examined twice, 2 years apart, by using phase imaging and transverse relaxation (R2*) mapping at 4.7 T. Quantitative differences in iron content in deep gray matter between patients and control subjects were evaluated with repeated-measures multivariate analysis of variance separately for R2* mapping and phase imaging. Multiple regression analysis was used to evaluate correlations of MR imaging measures, both 2-year-difference and single-time measurements, to baseline disease severity.R2* mapping using 2-year-difference measurements had the highest correlation to disease severity (r = 0.905, P.001) compared with R2* mapping using single-time measurements (r = 0.560, P = .019) and phase imaging by using either single-time (r = 0.539, P = .026) or 2-year-difference (r = 0.644, P = .005) measurements. Significant increases in R2* occur during 2 years in the substantia nigra (P.001) and globus pallidus (P = .035), which are both predictors of disease in regression analysis, in patients compared with control subjects. There were group differences in the substantia nigra, globus pallidus, pulvinar thalamus, thalamus, and caudate nucleus, compared with control subjects with R2* mapping (P.05), and group differences in the caudate nucleus and pulvinar thalamus, compared with control subjects with phase imaging (P.05).There are significant changes in deep gray matter iron content in MS during 2 years measured with MR imaging, changes that are strongly related to physical disability. Longitudinal measurements may produce a higher correlation to disease severity compared with single-time measurements because baseline iron content of deep gray matter is variable among subjects.

To investigate the relationship between iron staining and magnetic resonance (MR) imaging measurements in postmortem subjects with multiple sclerosis (MS).Institutional ethical approval was obtained, and informed consent was obtained from the subjects and/or their families. Four MR imaging methods based on transverse relaxation (T2 weighting, R2 mapping, and R2* mapping) and phase imaging were performed by using a 4.7-T system in three in situ postmortem patients with MS less than 28 hours after death and in one in vivo patient 1 year before death. Iron staining with the Perls iron reaction was performed after brain extraction. Region-of-interest measurements from six subcortical gray matter structures were obtained from MR imaging and then correlated with corresponding locations on photographs of iron-stained pathologic slices by using a separate linear least-squares regression in each subject. Iron status of white matter lesions, as determined by staining, was compared with appearance on MR images.R2* mapping had the highest intrasubject correlations with iron in subcortical gray matter (R(2) = 0.857, 0.628, and 0.685; all P.001), while R2 mapping (R(2) = 0.807, 0.615, 0.628, and 0.489; P.001 and P = .001, .034, and .001, respectively), phase imaging (R(2) = 0.672, 0.441, 0.596, 0.548; all P ≤ .001), and T2-weighted imaging (R(2) = 0.463, 0.582, 0.650, and 0.551; all P.001) had lower but still strong correlations. Within lesions, hypointense areas on phase images did not always represent iron. A hyperintense rim surrounding lesions on R2* maps was only present with iron staining, yet not all iron-staining lesions had R2* rim hyperintensity.All four MR imaging methods had significant linear correlations with iron and could potentially be used to determine iron status of subcortical gray matter structures in MS, with R2* mapping being preferred. A reliable method of determining iron status within MS lesions was not established.

Purpose To demonstrate 4.7 Tesla (T) imaging methods for visualizing lesions in multiple sclerosis in the human brain using phase susceptibility-weighting and T2 weighting. Materials and Methods Seven patients with relapsing-remitting multiple sclerosis were imaged at 4.7T using three-dimensional (3D) susceptibility-weighted imaging (SWI) with 0.90 mm3 voxel volumes, and with 2D T2-weighted fast spin echo (T2WFSE) with 0.34 mm3 voxels and 1.84 mm3 voxels. The visibility of MS lesions at 4.7T with phase SWI and T2WFSE was assessed by independent lesion counts made by an experienced neuroradiologist, and by quantitative measures. Results High resolution T2WFSE at 4.7T provided excellent depiction of hyperintense lesions. When combined with phase SWI, 124 total lesions were identified of which 18% were only visible on phase SWI and not on T2WFSE. The phase lesions had a mean phase shift relative to local background of −11.15 ± 5.97 parts per billion. Conclusion Imaging at 4.7T can provide both high quality, high resolution T2WFSE and SWI for visualization of lesions in multiple sclerosis. Phase susceptibility-weighting can identify additional lesions that are not visible with high resolution T2WFSE. J. Magn. Reson. Imaging 2009;30:737–742. © 2009 Wiley-Liss, Inc.