Improving Xenon-129 lung ventilation image SNR with deep-learning based image reconstruction.

PURPOSE: To evaluate the feasibility and utility of a deep learning (DL)-based reconstruction for improving the SNR of hyperpolarized 129Xe lung ventilation MRI. METHODS: 129Xe 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 (VHI) 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: 129Xe 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 129Xe ventilation imaging using natural-abundance xenon appears feasible. CONCLUSION: DL-based image reconstruction significantly improves 129Xe 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 129Xe ventilation imaging with natural-abundance xenon in the future.

Extraction of a vascular function for a fully automated dynamic contrast-enhanced magnetic resonance brain image processing pipeline.

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.

Evaluation of deep learning reconstructed high-resolution 3D lumbar spine MRI.

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.

Pseudo Test-Retest Evaluation of Millimeter-Resolution Whole-Brain Dynamic Contrast-enhanced MRI in Patients with High-Grade Glioma.

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 M0 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 (Ktrans) 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 Ktrans, if Ktrans was estimated consecutively. The maximum reproducibility coefficient for median Ktrans 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.

Sparse precontrast T1 mapping for high-resolution whole-brain DCE-MRI.

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 <25 ms in white matter (WM) and <11 ms in brain tumor (BT). T1 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, T1 bias was <50 ms in WM and <30 ms in BT. For R ≤ 10, T1 SD was <107.1 ms in WM (COV ~9.9%) and <240.9 ms in BT (COV ~12.1%). In the healthy subject, T1 bias was <30 ms for R ≤ 16. At R = 4, T1 SD was 171.4 ms (COV ~13.0%). In the prospective brain tumor study, T1 values were consistent with literature values in WM and BT. CONCLUSION: High-resolution whole-brain VFA T1 mapping is feasible with sparse sampling, supporting its use for quantitative DCE-MRI.

In vivo Glx and Glu measurements from GABA-edited MRS at 3 T.

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+, TE = 68 ms, and macromolecule suppressed, MMSup, TE = 80 ms) with Glu and Glx quantified from a short-echo PRESS (PRESS-35, TE = 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 cm3 . 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.

Improvement of late gadolinium enhancement image quality using a deep learning-based reconstruction algorithm and its influence on myocardial scar quantification.

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.

Cerebral blood flow increases across 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 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.

Rotated spiral RARE for high spatial and temporal resolution volumetric arterial spin labeling acquisition.

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.

Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites.

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.

Localizing the seizure onset zone by comparing patient postictal hypoperfusion to healthy controls.

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.

Three-dimensional inhomogeneous magnetization transfer with rapid gradient-echo (3D ihMTRAGE) imaging.

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.

Longitudinal Reproducibility of MR Perfusion Using 3D Pseudocontinuous Arterial Spin Labeling With Hadamard-Encoded Multiple Postlabeling Delays.

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 (R2 = 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.

Functional magnetic resonance imaging study of working memory several years after pediatric concussion.

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.

Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites.

Accurate and reliable quantification of brain metabolites measured in vivo using 1H 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 T1-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.

Cerebral blood flow in children and adolescents several years after concussion.

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.

A comparison of inhomogeneous magnetization transfer, myelin volume fraction, and diffusion tensor imaging measures in healthy children.

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/VFm, respectively) which are suggested to have improved sensitivity to myelin. We compared RD, qihMT, and VFm 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 VFm and qihMT were significantly more strongly correlated (qihMT-VFm r = 0.89) than either measure was with RD (RD-qihMT r = -0.66, RD-VFm 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 B0. All measures appear to be sensitive to myelin content, though qihMT and VFm 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.

Joint arterial input function and tracer kinetic parameter estimation from undersampled dynamic contrast-enhanced MRI using a model consistency constraint.

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.

Transit time corrected arterial spin labeling technique aids to overcome delayed transit time effect.

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.

Big GABA: Edited MR spectroscopy at 24 research sites.

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.