Imaging chronic active lesions in multiple sclerosis: a consensus statement.

Chronic active lesions (CAL) are an important manifestation of chronic inflammation in multiple sclerosis (MS) and have implications for non-relapsing biological progression. In recent years, the discovery of innovative magnetic resonance imaging (MRI) and PET derived biomarkers has made it possible to detect CAL, and to some extent quantify them, in the brain of persons with MS, in vivo. Paramagnetic rim lesions on susceptibility-sensitive MRI sequences, MRI-defined slowly expanding lesions on T1-weighted (T1-w) and T2-w scans, and 18-kDa translocator protein-positive lesions on PET are promising candidate biomarkers of CAL. While partially overlapping, these biomarkers do not have equivalent sensitivity and specificity to histopathological CAL. Standardization in the use of available imaging measures for CAL identification, quantification, and monitoring is lacking. To fast-forward clinical translation of CAL, the North American Imaging in Multiple Sclerosis Cooperative developed a Consensus Statement, which provides guidance for the radiological definition and measurement of CAL. The proposed manuscript presents this Consensus Statement, summarizes the multistep process leading to it, and identifies the remaining major gaps in knowledge.

Denoising of diffusion MRI in the cervical spinal cord - effects of denoising strategy and acquisition on intra-cord contrast, signal modeling, and feature conspicuity.

Quantitative diffusion MRI (dMRI) is a promising technique for evaluating the spinal cord in health and disease. However, low signal-to-noise ratio (SNR) can impede interpretation and quantification of these images. The purpose of this study is to evaluate several dMRI denoising approaches on their ability to improve the quality, reliability, and accuracy of quantitative diffusion MRI of the spinal cord. We evaluate three denoising approaches (Non-Local Means, Marchenko-Pastur PCA, and a newly proposed Patch2Self algorithm) and conduct five experiments to validate the denoising performance on clinical-quality and commonly-acquired dMRI acquisitions: 1) a phantom experiment to assess denoising error and bias; 2) a multi-vendor, multi-acquisition open experiment for both qualitative and quantitative evaluation of noise residuals; 3) a bootstrapping experiment to estimate uncertainty of parametric maps; 4) an assessment of spinal cord lesion conspicuity in a multiple sclerosis group; and 5) an evaluation of denoising for advanced parametric multi-compartment modeling. We find that all methods improve signal-to-noise ratio and conspicuity of MS lesions in individual diffusion weighted images (DWIs), but MPPCA and Patch2Self excel at improving the quality and intra-cord contrast of diffusion weighted images - removing signal fluctuations due to thermal noise while improving precision of estimation of diffusion parameters even with very few DWIs (i.e., 16-32) typical of clinical acquisitions. These denoising approaches hold promise for facilitating reliable diffusion observations and measurements in the spinal cord to investigate biological and pathological processes.

Cervical spinal cord susceptibility-weighted MRI at 7T: Application to multiple sclerosis.

BACKGROUND: Susceptibility-weighted imaging (SWI) has been extensively studied in the brain and in diseases of the central nervous system such as multiple sclerosis (MS) providing unique opportunities to visualize cerebral vasculature and disease-related pathology, including the central vein sign (CVS) and paramagnetic rim lesions (PRLs). However, similar studies evaluating SWI in the spinal cord of patients with MS remain severely limited. PURPOSE: Based on our previous findings of enlarged spinal vessels in MS compared to healthy controls (HCs), we developed high-field SWI acquisition and processing methods for the cervical spinal cord with application in people with MS (pwMS) and HCs. Here, we demonstrate the vascular variability between the two cohorts and unique MS lesion features in the cervical cord. METHODS: In this retrospective, exploratory pilot study conducted between March 2021 and March 2022, we scanned 12 HCs and 9 pwMS using an optimized non-contrast 2D T2*-weighted gradient echo sequence at 7 tesla. The overall appearance of the white and gray matter as well as tissue vasculature were compared between the two cohorts and areas of MS pathology in the patient group were assessed using both the magnitude and processed SWI images. RESULTS: We show improved visibility of vessels and more pronounced gray and white matter contrast in the MS group compared to HCs, hypointensities surrounding the cord in the MS cohort, and identify signal changes indicative of the CVS and paramagnetic rims in 66 % of pwMS with cervical spinal lesions. CONCLUSION: In this first study of SWI at 7T in the human spinal cord, SWI holds promise in advancing our understanding of disease processes in the cervical cord in MS.

J-Difference editing (MEGA) of lactate in the human brain at 3T.

PURPOSE: The need to detect and quantify brain lactate accurately by MRS has stimulated the development of editing sequences based on J coupling effects. In J-difference editing of lactate, threonine can be co-edited and it contaminates lactate estimates due to the spectral proximity of the coupling partners of their methyl protons. We therefore implemented narrow-band editing 180° pulses (E180) in MEGA-PRESS acquisitions to resolve separately the 1.3-ppm resonances of lactate and threonine. METHODS: Two 45.3-ms rectangular E180 pulses, which had negligible effects 0.15-ppm away from the carrier frequency, were implemented in a MEGA-PRESS sequence with TE 139 ms. Three acquisitions were designed to selectively edit lactate and threonine, in which the E180 pulses were tuned to 4.1 ppm, 4.25 ppm, and a frequency far off resonance. Editing performance was validated with numerical analyses and acquisitions from phantoms. The narrow-band E180 MEGA and another MEGA-PRESS sequence with broad-band E180 pulses were evaluated in six healthy subjects. RESULTS: The 45.3-ms E180 MEGA offered a difference-edited lactate signal with lower intensity and reduced contamination from threonine compared to the broad-band E180 MEGA. The 45.3 ms E180 pulse had MEGA editing effects over a frequency range larger than seen in the singlet-resonance inversion profile. Lactate and threonine in healthy brain were both estimated to be 0.4 ± 0.1 mM, with reference to N-acetylaspartate at 12 mM. CONCLUSION: Narrow-band E180 MEGA editing minimizes threonine contamination of lactate spectra and may improve the ability to detect modest changes in lactate levels.

Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors.

Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.

Integrating the BIDS Neuroimaging Data Format and Workflow Optimization for Large-Scale Medical Image Analysis.

A robust medical image computing infrastructure must host massive multimodal archives, perform extensive analysis pipelines, and execute scalable job management. An emerging data format standard, the Brain Imaging Data Structure (BIDS), introduces complexities for interfacing with XNAT archives. Moreover, workflow integration is combinatorically problematic when matching large amount of processing to large datasets. Historically, workflow engines have been focused on refining workflows themselves instead of actual job generation. However, such an approach is incompatible with data centric architecture that hosts heterogeneous medical image computing. Distributed automation for XNAT toolkit (DAX) provides large-scale image storage and analysis pipelines with an optimized job management tool. Herein, we describe developments for DAX that allows for integration of XNAT and BIDS standards. We also improve DAX's efficiencies of diverse containerized workflows in a high-performance computing (HPC) environment. Briefly, we integrate YAML configuration processor scripts to abstract workflow data inputs, data outputs, commands, and job attributes. Finally, we propose an online database-driven mechanism for DAX to efficiently identify the most recent updated sessions, thereby improving job building efficiency on large projects. We refer the proposed overall DAX development in this work as DAX-1 (DAX version 1). To validate the effectiveness of the new features, we verified (1) the efficiency of converting XNAT data to BIDS format and the correctness of the conversion using a collection of BIDS standard containerized neuroimaging workflows, (2) how YAML-based processor simplified configuration setup via a sequence of application pipelines, and (3) the productivity of DAX-1 on generating actual HPC processing jobs compared with earlier DAX baseline method. The empirical results show that (1) DAX-1 converting XNAT data to BIDS has similar speed as accessing XNAT data only; (2) YAML can integrate to the DAX-1 with shallow learning curve for users, and (3) DAX-1 reduced the job/assessor generation latency by finding recent modified sessions. Herein, we present approaches for efficiently integrating XNAT and modern image formats with a scalable workflow engine for the large-scale dataset access and processing.

Multi-shot acquisitions for stimulus-evoked spinal cord BOLD fMRI.

PURPOSE: To demonstrate the feasibility of 3D multi-shot magnetic resonance imaging acquisitions for stimulus-evoked blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) in the human spinal cord in vivo. METHODS: Two fMRI studies were performed at 3T. The first study was a hypercapnic gas challenge where data were acquired from healthy volunteers using a multi-shot 3D fast field echo (FFE) sequence as well as single-shot multi-slice echo-planar imaging (EPI). In the second study, another cohort of healthy volunteers performed an upper extremity motor task while fMRI data were acquired using a 3D multi-shot acquisition. RESULTS: Both 2D-EPI and 3D-FFE were shown to be sensitive to BOLD signal changes in the cervical spinal cord, and had comparable contrast-to-noise ratios in gray matter. FFE exhibited much less signal drop-out and weaker geometric distortions compared to EPI. In the motor paradigm study, the mean number of active voxels was highest in the ventral gray matter horns ipsilateral to the side of the task and at the spinal level associated with innervation of finger extensors. CONCLUSIONS: Highly multi-shot acquisition sequences such as 3D-FFE are well suited for stimulus-evoked spinal cord BOLD fMRI.

Does the magnetization transfer effect bias chemical exchange saturation transfer effects? Quantifying chemical exchange saturation transfer in the presence of magnetization transfer.

PURPOSE: Chemical exchange saturation transfer (CEST) is an MRI technique sensitive to the presence of low-concentration solute protons exchanging with water. However, magnetization transfer (MT) effects also arise when large semisolid molecules interact with water, which biases CEST parameter estimates if quantitative models do not account for macromolecular effects. This study establishes under what conditions this bias is significant and demonstrates how using an appropriate model provides more accurate quantitative CEST measurements. METHODS: CEST and MT data were acquired in phantoms containing bovine serum albumin and agarose. Several quantitative CEST and MT models were used with the phantom data to demonstrate how underfitting can influence estimates of the CEST effect. CEST and MT data were acquired in healthy volunteers, and a two-pool model was fit in vivo and in vitro, whereas removing increasing amounts of CEST data to show biases in the CEST analysis also corrupts MT parameter estimates. RESULTS: When all significant CEST/MT effects were included, the derived parameter estimates for each CEST/MT pool significantly correlated (P < .05) with bovine serum albumin/agarose concentration; minimal or negative correlations were found with underfitted data. Additionally, a bootstrap analysis demonstrated that significant biases occur in MT parameter estimates (P < .001) when unmodeled CEST data are included in the analysis. CONCLUSIONS: These results indicate that current practices of simultaneously fitting both CEST and MT effects in model-based analyses can lead to significant bias in all parameter estimates unless a sufficiently detailed model is utilized. Therefore, care must be taken when quantifying CEST and MT effects in vivo by properly modeling data to minimize these biases.

Selective inversion recovery quantitative magnetization transfer imaging: Toward a 3 T clinical application in multiple sclerosis.

BACKGROUND: Assessing the degree of myelin injury in patients with multiple sclerosis (MS) is challenging due to the lack of magnetic resonance imaging (MRI) methods specific to myelin quantity. By measuring distinct tissue parameters from a two-pool model of the magnetization transfer (MT) effect, quantitative magnetization transfer (qMT) may yield these indices. However, due to long scan times, qMT has not been translated clinically. OBJECTIVES: We aim to assess the clinical feasibility of a recently optimized selective inversion recovery (SIR) qMT and to test the hypothesis that SIR-qMT-derived metrics are informative of radiological and clinical disease-related changes in MS. METHODS: A total of 18 MS patients and 9 age- and sex-matched healthy controls (HCs) underwent a 3.0 Tesla (3 T) brain MRI, including clinical scans and an optimized SIR-qMT protocol. Four subjects were re-scanned at a 2-week interval to determine inter-scan variability. RESULTS: SIR-qMT measures differed between lesional and non-lesional tissue (p < 0.0001) and between normal-appearing white matter (NAWM) of patients with more advanced disability and normal white matter (WM) of HCs (p < 0.05). SIR-qMT measures were associated with lesion volumes, disease duration, and disability scores (p ⩽ 0.002). CONCLUSION: SIR-qMT at 3 T is clinically feasible and predicts both radiological and clinical disease severity in MS.

Spatial distribution of multiple sclerosis lesions in the cervical spinal cord.

Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.

Population Genomics Training for the Next Generation of Conservation Geneticists: ConGen 2018 Workshop.

The increasing availability and complexity of next-generation sequencing (NGS) data sets make ongoing training an essential component of conservation and population genetics research. A workshop entitled "ConGen 2018" was recently held to train researchers in conceptual and practical aspects of NGS data production and analysis for conservation and ecological applications. Sixteen instructors provided helpful lectures, discussions, and hands-on exercises regarding how to plan, produce, and analyze data for many important research questions. Lecture topics ranged from understanding probabilistic (e.g., Bayesian) genotype calling to the detection of local adaptation signatures from genomic, transcriptomic, and epigenomic data. We report on progress in addressing central questions of conservation genomics, advances in NGS data analysis, the potential for genomic tools to assess adaptive capacity, and strategies for training the next generation of conservation genomicists.

Evidence for adaptive introgression of exons across a hybrid swarm in deer.

BACKGROUND: Secondary contact between closely related lineages can result in a variety of outcomes, including hybridization, depending upon the strength of reproductive barriers. By examining the extent to which different parts of the genome introgress, it is possible to infer the strength of selection and gain insight into the evolutionary trajectory of lineages. Following secondary contact approximately 8000 years ago in the Pacific Northwest, mule deer (Odocoileus hemionus hemionus) and black-tailed deer (O. h. columbianus) formed a hybrid swarm along the Cascade mountain range despite substantial differences in body size (up to two times) and habitat preference. In this study, we examined genetic population structure, extent of introgression, and selection pressures in freely interbreeding populations of mule deer and black-tailed deer using mitochondrial DNA sequences, 9 microsatellite loci, and 95 SNPs from protein-coding genes. RESULTS: We observed bi-directional hybridization and classified approximately one third of the 172 individuals as hybrids, almost all of which were beyond the F1 generation. High genetic differentiation between black-tailed deer and mule deer at protein-coding genes suggests that there is positive divergent selection, though selection on these loci is relatively weak. Contrary to predictions, there was not greater selection on protein-coding genes thought to be associated with immune function and mate choice. Geographic cline analyses were consistent across genetic markers, suggesting long-term stability (over hundreds of generations), and indicated that the center of the hybrid swarm is 20-30 km to the east of the Cascades ridgeline, where there is a steep ecological transition from wet, forested habitat to dry, scrub habitat. CONCLUSIONS: Our data are consistent with a genetic boundary between mule deer and black-tailed deer that is porous but maintained by many loci under weak selection having a substantial cumulative effect. The absence of clear reproductive barriers and the consistent centering of geographic clines at a sharp ecotone suggests that ecology is a driver of hybrid swarm dynamics. Adaptive introgression in this study (and others) promotes gene flow and provides valuable insight into selection strength on specific genes and the evolutionary trajectory of hybridizing taxa.

Diffusion MRI microstructural models in the cervical spinal cord - Application, normative values, and correlations with histological analysis.

Multi-compartment tissue modeling using diffusion magnetic resonance imaging has proven valuable in the brain, offering novel indices sensitive to the tissue microstructural environment in vivo on clinical MRI scanners. However, application, characterization, and validation of these models in the spinal cord remain relatively under-studied. In this study, we apply a diffusion "signal" model (diffusion tensor imaging, DTI) and two commonly implemented "microstructural" models (neurite orientation dispersion and density imaging, NODDI; spherical mean technique, SMT) in the human cervical spinal cord of twenty-one healthy controls. We first provide normative values of DTI, SMT, and NODDI indices in a number of white matter ascending and descending pathways, as well as various gray matter regions. We then aim to validate the sensitivity and specificity of these diffusion-derived contrasts by relating these measures to indices of the tissue microenvironment provided by a histological template. We find that DTI indices are sensitive to a number of microstructural features, but lack specificity. The microstructural models also show sensitivity to a number of microstructure features; however, they do not capture the specific microstructural features explicitly modelled. Although often regarded as a simple extension of the brain in the central nervous system, it may be necessary to re-envision, or specifically adapt, diffusion microstructural models for application to the human spinal cord with clinically feasible acquisitions - specifically, adjusting, adapting, and re-validating the modeling as it relates to both theory (i.e. relevant biology, assumptions, and signal regimes) and parameter estimation (for example challenges of acquisition, artifacts, and processing).

Quantitative magnetization transfer imaging of the human locus coeruleus.

The locus coeruleus (LC) is the major origin of norepinephrine in the central nervous system, and is subject to age-related and neurodegenerative changes, especially in disorders such as Parkinson's disease and Alzheimer's disease. Previous studies have shown that neuromelanin (NM)-sensitive MRI can be used to visualize the LC, and it is hypothesized that magnetization transfer (MT) effects are the primary source of LC contrast. The aim of this study was to characterize the MT effects in LC imaging by applying high spatial resolution quantitative MT (qMT) imaging to create parametric maps of the macromolecular content of the LC and surrounding tissues. Healthy volunteers (n = 26; sex = 17 F/9M; age = 41.0 ±â€¯19.1 years) underwent brain MRI on a 3.0 T scanner. qMT data were acquired using a 3D MT-prepared spoiled gradient echo sequence. A traditional NM scan consisting of a T1-weighted turbo spin echo sequence with MT preparation was also acquired. The pool-size ratio (PSR) was estimated for each voxel using a single-point qMT approach. The LC was semi-automatically segmented on the MT-weighted images. The MT-weighted images provided higher contrast-ratio between the LC and surrounding pontine tegmentum (PT) (0.215 ±â€¯0.031) than the reference images without MT-preparation (-0.005 ±â€¯0.026) and the traditional NM images (0.138 ±â€¯0.044). The PSR maps showed significant differences between the LC (0.090 ±â€¯0.009) and PT (0.188 ±â€¯0.025). The largest difference between the PSR values in the LC and PT was observed in the central slices, which also correspond to those with the highest contrast-ratio. These results highlight the role of MT in generating NM-related contrast in the LC, and should serve as a foundation for future studies aiming to quantify pathological changes in the LC and surrounding structures in vivo.

7T quantitative magnetization transfer (qMT) of cortical gray matter in multiple sclerosis correlates with cognitive impairment.

Cognitive impairment (CI) is a major manifestation of multiple sclerosis (MS) and is responsible for extensively hindering patient quality of life. Cortical gray matter (cGM) damage is a significant contributor to CI, but is poorly characterized by conventional MRI let alone with quantitative MRI, such as quantitative magnetization transfer (qMT). Here we employed high-resolution qMT at 7T via the selective inversion recovery (SIR) method, which provides tissue-specific indices of tissue macromolecular content, such as the pool size ratio (PSR) and the rate of MT exchange (kmf). These indices could represent expected demyelination that occurs in the presence of gray matter damage. We utilized selective inversion recovery (SIR) qMT which provides a low SAR estimate of macromolecular-bulk water interactions using a tailored, B1 and B0 robust inversion recovery (IR) sequence acquired at multiple inversion times (TI) at 7T and fit to a two-pool model of magnetization exchange. Using this sequence, we evaluated qMT indices across relapsing-remitting multiple sclerosis patients (N = 19) and healthy volunteers (N = 37) and derived related associations with neuropsychological measures of cognitive impairment. We found a significant reduction in kmf in cGM of MS patients (15.5%, p = 0.002), unique association with EDSS (ρ = -0.922, p = 0.0001), and strong correlation with cognitive performance (ρ = -0.602, p = 0.0082). Together these findings indicate that the rate of MT exchange (kmf) may be a significant biomarker of cGM damage relating to CI in MS.

Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.

The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and longitudinal monitoring in MS. Automating this operation eliminates inter-rater variability and increases the efficiency of large-throughput analysis pipelines. Robust and reliable segmentation across multi-site spinal cord data is challenging because of the large variability related to acquisition parameters and image artifacts. In particular, a precise delineation of lesions is hindered by a broad heterogeneity of lesion contrast, size, location, and shape. The goal of this study was to develop a fully-automatic framework - robust to variability in both image parameters and clinical condition - for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data of MS and non-MS cases. Scans of 1042 subjects (459 healthy controls, 471 MS patients, and 112 with other spinal pathologies) were included in this multi-site study (n = 30). Data spanned three contrasts (T1-, T2-, and T2∗-weighted) for a total of 1943 vol and featured large heterogeneity in terms of resolution, orientation, coverage, and clinical conditions. The proposed cord and lesion automatic segmentation approach is based on a sequence of two Convolutional Neural Networks (CNNs). To deal with the very small proportion of spinal cord and/or lesion voxels compared to the rest of the volume, a first CNN with 2D dilated convolutions detects the spinal cord centerline, followed by a second CNN with 3D convolutions that segments the spinal cord and/or lesions. CNNs were trained independently with the Dice loss. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg (p ≤ 0.05), a state-of-the-art spinal cord segmentation method. Regarding lesion segmentation on MS data, our framework provided a Dice of 60%, a relative volume difference of -15%, and a lesion-wise detection sensitivity and precision of 83% and 77%, respectively. In this study, we introduce a robust method to segment the spinal cord and intramedullary MS lesions on a variety of MRI contrasts. The proposed framework is open-source and readily available in the Spinal Cord Toolbox.

Measurement of T2* in the human spinal cord at 3T.

PURPOSE: To measure the transverse relaxation time T2* in healthy human cervical spinal cord gray matter (GM) and white matter (WM) at 3T. METHODS: Thirty healthy volunteers were recruited. Axial images were acquired using an averaged multi-echo gradient-echo (mFFE) T2*-weighted sequence with 5 echoes. We used the signal equation for an mFFE sequence with constant dephasing gradients after each echo to jointly estimate the spin density and T2* for each voxel. RESULTS: No global difference in T2* was observed between all GM (41.3 ± 5.6 ms) and all WM (39.8 ± 5.4 ms). No significant differences were observed between left (43.2 ± 6.8 ms) and right (43.4 ± 5.5 ms) ventral GM, left (38.3 ± 6.1 ms) and right (38.6 ± 6.5 ms) dorsal GM, and left (39.4 ± 5.8 ms) and right (40.3 ± 5.8 ms) lateral WM. However, significant regional differences were observed between ventral (43.4 ± 5.7 ms) and dorsal (38.4 ± 6.0 ms) GM (p < 0.05), as well as between ventral (42.9 ± 6.5 ms) and dorsal (37.9 ± 6.2 ms) WM (p < 0.05). In analyses across slices, inferior T2* was longer than superior T2* in GM (44.7 ms vs. 40.1 ms; p < 0.01) and in WM (41.8 ms vs. 35.9 ms; p < 0.01). CONCLUSIONS: Significant differences in T2* are observed between ventral and dorsal GM, ventral and dorsal WM, and superior and inferior GM and WM. There is no evidence for bilateral asymmetry in T2* in the healthy cord. These values of T2* in the spinal cord are notably lower than most reported values of T2* in the cortex.

Trajectory optimized NUFFT: Faster non-Cartesian MRI reconstruction through prior knowledge and parallel architectures.

PURPOSE: The non-uniform fast Fourier transform (NUFFT) involves interpolation of non-uniformly sampled Fourier data onto a Cartesian grid, an interpolation that is slowed by complex, non-local data access patterns. A faster NUFFT would increase the clinical relevance of the plethora of advanced non-Cartesian acquisition methods. METHODS: Here we customize the NUFFT procedure for a radial trajectory and GPU architecture to eliminate the bottlenecks encountered when allowing for arbitrary trajectories and hardware. We call the result TRON, for TRajectory Optimized NUFFT. We benchmark the speed and accuracy TRON on a Shepp-Logan phantom and on whole-body continuous golden-angle radial MRI. RESULTS: TRON was 6-30× faster than the closest competitor, depending on test data set, and was the most accurate code tested. CONCLUSIONS: Specialization of the NUFFT algorithm for a particular trajectory yielded significant speed gains. TRON can be easily extended to other trajectories, such as spiral and PROPELLER. TRON can be downloaded at http://github.com/davidssmith/TRON.

Assessing thermal adaptation using family-based association and FST outlier tests in a threatened trout species.

Discovering genetic markers associated with phenotypic or ecological characteristics can improve our understanding of adaptation and guide conservation of key evolutionary traits. The Lahontan cutthroat trout (Oncorhynchus clarkii henshawi) of the northern Great Basin Desert, USA, demonstrated exceptional tolerance to high temperatures in the desert lakes where it resided historically. This trait is central to a conservation hatchery effort to protect the genetic legacy of the nearly extinct lake ecotype. We genotyped full-sibling families from this conservation broodstock and samples from the only two remaining, thermally distinct, native lake populations at 4,644 new single nucleotide polymorphisms (SNPs). Family-based genome-wide association testing of the broodstock identified nine and 26 SNPs associated with thermal tolerance (p < 0.05 and p < 0.1), measured in a previous thermal challenge experiment. Genes near the associated SNPs had complex functions related to immunity, growth, metabolism and ion homeostasis. Principal component analysis using the thermotolerance-related SNPs showed unexpected divergence between the conservation broodstock and the native lake populations at these loci. FST outlier tests on the native lake populations identified 18 loci shared between two or more of the tests, with two SNPs identified by all three tests (p < 0.01); none overlapped with loci identified by association testing in the broodstock. A recent history of isolation and the complex genetic and demographic backgrounds of Lahontan cutthroat trout probably limited our ability to find shared thermal tolerance loci. Our study extends the still relatively rare application of genomic tools testing for markers associated with important phenotypic or environmental characteristics in species of conservation concern.

Glutamate-sensitive imaging and evaluation of cognitive impairment in multiple sclerosis.

BACKGROUND: Cognitive impairment (CI) profoundly impacts quality of life for patients with multiple sclerosis (MS). Dysfunctional regulation of glutamate in gray matter (GM) has been implicated in the pathogenesis of MS by post-mortem pathological studies and in CI by in vivo magnetic resonance spectroscopy, yet GM pathology is subtle and difficult to detect using conventional T1- and T2-weighted magnetic resonance imaging (MRI). There is a need for high-resolution, clinically accessible imaging techniques that probe molecular changes in GM. OBJECTIVE: To study cortical GM pathology related to CI in MS using glutamate-sensitive chemical exchange saturation transfer (GluCEST) MRI at 7.0 Tesla (7T). METHODS: A total of 20 patients with relapsing-remitting MS and 20 healthy controls underwent cognitive testing, anatomical imaging, and GluCEST imaging. Glutamate-sensitive image contrast was quantified for cortical GM, compared between cohorts, and correlated with clinical measures of CI. RESULTS AND CONCLUSION: Glutamate-sensitive contrast was significantly increased in the prefrontal cortex of MS patients with accumulated disability (p < 0.05). In addition, glutamate-sensitive contrast in the prefrontal cortex was significantly correlated with symbol digit modality test (rS = -0.814) and choice reaction time (rS = 0.772) scores in patients (p < 0.05), suggesting that GluCEST MRI may have utility as a marker for GM pathology and CI.