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Several recent multi-compartment diffusion MRI investigations and modeling strategies have utilized the orientationally-averaged, or spherical mean, diffusion-weighted signal to study tissue microstructure of the central nervous system. Most experimental designs sample a large number of diffusion weighted directions in order to calculate the spherical mean signal, however, sampling a subset of these directions may increase scanning efficiency and enable either a decrease in scan time or the ability to sample more diffusion weightings. Here, we aim to determine the minimum number of gradient directions needed for a robust measurement of the spherical mean signal. We used computer simulations to characterize the variation of the measured spherical mean signal as a function of the number of gradient directions, while also investigating the effects of diffusion weighting (b-value), signal-to-noise ratio (SNR), available hardware, and spherical mean fitting strategy. We then utilize empirically acquired data in the brain and spinal cord to validate simulations, showing experimental results are in good agreement with simulations. We summarize these results by providing an intuitive lookup table to facilitate the determination of the minimal number of sampling directions needed for robust spherical mean measurements, and give recommendations based on SNR and experimental conditions.

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.

Background and purpose Axonal injury is a key player of disability in persons with multiple sclerosis (pwMS). Yet, detecting and measuring it in vivo is challenging. The neurite orientation dispersion and density imaging (NODDI) proposes a novel framework for probing axonal integrity in vivo. NODDI at 3.0 Tesla was used to quantify tissue damage in pwMS and its relationship with disease progression. Methods Eighteen pwMS (4 clinically isolated syndrome, 11 relapsing remitting, and 3 secondary progressive MS) and nine age- and sex-matched healthy controls underwent a brain MRI, inclusive of clinical sequences and a multi-shell diffusion acquisition. Parametric maps of axial diffusivity (AD), neurite density index (ndi), apparent isotropic volume fraction (ivf), and orientation dispersion index (odi) were fitted. Anatomically matched regions of interest were used to quantify AD and NODDI-derived metrics and to assess the relations between these measures and those of disease progression. Results AD, ndi, ivf, and odi significantly differed between chronic black holes (cBHs) and T2-lesions, and between the latter and normal appearing white matter (NAWM). All metrics except ivf significantly differed between NAWM located next to a cBH and that situated contra-laterally. Only NAWM odi was significantly associated with T2-lesion volume, the timed 25-foot walk test and disease duration. Conclusions NODDI is sensitive to tissue injury but its relationship with clinical progression remains limited.

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 3 Tesla. 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. CONCLUSION: Highly multi-shot acquisition sequences such as 3D-FFE are well suited for stimulus-evoked spinal cord BOLD fMRI.

Clinicians involved with different aspects of the care of persons with multiple sclerosis (MS) and scientists with expertise on clinical and imaging techniques convened in Dallas, TX, USA on February 27, 2019 at a North American Imaging in Multiple Sclerosis Cooperative workshop meeting. The aim of the workshop was to discuss cardinal pathobiological mechanisms implicated in the progression of MS and novel imaging techniques, beyond brain atrophy, to unravel these pathologies. Indeed, although brain volume assessment demonstrates changes linked to disease progression, identifying the biological mechanisms leading up to that volume loss are key for understanding disease mechanisms. To this end, the workshop focused on the application of advanced magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging techniques to assess and measure disease progression in both the brain and the spinal cord. Clinical translation of quantitative MRI was recognized as of vital importance, although the need to maintain a relatively short acquisition time mandated by most radiology departments remains the major obstacle toward this effort. Regarding PET, the panel agreed upon its utility to identify ongoing pathological processes. However, due to costs, required expertise, and the use of ionizing radiation, PET was not considered to be a viable option for ongoing care of persons with MS. Collaborative efforts fostering robust study designs and imaging technique standardization across scanners and centers are needed to unravel disease mechanisms leading to progression and discovering medications halting neurodegeneration and/or promoting repair.

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.

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.

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 a denoising approach, Patch2Self, to improve the quality, reliability, and accuracy of quantitative diffusion MRI of the spinal cord. Patch2Self is a self-supervised learning-based denoising method that leverages statistical independence of noise to suppress signal components strictly originating from random fluctuations. We conduct three experiments to validate the denoising performance of Patch2Self on clinical-quality, single-shell dMRI acquisitions with a small number of gradient directions: 1) inter-session scanrescan in healthy volunteers to evaluate enhancements in image contrast and model fitting; 2) repeated intra-session scans in a healthy volunteer to compare signal averaging to Patch2Self; and 3) assessment of spinal cord lesion conspicuity in a multiple sclerosis group. We find that Patch2Self improves intra-cord contrast, signal modeling, SNR, and lesion conspicuity within the spinal cord. This denoising approach holds promise for facilitating reliable diffusion measurements in the spinal cord to investigate biological and pathological processes.

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/. The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord., Measurement(s)spinal cordTechnology Type(s)magnetic resonance imagingFactor Type(s)manufacturer • siteSample Characteristic - OrganismHomo sapiensSample Characteristic - LocationCanada • Switzerland • Australia • United States of America • United Kingdom • Germany • French Republic • Czech Republic • Italy • Japan • Kingdom of Spain • China Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14052269

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 ± 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 ± 0.031) than the reference images without MT-preparation (−0.005 ± 0.026) and the traditional NM images (0.138 ± 0.044). The PSR maps showed significant differences between the LC (0.090 ± 0.009) and PT (0.188 ± 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.

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 Conclusion:SIR-qMT at 3 T is clinically feasible and predicts both radiological and clinical disease severity in MS.

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/ . The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord.

Magnetization transfer (MT) is an MRI phenomenon, whereby protons associated with semi-solid-like macromolecules exchange information with surrounding water. Typically, MRI exploits water protons to form images, and the contrast between tissue types is driven largely by proton density and water relaxation. However, protons associated with macromolecules, which in the central nervous system is largely myelin, are not able to be imaged directly, but through MT we can image the effect of the macromolecular protons on water and derive an indirect measure of macromolecular composition within tissue. This opens the door to being able to assess certain types of pathology such as myelin damage in vivo. Our purpose is to provide a background on MT, the MT phenomenon, its biochemical origin, common quantification methods, including quantitative MT (qMT) at high and low field strengths. We will show brief examples to demonstrate the utility of MT MRI in vivo.

Diffusion magnetic resonance images may suffer from geometric distortions due to susceptibility induced off resonance fields, which cause geometric mismatch with anatomical images and ultimately affect subsequent quantification of microstructural or connectivity indices. State-of-the art diffusion distortion correction methods typically require data acquired with reverse phase encoding directions, resulting in varying magnitudes and orientations of distortion, which allow estimation of an undistorted volume. Alternatively, additional field maps acquisitions can be used along with sequence information to determine warping fields. However, not all imaging protocols include these additional scans and cannot take advantage of state-of-the art distortion correction. To avoid additional acquisitions, structural MRI (undistorted scans) can be used as registration targets for intensity driven correction. In this study, we aim to (1) enable susceptibility distortion correction with historical and/or limited diffusion datasets that do not include specific sequences for distortion correction and (2) avoid the computationally intensive registration procedure typically required for distortion correction using structural scans. To achieve these aims, we use deep learning (3D U-nets) to synthesize an undistorted b0 image that matches geometry of structural T1w images and intensity contrasts from diffusion images. Importantly, the training dataset is heterogenous, consisting of varying acquisitions of both structural and diffusion. We apply our approach to a withheld test set and show that distortions are successfully corrected after processing. We quantitatively evaluate the proposed distortion correction and intensity-based registration against state-of-the-art distortion correction (FSL topup). The results illustrate that the proposed pipeline results in b0 images that are geometrically similar to non-distorted structural images, and more closely match state-of-the-art correction with additional acquisitions. In addition, we show generalizability of the proposed approach to datasets that were not in the original training / validation / testing datasets. These datasets included varying populations, contrasts, resolutions, and magnitudes and orientations of distortion and show efficacious distortion correction. The method is available as a Singularity container, source code, and an executable trained model to facilitate evaluation.

Magnetization transfer (MT)–magnetic resonance imaging (MRI) techniques can provide access to visualizing macromolecular content of tissues, otherwise not assessable using conventional MRI. MT contrast is generated by the interaction between mobile water protons and the protons associated with tissue macromolecules. Given substantial variation between macromolecular compositions of tissues, this interaction differs by tissue type and results in macromolecular-sensitive contrast in MT-weighted images. MT contrast is generated by applying radiofrequency pulses to selectively saturate the macromolecular protons, and this saturation is transferred to the water protons resulting in an observed signal attenuation. The MT effect can be characterized via the MT ratio (MTR) and, more recently, via quantitative MT (qMT) methods. MT-MRI indices may be useful to detect and quantify macromolecular alterations, potentially offering unique opportunities to link pathophysiologic and clinical outcomes in disorders of the central nervous system (CNS), and response to treatments.

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.

Background and purpose An imaging biomarker of myelin integrity is an unmet need in multiple sclerosis (MS). Selective inversion recovery (SIR) quantitative magnetization transfer imaging (qMT) provides assays of myelin content in the human brain. We previously translated the SIR method to 7T and incorporated a rapid turbo field echo (TFE) readout for whole-brain imaging within clinically acceptable scan times. We herein provide histological validation and test in vivo feasibility and applicability of the SIR-TFE protocol in MS. Methods Clinical (T1 - and T2 -weighted) and SIR-TFE MRI scans were performed at 7T in a postmortem MS brain and MRI data were acquired in 10 MS patients and 14 heathy volunteers in vivo. The following parameters were estimated from SIR data: the macromolecular-to-free water pool-size-ratio (PSR), the spin-lattice relaxation rate of water (R1f ), and the MT exchange rate (kmf ). Differences in SIR parameters across tissue types, eg, white matter lesions (WM-Ls) and normal appearing WM (NAWM) in patients, and normal white matter (NWM) in heathy volunteers were evaluated. Associations between SIR parameters and disability scores were assessed. Results For postmortem scans, correspondence was observed between WM-Ls and NAWM from histology and PSR/R1f values. In vivo differences were detected for PSR, R1f , and kmf between WM-Ls and NWM (P ≤ .041). Associations were seen between WM-Ls/ NAWM PSR and disability scores (r ≤ -.671, P ≤ .048). Conclusions SIR-qMT at 7T provides sensitive, quantitative measures of myelin integrity for clinical and research applications.

Purpose The ability to evaluate pathological changes in the spinal cord in multiple sclerosis (MS) is limited because T1- and T2-w MRI imaging are not sensitive to biochemical changes in vivo. Amide proton transfer (APT) chemical exchange saturation transfer (CEST) can indirectly detect amide protons associated with proteins and peptides, potentially providing more pathological specificity. Here, we implement APT CEST in the cervical spinal cord of healthy and MS cohorts at 3T. Methods APT CEST of the cervical spinal cord was obtained in a cohort of 10 controls and 10 MS patients using a novel respiratory correction methodology. APT was quantified using two methods: 1) APTw, based off the conventional magnetization transfer ratio asymmetry, and 2) ΔAPT, a spatial characterization of APT changes in MS patients relative to the controls. Results Respiratory correction yielded highly reproducible z-spectra in white matter (intraclass correlation coefficient = 0.82). APTw signals in normal-appearing white matter (NAWM) of MS patients were significantly different from healthy controls (P = 0.04), whereas ΔAPT of MS patients highlighted large APT differences in NAWM. Conclusion Respiration correction in the spinal cord is necessary to accurately quantify APT CEST, which can provide unique biochemical information regarding disease processes within the spinal cord. Magn Reson Med 79:806–814, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Purpose To investigate the physical mechanisms associated with the contrast observed in neuromelanin MRI. Methods Phantoms having different concentrations of synthetic melanins with different degrees of iron loading were examined on a 3 Tesla scanner using relaxometry and quantitative magnetization transfer (MT). Results Concentration-dependent T1 and T2 shortening was most pronounced for the melanin pigment when combined with iron. Metal-free melanin had a negligible effect on the magnetization transfer spectra. On the contrary, the presence of iron-laden melanins resulted in a decreased magnetization transfer ratio. The presence of melanin or iron (or both) did not have a significant effect on the macromolecular content, represented by the pool size ratio. Conclusion The primary mechanism underlying contrast in neuromelanin-MRI appears to be the T1 reduction associated with melanin-iron complexes. The macromolecular content is not significantly influenced by the presence of melanin with or without iron, and thus the MT is not directly affected. However, as T1 plays a role in determining the MT-weighted signal, the magnetization transfer ratio is reduced in the presence of melanin-iron complexes. Magn Reson Med, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

Increasing reliance on electronic medical records at large medical centers provides unique opportunities to perform population level analyses exploring disease progression and etiology. The massive accumulation of diagnostic, procedure, and laboratory codes in one place has enabled the exploration of co-occurring conditions, their risk factors, and potential prognostic factors. While most of the readily identifiable associations in medical records are (now) well known to the scientific community, there is no doubt many more relationships are still to be uncovered in EMR data. In this paper, we introduce a novel finding index to help with that task. This new index uses data mined from real-time PubMed abstracts to indicate the extent to which empirically discovered associations are already known (i.e., present in the scientific literature). Our methods leverage second-generation p-values, which better identify associations that are truly clinically meaningful. We illustrate our new method with three examples: Autism Spectrum Disorder, Alzheimer's Disease, and Optic Neuritis. Our results demonstrate wide utility for identifying new associations in EMR data that have the highest priority among the complex web of correlations and causalities. Data scientists and clinicians can work together more effectively to discover novel associations that are both empirically reliable and clinically understudied.

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.

International audience; 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.

BACKGROUND AND PURPOSE: The purpose of the study is to characterize diffusion tensor imaging indices in the developing spinal cord, evaluating differences based on age and cord region. Describing the progression of DTI indices in the pediatric cord increases our understanding of spinal cord development. MATERIALS AND METHODS: A retrospective analysis was performed on DTI acquired in 121 pediatric patients (mean, 8.6 years; range, 0.3–18.0 years) at Monroe Carell Jr. Children's Hospital at Vanderbilt from 2017 to 2018. Diffusion-weighted images (15 directions; b = 750 s/mm(2); slice thickness, 5 mm; in-plane resolution, 1.0 × 1.0 mm(2)) were acquired on a 3T scanner in the cervicothoracic and/or thoracolumbar cord. Manual whole-cord segmentation was performed. Images were masked and further segmented into cervical, upper thoracic, thoracolumbar, and conus regions. Analyses of covariance were performed for each DTI-derived index to investigate how age affects diffusion across cord regions, and 95% confidence intervals were calculated across age for each derived index and region. Post hoc testing was performed to analyze regional differences. RESULTS: Analyses of covariance revealed significant correlations of age with axial diffusivity, mean diffusivity, and fractional anisotropy (all, P < .001). There were also significant differences among cord regions for axial diffusivity, radial diffusivity, mean diffusivity, and fractional anisotropy (all, P < .001). CONCLUSIONS: This research demonstrates that diffusion evolves in the pediatric spinal cord during development, dependent on both cord region and the diffusion index of interest. Future research could investigate how diffusion may be affected by common pediatric spinal pathologies.

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. 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. Scans of 1,042 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 1,943 volumes. 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. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg, 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. The proposed framework is open-source and readily available in the Spinal Cord Toolbox., Comment: 38 pages, 7 figures, 2 tables

Objects The diffusion‐based spherical mean technique (SMT) provides a novel model to relate multi‐b‐value diffusion magnetic resonance imaging (MRI) data to features of tissue microstructure. We propose the first clinical application of SMT to image the brain of patients with multiple sclerosis (MS) and investigate clinical feasibility and translation. Methods Eighteen MS patients and nine age‐ and sex‐matched healthy controls (HCs) underwent a 3.0 Tesla scan inclusive of clinical sequences and SMT images (isotropic resolution of 2 mm). Axial diffusivity (AD), apparent axonal volume fraction (V ax), and effective neural diffusivity (D ax) parametric maps were fitted. Differences in AD, V ax, and D ax between anatomically matched regions reflecting different tissues types were estimated using generalized linear mixed models for binary outcomes. Results Differences were seen in all SMT‐derived parameters between chronic black holes (cBHs) and T2‐lesions (P ≤ 0.0016), in V ax and AD between T2‐lesions and normal appearing white matter (NAWM) (P

BACKGROUND: Axonal injury is the primary source of irreversible neurological decline in persons with multiple sclerosis (pwMS). Identifying and quantifying myelin and axonal loss in lesional and perilesional tissue in vivo is fundamental for a better understanding of multiple sclerosis (MS) outcomes and patient impairment. Using advanced magnetic resonance imaging (MRI) methods, consisting of selective inversion recovery quantitative magnetization transfer imaging (SIR-qMT) and multi-compartment diffusion MRI with the spherical mean technique (SMT), we conducted a cross-sectional pilot study to assess myelin and axonal damage in the normal appearing white matter (NAWM) surrounding chronic black holes (cBHs) and how this pathology correlates with disability in vivo. We hypothesized that lesional axonal transection propagates tissue injury in the surrounding NAWM and that the degree of this injury is related to patient disability. METHODS: Eighteen pwMS underwent a 3.0 Tesla conventional clinical MRI, inclusive of T1 and T2 weighted protocols, as well as SIR-qMT and SMT. Regions of interests (ROIs) were manually delineated in cBHs, NAWM neighboring cBHs (perilesional NAWM), distant ipsilateral NAWM and contra-lateral distant NAWM. SIR-qMT-derived macromolecular-to-free pool size ratio (PSR) and SMT-derived apparent axonal volume fraction (V(ax)) were extracted to infer on myelin and axonal content, respectively. Group differences were assessed using mixed-effects regression models and correlation analyses were obtained by bootstrapping 95% confidence interval. RESULTS: In comparison to perilesional NAWM, both PSR and V(ax) values were reduced in cBHs (p < 0.0001) and increased in distant contra-lateral NAWM ROIs (p < 0.001 for PSR and p < 0.0001 for V(ax)) but not ipsilateral NAWM (p = 0.176 for PSR and p = 0.549 for V(ax)). V(ax) values measured in cBHs correlated with those in perilesional NAWM (Pearson rho = 0.63, p < 0.001). No statistically relevant associations were seen between PSR/V(ax) values and clinical and/or MRI metrics of the disease with the exception of cBH PSR values, which correlated with the Expanded Disability Status Scale (Pearson rho = −0.63, p = 0.03). CONCLUSIONS: Our results show that myelin and axonal content, detected by PSR and V(ax), are reduced in perilesional NAWM, as a function of the degree of focal cBH axonal injury. This finding is indicative of an ongoing anterograde/retrograde degeneration and suggests that treatment prevention of cBH development is a key factor for preserving NAWM integrity in surrounding tissue. It also suggests that measuring changes in perilesional areas over time may be a useful measure of outcome for proof-of-concept clinical trials on neuroprotection and repair. PSR and V(ax) largely foiled to capture associations with clinical and MRI characteristics, likely as a result of the small sample size and cross-sectional design, however, longitudinal assessment of a larger cohort may unravel the impact of this pathology on disease progression.