ObjectiveConventional magnetic resonance imaging (MRI) of the multiple sclerosis spinal cord is limited by low specificity regarding the underlying pathological processes, and new MRI metrics assessing microscopic damage are required. We aim to show for the first time that neurite orientation dispersion (i.e., variability in axon/dendrite orientations) is a new biomarker that uncovers previously undetected layers of complexity of multiple sclerosis spinal cord pathology. Also, we validate against histology a clinically viable MRI technique for dispersion measurement (neurite orientation dispersion and density imaging, NODDI), to demonstrate the strong potential of the new marker.MethodsWe related quantitative metrics from histology and MRI in four post mortem spinal cord specimens (two controls; two progressive multiple sclerosis cases). The samples were scanned at high field, obtaining maps of neurite density and orientation dispersion from NODDI and routine diffusion tensor imaging (DTI) indices. Histological procedures provided markers of astrocyte, microglia, myelin and neurofilament density, as well as neurite dispersion.ResultsWe report from both NODDI and histology a trend toward lower neurite dispersion in demyelinated lesions, indicative of reduced neurite architecture complexity. Also, we provide unequivocal evidence that NODDI‐derived dispersion matches its histological counterpart (P < 0.001), while DTI metrics are less specific and influenced by several biophysical substrates.InterpretationNeurite orientation dispersion detects a previously undescribed and potentially relevant layer of microstructural complexity of multiple sclerosis spinal cord pathology. Clinically feasible techniques such as NODDI may play a key role in clinical trial and practice settings, as they provide histologically meaningful dispersion indices.

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication.

Diffusion MRI is being used increasingly in studies of the brain and other parts of the body for its ability to provide quantitative measures that are sensitive to changes in tissue microstructure. However, inter-scanner and inter-protocol differences are known to induce significant measurement variability, which in turn jeopardises the ability to obtain ‘truly quantitative measures’ and challenges the reliable combination of different datasets. Combining datasets from different scanners and/or acquired at different time points could dramatically increase the statistical power of clinical studies, and facilitate multi-centre research. Even though careful harmonisation of acquisition parameters can reduce variability, inter-protocol differences become almost inevitable with improvements in hardware and sequence design over time, even within a site. In this work, we present a benchmark diffusion MRI database of the same subjects acquired on three distinct scanners with different maximum gradient strength (40, 80, and 300 mT/m), and with ‘standard’ and ‘state-of-the-art’ protocols, where the latter have higher spatial and angular resolution. The dataset serves as a useful testbed for method development in cross-scanner/cross-protocol diffusion MRI harmonisation and quality enhancement. Using the database, we compare the performance of five different methods for estimating mappings between the scanners and protocols. The results show that cross-scanner harmonisation of single-shell diffusion data sets can reduce the variability between scanners, and highlight the promises and shortcomings of today's data harmonisation techniques.

Here we present the application of neurite orientation dispersion and density imaging (NODDI) to the healthy spinal cord in vivo. NODDI provides maps such as the intra-neurite tissue volume fraction (vin), the orientation dispersion index (ODI) and the isotropic volume fraction (viso), and here we investigate their potential for spinal cord imaging. We scanned five healthy volunteers, four of whom twice, on a 3T MRI system with a ZOOM-EPI sequence. In accordance to the published NODDI protocol, multiple b-shells were acquired at cervical level and both NODDI and diffusion tensor imaging (DTI) metrics were obtained and analysed to: i) characterise differences in grey and white matter (GM/WM); ii) assess the scan-rescan reproducibility of NODDI; iii) investigate the relationship between NODDI and DTI; and iv) compare the quality of fit of NODDI and DTI. Our results demonstrated that: i) anatomical features can be identified in NODDI maps, such as clear contrast between GM and WM in ODI; ii) the variabilities of vin and ODI are comparable to that of DTI and are driven by biological differences between subjects for ODI, have similar contribution from measurement errors and biological variation for vin, whereas viso shows higher variability, driven by measurement errors; iii) NODDI identifies potential sources contributing to DTI indices, as in the brain; and iv) NODDI outperforms DTI in terms of quality of fit. In conclusion, this work shows that NODDI is a useful model for in vivo diffusion MRI of the spinal cord, providing metrics closely related to tissue microstructure, in line with findings in the brain.

Quantitative spinal cord (SC) magnetic resonance imaging (MRI) is fraught with challenges, among which is the lack of standardized imaging protocols. Here we present a prospectively harmonized quantitative MRI protocol, which we refer to as the spine generic protocol, for the three main 3T MRI vendors: GE, Philips and Siemens. The protocol provides valuable metrics for assessing SC macrostructural and microstructural integrity: T1-weighted and T2-weighted imaging for SC cross-sectional area (CSA) computation, multi-echo gradient echo for gray matter CSA, as well as magnetization transfer and diffusion weighted imaging for assessing white matter microstructure. The spine generic protocol was used to acquire data across 42 centers in 260 healthy subjects, as detailed in the companion paper [REF-DATA]. The spine generic protocol is open-access and its latest version can be found at: https://spinalcordmri.org/protocols. The protocol will serve as a valuable starting point for researchers and clinicians implementing new SC imaging initiatives. Note to the reviewer/editor/publisher: the companion paper is referred to as [REF-DATA]6/52 121 122dealing with cervical myelopathy and MS populations. Applications of the MethodThe proposed protocol is not geared towards a specific disease and it is suitable for imaging WM pathology (demyelination and Wallerian degeneration via axon/myelin-sensitive 122 https://mssociety.ca/about-ms-research/about-our-research-program/research-we-fund/canadian-prospect ive-cohort-study-to-understand-progression-in-ms-canproco 121 https://www.wingsforlife.com/us/research/imaging-spinal-cord-injury-and-assessing-its-predictive-value-th e-inspired-study-2675/ 9/52

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Background: Multiple sclerosis (MS) affects both brain and spinal cord. However, studies of the neuraxis with advanced magnetic resonance imaging (MRI) are rare because of long acquisition times. We investigated neurodegeneration in MS brain and cervical spinal cord using neurite orientation dispersion and density imaging (NODDI). Objective: The aim of this study was to investigate possible alterations, and their clinical relevance, in neurite morphology along the brain and cervical spinal cord of relapsing–remitting MS (RRMS) patients. Methods: In total, 28 RRMS patients and 20 healthy controls (HCs) underwent brain and spinal cord NODDI at 3T. Physical and cognitive disability was assessed. Individual maps of orientation dispersion index (ODI) and neurite density index (NDI) in brain and spinal cord were obtained. We examined differences in NODDI measures between groups and the relationships between NODDI metrics and clinical scores using linear regression models adjusted for age, sex and brain tissue volumes or cord cross-sectional area (CSA). Results: Patients showed lower NDI in the brain normal-appearing white matter (WM) and spinal cord WM than HCs. In patients, a lower NDI in the spinal cord WM was associated with higher disability. Conclusion: Reduced neurite density occurs in the neuraxis but, especially when affecting the spinal cord, it may represent a mechanism of disability in MS.