F Grussu

Neurite orientation dispersion and density imaging of the healthy cervical spinal cord in vivo

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.

Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

Conventional 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.

Spinal cord grey matter segmentation challenge

ABSTRACT 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. HighlightsFirst grey matter spinal cord segmentation challenge.Six institutions participated in the challenge and compared their methods.Public available dataset from multiple vendors and sites.The challenge web site remains open to new submissions.

Bayesian Image Quality Transfer

Image quality transfer (IQT) aims to enhance clinical images of relatively low quality by learning and propagating high-quality structural information from expensive or rare data sets. However, the original framework gives no indication of confidence in its output, which is a significant barrier to adoption in clinical practice and downstream processing. In this article, we present a general Bayesian extension of IQT which enables efficient and accurate quantification of uncertainty, providing users with an essential prediction of the accuracy of enhanced images. We demonstrate the efficacy of the uncertainty quantification through super-resolution of diffusion tensor images of healthy and pathological brains. In addition, the new method displays improved performance over the original IQT and standard interpolation techniques in both reconstruction accuracy and robustness to anomalies in input images.

A framework for optimal whole-sample histological quantification of neurite orientation dispersion in the human spinal cord

BACKGROUND The complexity of fibre distributions in tissues is an important microstructural feature, now measurable in vivo by magnetic resonance imaging (MRI) through orientation dispersion (OD) indices. OD metrics have gained popularity for the characterisation of neurite morphology, but they still lack systematic validation. This paper demonstrates a framework for whole-sample histological quantification of OD in spinal cord specimens, potentially useful for validating MRI-derived OD estimates. NEW METHOD Our methodological framework is based on (i) sagittal sectioning; (ii) Palmgrens silver staining; (iii) structure tensor (ST) analysis; (iv) directional statistics. Novel elements are the data-driven optimisation of the spatial scale of ST analysis, and a new multivariate, weighted directional statistical approach for anisotropy-informed quantification of OD. RESULTS Palmgrens silver staining of sagittal spinal cord sections provides robust visualisation of neuronal elements, enabling OD quantification. The choice of spatial scale of ST analysis influences OD values, and weighted directional statistics provide OD maps with high contrast-to-noise. Segmentation of neurites prior to OD quantification is recommended. COMPARISON WITH EXISTING METHODS Our framework can potentially provide OD even in demyelinating diseases, where myelin-based histology is not suitable. As compared to conventional univariate approaches, our multivariate weighted directional statistics improve the contrast-to-noise of OD maps and more accurately describe the distribution of ST metrics. CONCLUSIONS Our framework enables practical whole-specimen characterisation of OD in the spinal cord. We recommend tuning the scale of ST analysis for optimal OD quantification, as well as neurite segmentation and weighted directional statistics, of which examples are provided herein.

Reduced field-of-view diffusion-weighted imaging of the lumbosacral enlargement: A pilot in vivo study of the healthy spinal cord at 3t

Diffusion tensor imaging (DTI) has recently started to be adopted into clinical investigations of spinal cord (SC) diseases. However, DTI applications to the lower SC are limited due to a number of technical challenges, related mainly to the even smaller size of the SC structure at this level, its position relative to the receiver coil elements and the effects of motion during data acquisition. Developing methods to overcome these problems would offer new means to gain further insights into microstructural changes of neurological conditions involving the lower SC, and in turn could help explain symptoms such as bladder and sexual dysfunction. In this work, the feasibility of obtaining grey and white matter (GM/WM) DTI indices such as axial/radial/mean diffusivity (AD/RD/MD) and fractional anisotropy (FA) within the lumbosacral enlargement (LSE) was investigated using a reduced field-of-view (rFOV) single-shot echo-planar imaging (ss-EPI) acquisition in 14 healthy participants using a clinical 3T MR system. The scan-rescan reproducibility of the measurements was assessed by calculating the percentage coefficient of variation (%COV). Mean FA was higher in WM compared to GM (0.58 and 0.4 in WM and GM respectively), AD and MD were higher in WM compared to GM (1.66 μm2ms-1 and 0.94 μm2ms-1 in WM and 1.2 μm2ms-1 and 0.82 μm2ms-1 in GM for AD and MD respectively) and RD was lower in WM compared to GM (0.58 μm2ms-1 and 0.63 μm2ms-1 respectively). The scan-rescan %COV was lower than 10% in all cases with the highest values observed for FA and the lowest for MD. This pilot study demonstrates that it is possible to obtain reliable tissue-specific estimation of DTI indices within the LSE using a rFOV ss-EPI acquisition. The DTI acquisition and analysis protocol presented here is clinically feasible and may be used in future investigations of neurological conditions implicating the lower SC.

Fast and reproducible in vivo T1 mapping of the human cervical spinal cord

To develop a fast and robust method for measuring T1 in the whole cervical spinal cord in vivo, and to assess its reproducibility.

An optimized framework for quantitative magnetization transfer imaging of the cervical spinal cord in vivo

To develop a framework to fully characterize quantitative magnetization transfer indices in the human cervical cord in vivo within a clinically feasible time.

Structural cortical network reorganization associated with early conversion to multiple sclerosis

Brain structural covariance networks (SCNs) based on pairwise statistical associations of cortical thickness data across brain areas reflect underlying physical and functional connections between them. SCNs capture the complexity of human brain cortex structure and are disrupted in neurodegenerative conditions. However, the longitudinal assessment of SCN dynamics has not yet been explored, despite its potential to unveil mechanisms underlying neurodegeneration. Here, we evaluated the changes of SCNs over 12 months in patients with a first inflammatory-demyelinating attack of the Central Nervous System and assessed their clinical relevance by comparing SCN dynamics of patients with and without conversion to multiple sclerosis (MS) over one year. All subjects underwent clinical and brain MRI assessments over one year. Brain cortical thicknesses for each subject and time point were used to obtain group-level between-area correlation matrices from which nodal connectivity metrics were obtained. Robust bootstrap-based statistical approaches (allowing sampling with replacement) assessed the significance of longitudinal changes. Patients who converted to MS exhibited significantly greater network connectivity at baseline than non-converters (p = 0.02) and a subsequent connectivity loss over time (p = 0.001–0.02), not observed in non-converters’ network. These findings suggest SCN analysis is sensitive to brain tissue changes in early MS, reflecting clinically relevant aspects of the condition. However, this is preliminary work, indicated by the low sample sizes, and its results and conclusions should be treated with caution and confirmed with larger cohorts.

Relevance of time-dependence for clinically viable diffusion imaging of the spinal cord

Time‐dependence is a key feature of the diffusion‐weighted (DW) signal, knowledge of which informs biophysical modelling. Here, we study time‐dependence in the human spinal cord, as its axonal structure is specific and different from the brain.