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.

Pathophysiological changes in the white and gray matter resulting from spinal cord injury can be revealed by magnetic resonance imaging (MRI) techniques that provides sensitive markers of macro-and microstructural integrity with important histological correlates. This review highlights spinal cord pathology in traumatic spinal cord injury (tSCI) and in non-traumatic spinal cord injury (i.e. degenerative cervical myelopathy (DCM)), detected by means of cross-sectional area measurements and spinal cord diffusion tensor imaging (DTI), and outlines the current trends and future directions.Cord MRI findings in these pathologies have provided important insights into the pathophysiological processes not just at the focal injury site, but also rostral and caudal to the spinal injury. Interestingly, although tSCI and DCM have different etiologies, they show similar magnitudes of remote tissue specific cord pathology, which suggests similar secondary degenerative mechanisms in tSCI and DCM.Advanced quantitative MRI protocols sensitive to tissue specific cord pathology have the potential to enhance current diagnosis and, more importantly, predict outcome in patients with traumatic and non-traumatic spinal cord injury. It is a promising area of research ripe for further study.

Agenesis of the corpus callosum (AgCC) is a congenital condition associated with wide-ranging emotional and social impairments often overlapping with the diagnostic criteria for autism. Mapping functional connectivity in the acallosal brain can help identify neural correlates of the deficits associated with this condition, and elucidate how congenital white matter alterations shape the topology of large-scale functional networks. By using resting-state BOLD functional magnetic resonance imaging (rsfMRI), here we show that acallosal BTBR T+tpr3tf/J (BTBR) mice, an idiopathic model of autism, exhibit impaired intra-hemispheric connectivity in fronto-cortical, but not in posterior sensory cortical areas. We also document profoundly altered subcortical and intra-hemispheric connectivity networks, with evidence of marked fronto-thalamic and striatal disconnectivity, along with aberrant spatial extension and strength of ipsilateral and local connectivity. Importantly, inter-hemispheric tracing of monosynaptic connections in the primary visual cortex using recombinant rabies virus confirmed the absence of direct homotopic pathways between posterior cortical areas of BTBR mice, suggesting a polysynaptic origin for the synchronous rsfMRI signal observed in these regions. Collectively, the observed long-range connectivity impairments recapitulate hallmark neuroimaging findings in autism, and are consistent with the behavioral phenotype of BTBR mice. In contrast to recent rsfMRI studies in high functioning AgCC individuals, the profound fronto-cortical and subcortical disconnectivity mapped suggest that compensatory mechanism may not necessarily restore the full connectional topology of the brain, resulting in residual connectivity alterations that serve as plausible substrates for the cognitive and emotional deficits often associated with AgCC.