Axons morphometry in the human spinal cord

Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

Electrospun drug-loaded scaffolds for nervous system repair

Nervous system injuries, encompassing peripheral nerve injury (PNI), spinal cord injury (SCI), and traumatic brain injury (TBI), present significant challenges to patients' wellbeing. Traditional treatment approaches have limitations in addressing the complexity of neural tissue regeneration and require innovative solutions. Among emerging strategies, implantable materials, particularly electrospun drug-loaded scaffolds, have gained attention for their potential to simultaneously provide structural support and controlled release of therapeutic agents. This review provides a thorough exploration of recent developments in the design and application of electrospun drug-loaded scaffolds for nervous system repair. The electrospinning process offers precise control over scaffold characteristics, including mechanical properties, biocompatibility, and topography, crucial for creating a conducive environment for neural tissue regeneration. The large surface area of the resulting fibrous networks enhances biomolecule attachment, influencing cellular behaviors such as adhesion, proliferation, and migration. Polymeric electrospun materials demonstrate versatility in accommodating a spectrum of therapeutics, from small molecules to proteins. This enables tailored interventions to accelerate neuroregeneration and mitigate inflammation at the injury site. A critical aspect of this review is the examination of the interplay between structural properties and pharmacological effects, emphasizing the importance of optimizing both aspects for enhanced therapeutic outcomes. Drawing upon the latest advancements in the field, we discuss the promising outcomes of preclinical studies using electrospun drug-loaded scaffolds for nervous system repair, as well as future perspectives and considerations for their design and implementation. This article is categorized under: Implantable Materials and Surgical Technologies > Nanomaterials and Implants Implantable Materials and Surgical Technologies > Nanotechnology in Tissue Repair and Replacement Therapeutic Approaches and Drug Discovery > Emerging Technologies.

Direct jet coaxial electrospinning of axon-mimicking fibers for diffusion tensor imaging

Hollow polymer microfibers with variable microstructural and hydrophilic properties were proposed as building elements to create axon-mimicking phantoms for validation of diffusion tensor imaging (DTI). The axon-mimicking microfibers were fabricated in a mm-thick 3D anisotropic fiber strip, by direct jet coaxial electrospinning of PCL/polysiloxane-based surfactant (PSi) mixture as shell and polyethylene oxide (PEO) as core. Hydrophilic PCL-PSi fiber strips were first obtained by carefully selecting appropriate solvents for the core and appropriate fiber collector rotating and transverse speeds. The porous cross-section and anisotropic orientation of axon-mimicking fibers were then quantitatively evaluated using two ImageJ plugins-nearest distance (ND) and directionality based on their scanning electron microscopy (SEM) images. Third, axon-mimicking phantom was constructed from PCL-PSi fiber strips with variable porous-section and fiber orientation and tested on a 3T clinical MR scanner. The relationship between DTI measurements (mean diffusivity [MD] and fractional anisotropy [FA]) of phantom samples and their pore size and fiber orientation was investigated. Two key microstructural parameters of axon-mimicking phantoms including normalized pore distance and dispersion of fiber orientation could well interpret the variations in DTI measurements. Two PCL-PSi phantom samples made from different regions of the same fiber strips were found to have similar MD and FA values, indicating that the direct jet coaxial electrospun fiber strips had consistent microstructure. More importantly, the MD and FA values of the developed axon-mimicking phantoms were mostly in the biologically relevant range.

Temporal Diffusion Ratio (TDR) for imaging restricted diffusion: Optimisation and pre-clinical demonstration

Temporal Diffusion Ratio (TDR) is a recently proposed dMRI technique (Dell'Acqua et al., proc. ISMRM 2019) which provides contrast between areas with restricted diffusion and areas either without restricted diffusion or with length scales too small for characterisation. Hence, it has a potential for informing on pore sizes, in particular the presence of large axon diameters or other cellular structures. TDR employs the signal from two dMRI acquisitions obtained with the same, large, b-value but with different diffusion gradient waveforms. TDR is advantageous as it employs standard acquisition sequences, does not make any assumptions on the underlying tissue structure and does not require any model fitting, avoiding issues related to model degeneracy. This work for the first time introduces and optimises the TDR method in simulation for a range of different tissues and scanner constraints and validates it in a pre-clinical demonstration. We consider both substrates containing cylinders and spherical structures, representing cell soma in tissue. Our results show that contrasting an acquisition with short gradient duration, short diffusion time and high gradient strength with an acquisition with long gradient duration, long diffusion time and low gradient strength, maximises the TDR contrast for a wide range of pore configurations. Additionally, in the presence of Rician noise, computing TDR from a subset (50% or fewer) of the acquired diffusion gradients rather than the entire shell as proposed originally further improves the contrast. In the last part of the work the results are demonstrated experimentally on rat spinal cord. In line with simulations, the experimental data shows that optimised TDR improves the contrast compared to non-optimised TDR. Furthermore, we find a strong correlation between TDR and histology measurements of axon diameter. In conclusion, we find that TDR has great potential and is a very promising alternative (or potentially complement) to model-based approaches for informing on pore sizes and restricted diffusion in general.

Variation in Diffusion Tensor Imaging Parameters in the Cervical and Thoracic Spinal Cord (C1-C5 and C6-T2) Segments of Normal Beagle Dogs

This study aimed to determine the characteristics and reference values of each vertebra in the cervicothoracic region by performing diffusion tensor imaging (DTI) scans and analyzing DTI parameters in normal Beagle dogs. In five adult Beagles under anesthetic maintenance, DTI was performed using a 1.5-T magnetic resonance imaging (MRI) scanner. Axial DTI was performed using three overlapping slabs to cover the cervical and thoracic spinal cords. After post-processing, DTI parameters were calculated along the entire spinal cord. Among DTI parameters, fractional anisotropy, relative anisotropy, and axonal diffusivity significantly decreased in the caudal direction. However, the apparent diffusion coefficient, radial diffusivity, and mean diffusivity values were not significantly correlated with vertebral levels. We provide evidence for the existence of segment-dependent DTI parameters in the canine cervical spinal cord. Therefore, comparisons of DTI parameters between lesions at different vertebral levels should be avoided unless normative data are available. Furthermore, the DTI data obtained in this study may contribute to the development of a clinical reference for spinal cord evaluation in dogs using DTI parameters.

Histology-informed automatic parcellation of white matter tracts in the rat spinal cord

The white matter is organized into “tracts” or “bundles,” which connect different parts of the central nervous system. Knowing where these tracts are located in each individual is important for understanding the cause of potential sensorial, motor or cognitive deficits and for developing appropriate treatments. Traditionally, tracts are found using tracer injection, which is a difficult, slow and poorly scalable technique. However, axon populations from a given tract exhibit specific characteristics in terms of morphometrics and myelination. Hence, the delineation of tracts could, in principle, be done based on their morphometry. The objective of this study was to generate automatic parcellation of the rat spinal white matter tracts using the manifold information from scanning electron microscopy images of the entire spinal cord. The axon morphometrics (axon density, axon diameter, myelin thickness and g-ratio) were computed pixelwise following automatic axon segmentation using AxonSeg. The parcellation was based on an agglomerative clustering algorithm to group the tracts. Results show that axon morphometrics provide sufficient information to automatically identify some white matter tracts in the spinal cord, however, not all tracts were correctly identified. Future developments of microstructure quantitative MRI even bring hope for a personalized clustering of white matter tracts in each individual patient. The generated atlas and the associated code can be found at https://github.com/neuropoly/tract-clustering.

Viscoelastic damage evaluation of the axon

In this manuscript, we have studied the microstructure of the axonal cytoskeleton and adopted a bottom-up approach to evaluate the mechanical responses of axons. The cytoskeleton of the axon includes the microtubules (MT), Tau proteins (Tau), neurofilaments (NF), and microfilaments (MF). Although most of the rigidity of the axons is due to the MT, the viscoelastic response of axons comes from the Tau. Early studies have shown that NF and MF do not provide significant elasticity to the overall response of axons. Therefore, the most critical aspect of the mechanical response of axons is the microstructural topology of how MT and Tau are connected and construct the cross-linked network. Using a scanning electron microscope (SEM), the cross-sectional view of the axons revealed that the MTs are organized in a hexagonal array and cross-linked by Tau. Therefore, we have developed a hexagonal Representative Volume Element (RVE) of the axonal microstructure with MT and Tau as fibers. The matrix of the RVE is modeled by considering a combined effect of NF and MF. A parametric study is done by varying fiber geometric and mechanical properties. The Young’s modulus and spacing of MT are varied between 1.5 and 1.9 GPa and 20–38 nm, respectively. Tau is modeled as a 3-parameter General Maxwell viscoelastic material. The failure strains for MT and Tau are taken to be 50 and 40%, respectively. A total of 4 RVEs are prepared for finite element analysis, and six loading cases are inspected to quantify the three-dimensional (3D) viscoelastic relaxation response. The volume-averaged stress and strain are then used to fit the relaxation Prony series. Next, we imposed varying strain rates (between 10/sec to 50/sec) on the RVE and analyzed the axonal failure process. We have observed that the 40% failure strain of Tau is achieved in all strain rates before the MT reaches its failure strain of 50%. The corresponding axonal failure strain and stress vary between 6 and 11% and 5–19.8 MPa, respectively. This study can be used to model macroscale axonal aggregate typical of the white matter region of the brain tissue.

Rapid, automated nerve histomorphometry through open-source artificial intelligence

We aimed to develop and validate a deep learning model for automated segmentation and histomorphometry of myelinated peripheral nerve fibers from light microscopic images. A convolutional neural network integrated in the AxonDeepSeg framework was trained for automated axon/myelin segmentation using a dataset of light-microscopic cross-sectional images of osmium tetroxide-stained rat nerves including various axonal regeneration stages. In a second dataset, accuracy of automated segmentation was determined against manual axon/myelin labels. Automated morphometry results, including axon diameter, myelin sheath thickness and g-ratio were compared against manual straight-line measurements and morphometrics extracted from manual labels with AxonDeepSeg as a reference standard. The neural network achieved high pixel-wise accuracy for nerve fiber segmentations with a mean (± standard deviation) ground truth overlap of 0.93 (± 0.03) for axons and 0.99 (± 0.01) for myelin sheaths, respectively. Nerve fibers were identified with a sensitivity of 0.99 and a precision of 0.97. For each nerve fiber, the myelin thickness, axon diameter, g-ratio, solidity, eccentricity, orientation, and individual x -and y-coordinates were determined automatically. Compared to manual morphometry, automated histomorphometry showed superior agreement with the reference standard while reducing the analysis time to below 2.5% of the time needed for manual morphometry. This open-source convolutional neural network provides rapid and accurate morphometry of entire peripheral nerve cross-sections. Given its easy applicability, it could contribute to significant time savings in biomedical research while extracting unprecedented amounts of objective morphologic information from large image datasets.

Mapping the rest of the human connectome: Atlasing the spinal cord and peripheral nervous system

The emergence of diffusion, structural, and functional neuroimaging methods has enabled major multi-site efforts to map the human connectome, which has heretofore been defined as containing all neural connections in the central nervous system (CNS). However, these efforts are not structured to examine the richness and complexity of the peripheral nervous system (PNS), which arguably forms the (neglected) rest of the connectome. Despite increasing interest in an atlas of the spinal cord (SC) and PNS which is simultaneously stereotactic, interactive, electronically dissectible, scalable, population-based and deformable, little attention has thus far been devoted to this task of critical importance. Nevertheless, the atlasing of these complete neural structures is essential for neurosurgical planning, neurological localization, and for mapping those components of the human connectome located outside of the CNS. Here we recommend a modification to the definition of the human connectome to include the SC and PNS, and argue for the creation of an inclusive atlas to complement current efforts to map the brain's human connectome, to enhance clinical education, and to assist progress in neuroscience research. In addition to providing a critical overview of existing neuroimaging techniques, image processing methodologies and algorithmic advances which can be combined for the creation of a full connectome atlas, we outline a blueprint for ultimately mapping the entire human nervous system and, thereby, for filling a critical gap in our scientific knowledge of neural connectivity.

Multiscale Imaging Approach for Studying the Central Nervous System: Methodology and Perspective

Non-invasive imaging methods have become essential tools for understanding the central nervous system (CNS) in health and disease. In particular, magnetic resonance imaging (MRI) techniques provide information about the anatomy, microstructure, and function of the brain and spinal cord in vivo non-invasively. However, MRI is limited by its spatial resolution and signal specificity. In order to mitigate these shortcomings, it is crucial to validate MRI with an array of ancillary ex vivo imaging techniques. These techniques include histological methods, such as light and electron microscopy (EM), which can provide specific information on the tissue structure in healthy and diseased brain and spinal cord, at cellular and subcellular level. However, these conventional histological techniques are intrinsically two-dimensional (2D) and, as a result of sectioning, lack volumetric information of the tissue. This limitation can be overcome with genuine three-dimensional (3D) imaging approaches of the tissue. 3D highly resolved information of the CNS achievable by means of other imaging techniques can complement and improve the interpretation of MRI measurements. In this article, we provide an overview of different 3D imaging techniques that can be used to validate MRI. As an example, we introduce an approach of how to combine diffusion MRI and synchrotron X-ray phase contrast tomography (SXRPCT) data. Our approach paves the way for a new multiscale assessment of the CNS allowing to validate and to improve our understanding of in vivo imaging (such as MRI).

Construction of a rat spinal cord atlas of axon morphometry

Atlases of the central nervous system are essential for understanding the pathophysiology of neurological diseases, which remains one of the greatest challenges in neuroscience research today. These atlases provide insight into the underlying white matter microstructure and have been created from a variety of animal models, including rats. Although existing atlases of the rat spinal cord provide some details of axon microstructure, there is currently no histological dataset that quantifies axon morphometry exhaustively in the entire spinal cord. In this study, we created the first comprehensive rat spinal cord atlas of the white matter microstructure with quantifiable axon and myelin morphometrics. Using full-slice scanning electron microscopy images and state-of-the-art segmentation algorithms, we generated an atlas of microstructural metrics such as axon diameter, axonal density and g-ratio. After registering the Watson spinal cord white matter atlas to our template, we computed statistics across metrics, spinal levels and tracts. We notably found that g-ratio is relatively constant, whereas axon diameter showed the greatest variation. The atlas, data and full analysis code are freely available at: https://github.com/neuropoly/atlas-rat.

Imaging G-Ratio in Multiple Sclerosis Using High-Gradient Diffusion MRI and Macromolecular Tissue Volume

BACKGROUND AND PURPOSE

Remyelination represents an area of great therapeutic interest in multiple sclerosis but currently lacks a robust imaging marker. The purpose of this study was to use high-gradient diffusion MRI and macromolecular tissue volume imaging to obtain estimates of axonal volume fraction, myelin volume fraction, and the imaging g-ratio in patients with MS and healthy controls and to explore their relationship to neurologic disability in MS.

MATERIALS AND METHODS

Thirty individuals with MS (23 relapsing-remitting MS, 7 progressive MS) and 19 age-matched healthy controls were scanned on a 3T MRI scanner equipped with 300 mT/m maximum gradient strength using a comprehensive multishell diffusion MRI protocol. Macromolecular tissue volume imaging was performed to quantify the myelin volume fraction. Diffusion data were fitted to a 3-compartment model of white matter using a spheric mean approach to yield estimates of axonal volume fraction. The imaging g-ratio was calculated from the ratio of myelin volume fraction and axonal volume fraction. Imaging metrics were compared between groups using 2-sided t tests with a Bonferroni correction.

RESULTS

The mean g-ratio was significantly elevated in lesions compared with normal-appearing WM (0.74 vs 0.67, P < .001). Axonal volume fraction (0.17 vs 0.23, P < .001) and myelin volume fraction (0.17 vs 0.25, P < .001) were significantly lower in lesions than normal-appearing WM. Myelin volume fraction was lower in normal-appearing WM compared with that in healthy controls (0.25 vs 0.27, P = .009). Disability, as measured by the Expanded Disability Status Scale, was significantly associated with myelin volume fraction (β = -40.5, P = .001) and axonal volume fraction (β = -41.0, P = .016) in normal-appearing WM.

CONCLUSIONS

The imaging g-ratio may serve as a biomarker for the relative degree of axonal and myelin loss in MS.

Myelin Water Fraction and Intra/Extracellular Water Geometric Mean T2 Normative Atlases for the Cervical Spinal Cord from 3T MRI

BACKGROUND AND PURPOSE

Acquiring and interpreting quantitative myelin-specific MRI data at an individual level is challenging because of technical difficulties and natural myelin variation in the population. To overcome these challenges, we used multiecho T₂ myelin water imaging (MWI) to create T₂ metric healthy population atlases that depict the mean and variation of myelin water fraction (MWF), and intra- and extracellular water mobility as described by geometric mean T₂ (IEGMT₂ ).

METHODS

Cervical cord MWI was performed at 3T on 20 healthy individuals (10M/10F, mean age: 36 years) and 3 relapsing remitting multiple sclerosis (RRMS) participants (1M/2F, age: 39/42/37 years). Anatomical data were collected for the purpose of image segmentation and registration. Atlases were created by coregistering and averaging T₂ metrics from all controls. Voxel-wise z-score maps from 3 RRMS participants were produced to demonstrate the preliminary utility of the MWF and IEGMT₂ atlases.

RESULTS

The average MWF atlas provides a representation of myelin in the spinal cord consistent with well-known spinal cord anatomical characteristics. The IEGMT₂ atlas also depicted structural variations in the spinal cord. Z-score analysis illustrated distinct abnormalities in MWF and IEGMT₂ in the 3 RRMS cases.

CONCLUSIONS

Our findings highlight the potential for using a quantitative T₂ relaxation metric atlas to visualize and detect pathology in spinal cord. Our MWF and IEGMT₂ atlases (URL: https://sourceforge.net/projects/mwi-spinal-cord-atlases/) can serve as normative references in the cervical spinal cord for other studies.

Brainstem and spinal cord MRI identifies altered sensorimotor pathways post-stroke

Damage to the corticospinal tract is widely studied following unilateral subcortical stroke, whereas less is known about changes to other sensorimotor pathways. This may be due to the fact that many studies investigated morphological changes in the brain, where the majority of descending and ascending brain pathways are overlapping, and did not investigate the brainstem where they separate. Moreover, these pathways continue passing through separate regions in the spinal cord. Here, using a high-resolution structural MRI of both the brainstem and the cervical spinal cord, we were able to identify a number of microstructurally altered pathways, in addition to the corticospinal tract, post stroke. Moreover, decreases in ipsi-lesional corticospinal tract integrity and increases in contra-lesional medial reticulospinal tract integrity were correlated with motor impairment severity in individuals with stroke.

There are few studies of structural changes in ascending and descending sensorimotor pathways after stroke, beyond the corticospinal tract, in the brain. Here the authors identify changes in white matter structure in brainstem and spinal cord following stroke, and show its relationship to motor impairment.

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).

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

Purpose

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.

Methods

We run Monte Carlo simulations using a synthetic model of spinal cord white matter (WM) (large axons), and of brain WM (smaller axons). Furthermore, we study clinically feasible multi‐shell DW scans of the cervical spinal cord (b = 0; b = 711 s mm⁻²; b = 2855 s mm⁻²), obtained using three diffusion times (Δ of 29, 52 and 76 ms) from three volunteers.

Results

Both intra‐/extra‐axonal perpendicular diffusivities and kurtosis excess show time‐dependence in our synthetic spinal cord model. This time‐dependence is reflected mostly in the intra‐axonal perpendicular DW signal, which also exhibits strong decay, unlike our brain model. Time‐dependence of the total DW signal appears detectable in the presence of noise in our synthetic spinal cord model, but not in the brain. In WM in vivo, we observe time‐dependent macroscopic and microscopic diffusivities and diffusion kurtosis, NODDI and two‐compartment SMT metrics. Accounting for large axon calibers improves fitting of multi‐compartment models to a minor extent.

Conclusions

Time‐dependence of clinically viable DW MRI metrics can be detected in vivo in spinal cord WM, thus providing new opportunities for the non‐invasive estimation of microstructural properties. The time‐dependence of the perpendicular DW signal may feature strong intra‐axonal contributions due to large spinal axon caliber. Hence, a popular model known as “stick” (zero‐radius cylinder) may be sub‐optimal to describe signals from the largest spinal axons.