RESUMO
Brain white matter is a dynamic environment that continuously adapts and reorganizes in response to stimuli and pathological changes. Glial cells, especially, play a key role in tissue repair, inflammation modulation, and neural recovery. The movements of glial cells and changes in their concentrations can influence the surrounding axon morphology. We introduce the White Matter Generator (WMG) tool to enable the study of how axon morphology is influenced through such dynamical processes, and how this, in turn, influences the diffusion-weighted MRI signal. This is made possible by allowing interactive changes to the configuration of the phantom generation throughout the optimization process. The phantoms can consist of myelinated axons, unmyelinated axons, and cell clusters, separated by extra-cellular space. Due to morphological flexibility and computational advantages during the optimization, the tool uses ellipsoids as building blocks for all structures; chains of ellipsoids for axons, and individual ellipsoids for cell clusters. After optimization, the ellipsoid representation can be converted to a mesh representation which can be employed in Monte-Carlo diffusion simulations. This offers an effective method for evaluating tissue microstructure models for diffusion-weighted MRI in controlled bio-mimicking white matter environments. Hence, the WMG offers valuable insights into white matter's adaptive nature and implications for diffusion-weighted MRI microstructure models, and thereby holds the potential to advance clinical diagnosis, treatment, and rehabilitation strategies for various neurological disorders and injuries.
RESUMO
We enable the estimation of the per-axon axial diffusivity from single encoding, strongly diffusion-weighted, pulsed gradient spin echo data. Additionally, we improve the estimation of the per-axon radial diffusivity compared to estimates based on spherical averaging. The use of strong diffusion weightings in magnetic resonance imaging (MRI) allows to approximate the signal in white matter as the sum of the contributions from only axons. At the same time, spherical averaging leads to a major simplification of the modeling by removing the need to explicitly account for the unknown distribution of axonal orientations. However, the spherically averaged signal acquired at strong diffusion weightings is not sensitive to the axial diffusivity, which cannot therefore be estimated although needed for modeling axons - especially in the context of multi-compartmental modeling. We introduce a new general method for the estimation of both the axial and radial axonal diffusivities at strong diffusion weightings based on kernel zonal modeling. The method could lead to estimates that are free from partial volume bias with gray matter or other isotropic compartments. The method is tested on publicly available data from the MGH Adult Diffusion Human Connectome project. We report reference values of axonal diffusivities based on 34 subjects, and derive estimates of axonal radii from only two shells. The estimation problem is also addressed from the angle of the required data preprocessing, the presence of biases related to modeling assumptions, current limitations, and future possibilities.
Assuntos
Conectoma , Substância Branca , Adulto , Humanos , Imagem de Difusão por Ressonância Magnética/métodos , Substância Branca/diagnóstico por imagem , Axônios/patologia , Encéfalo/diagnóstico por imagemRESUMO
In magnetic resonance imaging, the application of a strong diffusion weighting suppresses the signal contributions from the less diffusion-restricted constituents of the brain's white matter, thus enabling the estimation of the transverse relaxation time T2 that arises from the more diffusion-restricted constituents such as the axons. However, the presence of cell nuclei and vacuoles can confound the estimation of the axonal T2, as diffusion within those structures is also restricted, causing the corresponding signal to survive the strong diffusion weighting. We devise an estimator of the axonal T2 based on the directional spherical variance of the strongly diffusion-weighted signal. The spherical variance T2 estimates are insensitive to the presence of isotropic contributions to the signal like those provided by cell nuclei and vacuoles. We show that with a strong diffusion weighting these estimates differ from those obtained using the directional spherical mean of the signal which contains both axonal and isotropically-restricted contributions. Our findings hint at the presence of an MRI-visible isotropically-restricted contribution to the signal in the white matter ex vivo fixed tissue (monkey) at 7T, and do not allow us to discard such a possibility also for in vivo human data collected with a clinical 3T system.
Assuntos
Imagem de Difusão por Ressonância Magnética , Substância Branca , Axônios , Encéfalo/diagnóstico por imagem , Imagem de Difusão por Ressonância Magnética/métodos , Imageamento por Ressonância Magnética , Substância Branca/diagnóstico por imagemRESUMO
Noninvasive estimation of axon diameter with diffusion MRI holds the potential to investigate the dynamic properties of the brain network and pathology of neurodegenerative diseases. Recent studies use powder averaging to account for complex white matter architectures, but these have not been validated for real axonal geometries from regions that contain fibre crossings. Here, we present 120-304µm long segmented axons from X-ray nano-holotomography volumes of a splenium and crossing fibre region of a vervet monkey brain. We show that the axons in the complex crossing fibre region, which contains callosal, association, and corticospinal connections, exhibit a wider diameter distribution than those of the splenium region. To accurately estimate the axon diameter in these regions, therefore, sensitivity to a wide range of diameters is required. We demonstrate how the q-value, b-value, signal-to-noise ratio and the assumed intra-axonal parallel diffusivity influence the range of measurable diameters with powder average approaches. Furthermore, we show how Gaussian distributed noise results in a wider range of measurable diameter at high b-values than Rician distributed noise, even at high signal-to-noise ratios of 100. The number of gradient directions is also shown to impose a lower bound on measurable diameter. Our results indicate that axon diameter estimation can be performed with only few b-shells, and that additional shells do not improve the accuracy of the estimate. For strong gradients available on human Connectom and preclinical scanners, Monte Carlo simulations of diffusion confirm that powder averaging techniques succeed in providing accurate estimates of axon diameter across a range of diameters, sequence parameters and diffusion times, even in complex white matter architectures. At relatively low b-values, the diameter estimate becomes sensitive to axonal microdispersion and the intra-axonal parallel diffusivity shows time dependency at both in vivo and ex vivo intrinsic diffusivities.
Assuntos
Axônios/ultraestrutura , Imagem de Difusão por Ressonância Magnética/métodos , Imageamento Tridimensional , Animais , Chlorocebus aethiops , Método de Monte Carlo , Distribuição Normal , Razão Sinal-RuídoRESUMO
Axonal conduction velocity, which ensures efficient function of the brain network, is related to axon diameter. Noninvasive, in vivo axon diameter estimates can be made with diffusion magnetic resonance imaging, but the technique requires three-dimensional (3D) validation. Here, high-resolution, 3D synchrotron X-ray nano-holotomography images of white matter samples from the corpus callosum of a monkey brain reveal that blood vessels, cells, and vacuoles affect axonal diameter and trajectory. Within single axons, we find that the variation in diameter and conduction velocity correlates with the mean diameter, contesting the value of precise diameter determination in larger axons. These complex 3D axon morphologies drive previously reported 2D trends in axon diameter and g-ratio. Furthermore, we find that these morphologies bias the estimates of axon diameter with diffusion magnetic resonance imaging and, ultimately, impact the investigation and formulation of the axon structure-function relationship.
Assuntos
Axônios/fisiologia , Animais , Feminino , Haplorrinos , Imageamento Tridimensional , Imageamento por Ressonância Magnética , Bainha de Mielina/metabolismo , Relação Estrutura-Atividade , Vacúolos/metabolismo , Substância Branca/anatomia & histologiaRESUMO
OBJECTIVES: Light microscopical analysis in two dimensions, combined with immunohistochemistry, is presently the gold standard to describe the enteric nervous system (ENS). Our aim was to assess the usefulness of three-dimensional (3D) imaging by X-ray phase-contrast tomography in evaluating the ENS of the human bowel. MATERIAL AND METHODS: Myenteric ganglia were identified in full-thickness biopsies of the ileum and colon by hematoxylin & eosin staining. A1-mm biopsy punch was taken from the paraffin blocks and placed into a Kapton® tube for subsequent tomographic investigation. The samples were scanned, without further preparation, using phase-contrast tomography at two different scales: overview scans (performed with laboratory setups), which allowed localization of the nervous tissue (â¼1µm effective voxel size); and high-resolution scans (performed with a synchrotron endstation), which imaged localized regions of 320x320x320 µm3 (176 nm effective voxel size). RESULTS: The contrast allowed us to follow the shape and the size changes of the ganglia, as well as to study their cellular components together with the cells and cellular projections of the periganglional space. Furthermore, it was possible to show the 3D network of the myenteric plexus and to quantify its volume within the samples. CONCLUSIONS: Phase-contrast X-ray tomography can be applied for volume analyses of the human ENS and to study tissue components in unstained paraffin-embedded tissue biopsies. This technique could potentially be used to study disease mechanisms, and to compare healthy and diseased tissues in clinical research.