Diffusion Imaging of the Spinal Cord: Clinical Applications

Spinal cord pathologic condition often presents as a neurologic emergency where timely and accurate diagnosis is critical to expedite appropriate treatment and minimize severe morbidity and even mortality. MR imaging is the gold standard imaging technique for diagnosing patients with suspected spinal cord pathologic condition. This review will focus on the basic principles of diffusion imaging and how spinal anatomy presents technical challenges to its application. Both the promises and shortcomings of spinal diffusion imaging will then be explored in the context of several clinical spinal cord pathologies for which diffusion has been evaluated.

Detection of axonal degeneration in a mouse model of Huntington's disease: comparison between diffusion tensor imaging and anomalous diffusion metrics

OBJECTIVE

The goal of this work is to study the changes in white matter integrity in R6/2, a well-established animal model of Huntington's disease (HD) that are captured by ex vivo diffusion imaging (DTI) using a high field MRI (17.6 T).

MATERIALS AND METHODS

DTI and continuous time random walk (CTRW) models were used to fit changes in the diffusion-weighted signal intensity in the corpus callosum of controls and in R6/2 mice.

RESULTS

A significant 13% decrease in fractional anisotropy, a 7% increase in axial diffusion, and a 33% increase in radial diffusion were observed between R6/2 and control mice. No change was observed in the CTRW beta parameter, but a significant decrease in the alpha parameter (- 21%) was measured. Histological analysis of the corpus callosum showed a decrease in axonal organization, myelin alterations, and astrogliosis. Electron microscopy studies demonstrated ultrastructural changes in degenerating axons, such as an increase in tortuosity in the R6/2 mice.

CONCLUSIONS

DTI and CTRW diffusion models display quantitative changes associated with the microstructural alterations observed in the corpus callosum of the R6/2 mice. The observed increase in the diffusivity and decrease in the alpha CTRW parameter providing support for the use of these diffusion models for non-invasive detection of white matter alterations in HD.

Scattering and Diffraction of Elastodynamic Waves in a Concentric Cylindrical Phantom for MR Elastography

AIM

The focus of this paper is to report on the design and construction of a multiply connected phantom for use in magnetic resonance elastography (MRE)-an imaging technique that allows for the noninvasive visualization of the displacement field throughout an object from externally driven harmonic motion-as well as its inverse modeling with a closed-form analytic solution which is derived herein from first principles.

METHODS

Mathematically, the phantom is described as two infinite concentric circular cylinders with unequal complex shear moduli, harmonically vibrated at the exterior surface in a direction along their common axis. Each concentric cylinder is made of a hydrocolloid with its own specific solute concentration. They are assembled in a multistep process for which custom scaffolding was designed and built. A customized spin-echo-based MR elastography sequence with a sinusoidal motion-sensitizing gradient was used for data acquisition on a 9.4 T Agilent small-animal MR scanner. Complex moduli obtained from the inverse model are used to solve the forward problem with a finite-element method.

RESULTS

Both complex shear moduli show a significant frequency dependence (p 0.001) in keeping with previous work.

CONCLUSION

The novel multiply connected phantom and mathematical model are validated as a viable tool for MRE studies.

SIGNIFICANCE

On a small enough scale much of physiology can be mathematically modeled with basic geometric shapes, e.g., a cylinder representing a blood vessel. This study demonstrates the possibility of elegant mathematical analysis of phantoms specifically designed and carefully constructed for biomedical MRE studies.

Anisotropic fractional diffusion tensor imaging

Traditional diffusion tensor imaging (DTI) maps brain structure by fitting a diffusion model to the magnitude of the electrical signal acquired in magnetic resonance imaging (MRI). Fractional DTI employs anomalous diffusion models to obtain a better fit to real MRI data, which can exhibit anomalous diffusion in both time and space. In this paper, we describe the challenge of developing and employing anisotropic fractional diffusion models for DTI. Since anisotropy is clearly present in the three-dimensional MRI signal response, such models hold great promise for improving brain imaging. We then propose some candidate models, based on stochastic theory.

Analysis of YFP(J16)-R6/2 reporter mice and postmortem brains reveals early pathology and increased vulnerability of callosal axons in Huntington's disease

Cumulative evidence indicates that the onset and severity of Huntington's disease (HD) symptoms correlate with connectivity deficits involving specific neuronal populations within cortical and basal ganglia circuits. Brain imaging studies and pathological reports further associated these deficits with alterations in cerebral white matter structure and axonal pathology. However, whether axonopathy represents an early pathogenic event or an epiphenomenon in HD remains unknown, nor is clear the identity of specific neuronal populations affected. To directly evaluate early axonal abnormalities in the context of HD in vivo, we bred transgenic YFP(J16) with R6/2 mice, a widely used HD model. Diffusion tensor imaging and fluorescence microscopy studies revealed a marked degeneration of callosal axons long before the onset of motor symptoms. Accordingly, a significant fraction of YFP-positive cortical neurons in YFP(J16) mice cortex were identified as callosal projection neurons. Callosal axon pathology progressively worsened with age and was influenced by polyglutamine tract length in mutant huntingtin (mhtt). Degenerating axons were dissociated from microscopically visible mhtt aggregates and did not result from loss of cortical neurons. Interestingly, other axonal populations were mildly or not affected, suggesting differential vulnerability to mhtt toxicity. Validating these results, increased vulnerability of callosal axons was documented in the brains of HD patients. Observations here provide a structural basis for the alterations in cerebral white matter structure widely reported in HD patients. Collectively, our data demonstrate a dying-back pattern of degeneration for cortical projection neurons affected in HD, suggesting that axons represent an early and potentially critical target for mhtt toxicity.

Measuring embeddedness: Hierarchical scale-dependent information exchange efficiency of the human brain connectome

This article presents a novel approach for understanding information exchange efficiency and its decay across hierarchies of modularity, from local to global, of the structural human brain connectome. Magnetic resonance imaging techniques have allowed us to study the human brain connectivity as a graph, which can then be analyzed using a graph-theoretical approach. Collectively termed brain connectomics, these sophisticated mathematical techniques have revealed that the brain connectome, like many networks, is highly modular and brain regions can thus be organized into communities or modules. Here, using tractography-informed structural connectomes from 46 normal healthy human subjects, we constructed the hierarchical modularity of the structural connectome using bifurcating dendrograms. Moving from fine to coarse (i.e., local to global) up the connectome's hierarchy, we computed the rate of decay of a new metric that hierarchically preferentially weighs the information exchange between two nodes in the same module. By computing "embeddedness"-the ratio between nodal efficiency and this decay rate, one could thus probe the relative scale-invariant information exchange efficiency of the human brain. Results suggest that regions that exhibit high embeddedness are those that comprise the limbic system, the default mode network, and the subcortical nuclei. This supports the presence of near-decomposability overall yet relative embeddedness in select areas of the brain. The areas we identified as highly embedded are varied in function but are arguably linked in the evolutionary role they play in memory, emotion and behavior.

Diffusion tensor MRI phantom exhibits anomalous diffusion

This paper reports diffusion weighted MRI measurements of cyclohexane in a novel diffusion tensor MRI phantom composed of hollow coaxial electrospun fibers (average diameter 10.2 μm). Recent studies of the phantom demonstrated its potential as a calibration standard at low b values (less than 1000 s/mm<;sup>2<;/sup>) for mean diffusivity and fractional anisotropy. In this paper, we extend the characterization of cyclohexane diffusion in this heterogeneous, anisotropic material to high b values (up to 5000 s/mm<;sup>2<;/sup>), where the apparent diffusive motion of the cyclohexane exhibits anomalous behavior (i.e., the molecular mean squared displacement increases with time raised to the fractional power 2α/β). Diffusion tensor MRI was performed at 9.4 T using an Agilent imaging scanner and the data fit to a fractional order Mittag-Leffler (generalized exponential) decay model. Diffusion along the fibers was found to be Gaussian (2α/β=l), while diffusion across the fibers was sub-diffusive (2α/β<;l). Fiber tract reconstruction of the data was consistent with scanning electron micrograph images of the material. These studies suggest that this phantom material may be used to calibrate MR systems in both the normal (Gaussian) and anomalous diffusion regimes.