High Resolution Ex Vivo Diffusion Tensor Distribution MRI of Neural Tissue

Neural tissue microstructure plays a key role in developmental, physiological and pathophysiological processes. In the continuing quest to characterize it at ever finer length scales, we use a novel diffusion tensor distribution (DTD) paradigm to probe microstructural features much smaller than the nominal MRI voxel size. We first assume the DTD is a normal tensor variate distribution constrained to lie on the manifold of positive definite matrices, characterized by a mean and covariance tensor. We then estimate the DTD using Monte Carlo signal inversion combined with parsimonious model selection framework that exploits a hierarchy of symmetries of mean and covariance tensors. High resolution multiple pulsed field gradient (mPFG) MRI measurements were performed on a homogeneous isotropic diffusion phantom (PDMS) for control, and excised visual cortex and spinal cord of macaque monkey to investigate the capabilities of DTD MRI in revealing neural tissue microstructural features using strong gradients not typically available in clinical MRI scanners. DTD-derived stains and glyphs, which disentangle size, shape, and orientation heterogeneities of microscopic diffusion tensors, are presented for all samples along with the distribution of the mean diffusivity (MD) within each voxel. We also present a new glyph to visualize the symmetric (kurtosis) and asymmetric parts of the fourth-order covariance tensor. An isotropic mean diffusion tensor and zero covariance tensor was found for the isotropic PDMS phantom, as expected, while the covariance tensor (both symmetric and asymmetric parts) for neural tissue was non-zero indicating that the kurtosis tensor may not be sufficient to fully describe the microstructure. Cortical layers were clearly delineated in the higher moments of the MD spectrum consistent with histology, and microscopic anisotropy was detected in both gray and white matter of neural tissue. DTD MRI captures crossing and splaying white matter fibers penetrating into the cortex, and skewed fiber diameter distributions in the white matter tracts within the cortex and spinal cord. DTD MRI was also shown to subsume diffusion tensor imaging (DTI) while providing additional microstructural information about tissue heterogeneity and microscopic anisotropy within each voxel.Peer reviewe

Modeling Basal Ganglia for understanding Parkinsonian Reaching Movements

We present a computational model that highlights the role of basal ganglia (BG) in generating simple reaching movements. The model is cast within the reinforcement learning (RL) framework with the correspondence between RL components and neuroanatomy as follows: dopamine signal of substantia nigra pars compacta as the Temporal Difference error, striatum as the substrate for the Critic, and the motor cortex as the Actor. A key feature of this neurobiological interpretation is our hypothesis that the indirect pathway is the Explorer. Chaotic activity, originating from the indirect pathway part of the model, drives the wandering, exploratory movements of the arm. Thus the direct pathway subserves exploitation while the indirect pathway subserves exploration. The motor cortex becomes more and more independent of the corrective influence of BG, as training progresses. Reaching trajectories show diminishing variability with training. Reaching movements associated with Parkinson's disease (PD) are simulated by (a) reducing dopamine and (b) degrading the complexity of indirect pathway dynamics by switching it from chaotic to periodic behavior. Under the simulated PD conditions, the arm exhibits PD motor symptoms like tremor, bradykinesia and undershoot. The model echoes the notion that PD is a dynamical disease.Comment: Neural Computation, In Pres

Peritumoral tissue compression is predictive of exudate flux in a rat model of cerebral tumor: an MRI study in an embedded tumor

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115972/1/nbm3418.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/115972/2/nbm3418_am.pd

A new framework for MR diffusion tensor distribution

The ability to characterize heterogeneous and anisotropic water diffusion processes within macroscopic MRI voxels non-invasively and in vivo is a desideratum in biology, neuroscience, and medicine. While an MRI voxel may contain approximately a microliter of tissue, our goal is to examine intravoxel diffusion processes on the order of picoliters. Here we propose a new theoretical framework and efficient experimental design to describe and measure such intravoxel structural heterogeneity and anisotropy. We assume that a constrained normal tensor-variate distribution (CNTVD) describes the variability of positive definite diffusion tensors within a voxel which extends its applicability to a wide range of b-values while preserving the richness of diffusion tensor distribution (DTD) paradigm unlike existing models. We introduce a new Monte Carlo (MC) scheme to synthesize realistic 6D DTD numerical phantoms and invert the MR signal. We show that the signal inversion is well-posed and estimate the CNTVD parameters parsimoniously by exploiting the different symmetries of the mean and covariance tensors of CNTVD. The robustness of the estimation pipeline is assessed by adding noise to calculated MR signals and compared with the ground truth. A family of invariant parameters and glyphs which characterize microscopic shape, size and orientation heterogeneity within a voxel are also presented.Peer reviewe

MRI-based computational model of heterogeneous tracer transport following local infusion into a mouse hind limb tumor.

Systemic drug delivery to solid tumors involving macromolecular therapeutic agents is challenging for many reasons. Amongst them is their chaotic microvasculature which often leads to inadequate and uneven uptake of the drug. Localized drug delivery can circumvent such obstacles and convection-enhanced delivery (CED)--controlled infusion of the drug directly into the tissue--has emerged as a promising delivery method for distributing macromolecules over larger tissue volumes. In this study, a three-dimensional MR image-based computational porous media transport model accounting for realistic anatomical geometry and tumor leakiness was developed for predicting the interstitial flow field and distribution of albumin tracer following CED into the hind-limb tumor (KHT sarcoma) in a mouse. Sensitivity of the model to changes in infusion flow rate, catheter placement and tissue hydraulic conductivity were investigated. The model predictions suggest that 1) tracer distribution is asymmetric due to heterogeneous porosity; 2) tracer distribution volume varies linearly with infusion volume within the whole leg, and exponentially within the tumor reaching a maximum steady-state value; 3) infusion at the center of the tumor with high flow rates leads to maximum tracer coverage in the tumor with minimal leakage outside; and 4) increasing the tissue hydraulic conductivity lowers the tumor interstitial fluid pressure and decreases the tracer distribution volume within the whole leg and tumor. The model thus predicts that the interstitial fluid flow and drug transport is sensitive to porosity and changes in extracellular space. This image-based model thus serves as a potential tool for exploring the effects of transport heterogeneity in tumors

Perivascular network segmentations derived from high-field MRI and their implications for perivascular and parenchymal mass transport in the rat brain

Abstract A custom segmentation workflow was applied to ex vivo high-field MR images of rat brains acquired following in vivo intraventricular contrast agent infusion to generate maps of the perivascular spaces (PVS). The resulting perivascular network segmentations enabled analysis of perivascular connections to the ventricles, parenchymal solute clearance, and dispersive solute transport within PVS. Numerous perivascular connections between the brain surface and the ventricles suggest the ventricles integrate into a PVS-mediated clearance system and raise the possibility of cerebrospinal fluid (CSF) return from the subarachnoid space to the ventricles via PVS. Assuming rapid solute exchange between the PVS and CSF spaces primarily by advection, the extensive perivascular network decreased the mean clearance distance from parenchyma to the nearest CSF compartment resulting in an over 21-fold reduction in the estimated diffusive clearance time scale, irrespective of solute diffusivity. This corresponds to an estimated diffusive clearance time scale under 10 min for amyloid-beta which suggests that the widespread distribution of PVS may render diffusion an effective parenchymal clearance mechanism. Additional analysis of oscillatory solute dispersion within PVS indicates that advection rather than dispersion is likely the primary transport mechanism for dissolved compounds greater than 66 kDa in the long (> 2 mm) perivascular segments identified here, although dispersion may be significant for smaller compounds in shorter perivascular segments

A schematic of the problem along with a sample of the analyzed experimental data.

<p>(a) Depiction of baseline CED tumor simulation of tracer spread in hind limb, (b) infusion sites at the mid-plane used in the sensitivity analysis, (c) spatial maps of (min⁻¹) and (d) porosity at the mid-plane calculated from DCE-MRI data. In (a) the skin boundary is shown in green, tumor boundary in blue, tumor midplane in red and infusion cannula in magenta. The infusion cannula is shown for illustration purpose only.</p

Variation of tracer distribution volumes in tissue with infusion volume for the whole leg and tumor following CED (0.3 µL/min) at the center of the tumor for varying values of the hydraulic conductivity parameter, .

<p>Distribution volume dependence on infusion volume was fit to (a) linear (whole leg) and (b) exponential (tumor only) models.</p

Flow field and tracer distribution following CED of albumin (0.3 µL/min) at the center of the tumor for varying values of the hydraulic conductivity parameter, .

<p>(a & b) Interstitial fluid pressure (IFP) contours for  = 5 & 10 respectively; (c & d) Convective fluid velocity contours for  = 5 & 10 respectively; (e & f) Normalized tracer concentration contours at the end of infusion (1 hr) for  = 5 & 10 respectively. All contours are for the plane of infusion with the infusion site designated by a plus sign.</p

Variation of tracer distribution volumes in tissue with infusion volume for the whole leg and tumor following CED at center of the tumor for three different flow rates (0.3, 1 and 3 µL/min).

<p>Distribution volume dependence on infusion volume was fit to (a) linear (whole leg) and (b) exponential (tumor only) models.</p