Mapping complex myoarchitecture in the bovine tongue with diffusion-spectrum magnetic resonance imaging

The ability to resolve complex fiber populations in muscular tissues is important for relating tissue structure with mechanical function. To address this issue in the case of tongue, we employed diffusion spectrum imaging (DSI), an MRI method for determining three-dimensional myoarchitecture where myofiber populations are variably aligned. By specifically varying gradient field strength, molecular displacement in a tissue can be determined by Fourier-transforming the echo intensity against gradient strength at fixed gradient pulse spacing. The displacement profiles are visualized by graphing three-dimensional isocontour icons for each voxel, with the isocontour shape and size representing the magnitude and direction of the constituting fiber populations. To validate this method, we simulated a DSI experiment within the constraints of arbitrary crossing fibers, and determined that DSI accurately depicts the angular relationships between these fibers. Considering the fiber relationships in the whole bovine tongue, we compared the images obtained by DSI with those obtained by diffusion tensor imaging in an anterior slice of the lingual core, a region known to possess extensive fiber crossing. In contrast to diffusion tensor imaging, which depicts the anterior core solely as a region with low anisotropy due to the presence of mixed-orientation fiber populations, DSI shows two distinct fiber populations, with an explicit orthogonal relationship to each other. In imaging the whole lingual tissue, we discerned arrays of crossing and noncrossing fibers involving the intrinsic and extrinsic muscles, which merged at regions of interface. We conclude that DSI has the capacity to determine three-dimensional fiber orientation in structurally complex muscular tissues.     

Multi-Fiber Tractography Visualizations for Diffusion MRI Data

In recent years, several new diffusion MRI approaches have been proposed to explore microstructural properties of the white matter, such as Q-ball imaging and spherical deconvolution-based techniques to estimate the orientation distribution function. These methods can describe the estimated diffusion profile with a higher accuracy than the more conventional second-rank diffusion tensor imaging technique. Despite many important advances, there are still inconsistent findings between different models that investigate the “crossing fibers” issue. Due to the high information content and the complex nature of the data, it becomes virtually impossible to interpret and compare results in a consistent manner. In this work, we present novel fiber tractography visualization approaches that provide a more complete picture of the microstructural architecture of fiber pathways: multi-fiber hyperstreamlines and streamribbons. By visualizing, for instance, the estimated fiber orientation distribution along the reconstructed tract in a continuous way, information of the local fiber architecture is combined with the global anatomical information derived from tractography. Facilitating the interpretation of diffusion MRI data, this approach can be useful for comparing different diffusion reconstruction techniques and may improve our understanding of the intricate white matter network.     

In?Vivo Orientation of Single Myosin Lever Arms in Zebrafish Skeletal Muscle

Cardiac and skeletal myosin assembled in the muscle lattice power contraction by transducing ATP free energy into the mechanical work of moving actin. Myosin catalytic/lever-arm domains comprise the transduction/mechanical coupling machinery that move actin by lever-arm rotation. In vivo, myosin is crowded and constrained by the fiber lattice as side chains are mutated and otherwise modified under normal, diseased, or aging conditions that collectively define the native myosin environment. Single-myosin detection uniquely defines bottom-up characterization of myosin functionality. The marriage of in vivo and single-myosin detection to study zebrafish embryo models of human muscle disease is a multiscaled technology that allows one-to-one registration of a selected myosin molecular alteration with muscle filament-sarcomere-cell-fiber-tissue-organ- and organism level phenotypes. In vivo single-myosin lever-arm orientation was observed at superresolution using a photoactivatable-green-fluorescent-protein (PAGFP)-tagged myosin light chain expressed in zebrafish skeletal muscle. By simultaneous observation of multiphoton excitation fluorescence emission and second harmonic generation from myosin, we demonstrated tag specificity for the lever arm. Single-molecule detection used highly inclined parallel beam illumination and was verified by quantized photoactivation and photobleaching. Single-molecule emission patterns from relaxed muscle in vivo provided extensive superresolved dipole orientation constraints that were modeled using docking scenarios generated for the myosin (S1) and GFP crystal structures. The dipole orientation data provided sufficient constraints to estimate S1/GFP coordination. The S1/GFP coordination in vivo is rigid and the lever-arm orientation distribution is well-ordered in relaxed muscle. For comparison, single myosins in relaxed permeabilized porcine papillary muscle fibers indicated slightly differently oriented lever arms and rigid S1/GFP coordination. Lever arms in both muscles indicated one preferred spherical polar orientation and widely distributed azimuthal orientations relative to the fiber symmetry axis. Cardiac myosin is more radially displaced from the fiber axis. Probe rigidity implies the PAGFP tag reliably indicates cross-bridge orientation in situ and in vivo.     

Sparse Solution of Fiber Orientation Distribution Function by Diffusion Decomposition

Fiber orientation is the key information in diffusion tractography. Several deconvolution methods have been proposed to obtain fiber orientations by estimating a fiber orientation distribution function (ODF). However, the L ₂ regularization used in deconvolution often leads to false fibers that compromise the specificity of the results. To address this problem, we propose a method called diffusion decomposition, which obtains a sparse solution of fiber ODF by decomposing the diffusion ODF obtained from q-ball imaging (QBI), diffusion spectrum imaging (DSI), or generalized q-sampling imaging (GQI). A simulation study, a phantom study, and an in-vivo study were conducted to examine the performance of diffusion decomposition. The simulation study showed that diffusion decomposition was more accurate than both constrained spherical deconvolution and ball-and-sticks model. The phantom study showed that the angular error of diffusion decomposition was significantly lower than those of constrained spherical deconvolution at 30° crossing and ball-and-sticks model at 60° crossing. The in-vivo study showed that diffusion decomposition can be applied to QBI, DSI, or GQI, and the resolved fiber orientations were consistent regardless of the diffusion sampling schemes and diffusion reconstruction methods. The performance of diffusion decomposition was further demonstrated by resolving crossing fibers on a 30-direction QBI dataset and a 40-direction DSI dataset. In conclusion, diffusion decomposition can improve angular resolution and resolve crossing fibers in datasets with low SNR and substantially reduced number of diffusion encoding directions. These advantages may be valuable for human connectome studies and clinical research.     

Resolving the three-dimensional myoarchitecture of bovine esophageal wall with diffusion spectrum imaging and tractography

In order to determine the three-dimensional (3D) resolved muscular anatomy of the mammalian esophagus, we have examined its myoarchitecture with diffusion spectrum magnetic resonance imaging (DSI) and tractography. DSI measures diffusion displacement as a function of magnetic gradients of varied direction and intensity and displays the displacement profile as a 3D contour per voxel. In tractography, the orientation vectors of maximum diffusion/voxel are identified, and intervoxel associations are constructed by a streamline algorithm based on angular similarity in order to generate mesoscale myofiber tracts. We demonstrate that the proximal body of the esophagus consists of helically aligned crossing fiber populations that overlap between layers in the form of a “zipper” region along the length of the tissue. With increasingly distal position along the length of the tissue, helix angle and skeletal muscle prevalence are reduced such that fibers align themselves in the most distal location into distinct inner circular and outer longitudinal smooth muscle layers. We conclude that esophageal myoanatomy consists of crossing myofibers exhibiting a decreasing degree of helicity as a function of axial position and propose that this unique geometric construct provides a mechanism to resist distension and promote aboral flow. This work was supported by the National Institutes of Health (grants RO1-DC05604 to Richard J. Gilbert and RO1- MH64044 to Van J. Wedeen.     

Seeing More by Showing Less: Orientation-Dependent Transparency Rendering for Fiber Tractography Visualization

Fiber tractography plays an important role in exploring the architectural organization of fiber trajectories, both in fundamental neuroscience and in clinical applications. With the advent of diffusion MRI (dMRI) approaches that can also model “crossing fibers”, the complexity of the fiber network as reconstructed with tractography has increased tremendously. Many pathways interdigitate and overlap, which hampers an unequivocal 3D visualization of the network and impedes an efficient study of its organization. We propose a novel fiber tractography visualization approach that interactively and selectively adapts the transparency rendering of fiber trajectories as a function of their orientation to enhance the visibility of the spatial context. More specifically, pathways that are oriented (locally or globally) along a user-specified opacity axis can be made more transparent or opaque. This substantially improves the 3D visualization of the fiber network and the exploration of tissue configurations that would otherwise be largely covered by other pathways. We present examples of fiber bundle extraction and neurosurgical planning cases where the added benefit of our new visualization scheme is demonstrated over conventional fiber visualization approaches.     

Demonstration of primary and secondary muscle fiber architecture of the bovine tongue by diffusion tensor magnetic resonance imaging

The myoarchitecture of the tongue is comprised of a complex array of muscle fiber bundles, which form the structural basis for lingual deformations during speech and swallowing. We used magnetic resonance imaging of the water diffusion tensor to display the primary and secondary fiber architectural attributes of the excised bovine tongue. Fiber orientation mapping provides a subdivision of the tongue into its principal intrinsic and extrinsic muscular components. The anterior tongue consists of a central region of orthogonally oriented intrinsic fibers surrounded by an axially oriented muscular sheath. The posterior tongue consists principally of a central region of extrinsic fibers, originating at the inferior surface and projecting in a fan-like manner in the superior, lateral, and posterior directions, and lateral populations of extrinsic fibers directed posterior-inferior and posterior-superior. Analysis of cross-fiber anisotropy indicates a basic contrast of design between the extrinsic and the intrinsic fibers. Whereas the extrinsic muscles exhibit a uniaxial architecture typical of skeletal muscle, the intrinsic core muscles, comprised of the verticalis and the transversus muscles, show strong cross-fiber anisotropy. This pattern is consistent with the theory that the tongue's core functions as a muscular hydrostat in that conjoint contraction of the transverse and vertical fibers enable the tissue to expand at right angles to these fibers. These findings suggest that three-dimensional analysis of diffusion tensor magnetic resonance imaging provides a structural basis for understanding the micromechanics of the mammalian tongue.     

Laplace-based modeling of fiber orientation in the tongue

Mechanical modeling of tongue deformation plays a significant role in the study of breathing, swallowing, and speech production. In the absence of internal joints, fiber orientations determine the direction of sarcomeric contraction and have great influence over real and simulated tissue motion. However, subject-specific experimental observations of fiber distribution are difficult to obtain; thus, models of fiber distribution are generally used in mechanical simulations. This paper describes modeling of fiber distribution using solutions of Laplace equations and compares the effectiveness of this approach against tractography from diffusion tensor magnetic resonance imaging. The experiments included qualitative comparison of streamlines from the fiber model against experimental tractography, as well as quantitative differences between biomechanical simulations focusing in the region near the genioglossus. The model showed good overall agreement in terms of fiber directionality and muscle positioning when compared to subject-specific imaging results and the literature. The angle between the fiber distribution model against tractography in the genioglossus and geniohyoid muscles averaged \(22^{\circ }\) likely due to experimental noise. However, kinematic responses were similar between simulations with modeled fibers versus experimentally obtained fibers; average discrepancy in surface displacement ranged from 1 to 7 mm, and average strain residual magnitude ranged from \(4\times 10^{-3}\) to 0.2. The results suggest that, for simulation purposes, the modeled fibers can act as a reasonable approximation for the tongue’s fiber distribution. Also, given its agreement with the global tongue anatomy, the approach may be used in model-based reconstruction of displacement tracking and diffusion results.     

Diffusion MRI of complex neural architecture

While functional brain imaging methods can locate the cortical regions subserving particular cognitive functions, the connectivity between the functional areas of the human brain remains poorly understood. Recently, investigators have proposed a method to image neural connectivity noninvasively using a magnetic resonance imaging method called diffusion tensor imaging (DTI). DTI measures the molecular diffusion of water along neural pathways. Accurate reconstruction of neural connectivity patterns from DTI has been hindered, however, by the inability of DTI to resolve more than a single axon direction within each imaging voxel. Here, we present a novel magnetic resonance imaging technique that can resolve multiple axon directions within a single voxel. The technique, called q-ball imaging, can resolve intravoxel white matter fiber crossing as well as white matter insertions into cortex. The ability of q-ball imaging to resolve complex intravoxel fiber architecture eliminates a key obstacle to mapping neural connectivity in the human brain noninvasively.     

Kinetics of Diffusion and Convection in 3.2-Å Pores: Exact Solution by Computer Simulation

The kinetics of transport in pores the size postulated for cell membranes has been investigated by direct computer simulation (molecular dynamics). The simulated pore is 11 Å long and 3.2 Å in radius, and the water molecules are modeled by hard, smooth spheres, 1 Å in radius. The balls are given an initial set of positions and velocities (with an average temperature of 313° K) and the computer then calculates their exact paths through the pore. Two different conditions were used at the ends of the pore. In one, the ends are closed and the balls are completely isolated. In the other, the ball density in each end region is fixed so that a pressure difference can be established and a net convective flow produced. The following values were directly measured in the simulated experiments: net and diffusive (oneway) flux; pressure, temperature, and diffusion coefficients in the pore; area available for diffusion; probability distribution of ball positions in the pore; and the interaction between diffusion and convection. The density, viscosity, and diffusion coefficients in the bulk fluid were determined from the theory of hard sphere dense gases. From these values, the “equivalent” pore radius (determined by the same procedure that is used for cell membranes) was computed and compared with the physical pore radius of the simulated pore.     

The pattern of apolipoprotein A-I lysine carbamylation reflects its lipidation state and the chemical environment within human atherosclerotic aorta

Protein lysine carbamylation is an irreversible post-translational modification resulting in generation of homocitrulline (N-ε-carbamyllysine), which no longer possesses a charged ε-amino moiety. Two distinct pathways can promote protein carbamylation. One results from urea decomposition, forming an equilibrium mixture of cyanate (CNO⁻) and the reactive electrophile isocyanate. The second pathway involves myeloperoxidase (MPO)-catalyzed oxidation of thiocyanate (SCN⁻), yielding CNO⁻ and isocyanate. Apolipoprotein A-I (apoA-I), the major protein constituent of high-density lipoprotein (HDL), is a known target for MPO-catalyzed modification in vivo, converting the cardioprotective lipoprotein into a proatherogenic and proapoptotic one. We hypothesized that monitoring site-specific carbamylation patterns of apoA-I recovered from human atherosclerotic aorta could provide insights into the chemical environment within the artery wall. To test this, we first mapped carbamyllysine obtained from in vitro carbamylation of apoA-I by both the urea-driven (nonenzymatic) and inflammatory-driven (enzymatic) pathways in lipid-poor and lipidated apoA-I (reconstituted HDL). Our results suggest that lysine residues within proximity of the known MPO-binding sites on HDL are preferentially targeted by the enzymatic (MPO) carbamylation pathway, whereas the nonenzymatic pathway leads to nearly uniform distribution of carbamylated lysine residues along the apoA-I polypeptide chain. Quantitative proteomic analyses of apoA-I from human aortic atheroma identified 16 of the 21 lysine residues as carbamylated and suggested that the majority of apoA-I carbamylation in vivo occurs on “lipid-poor” apoA-I forms via the nonenzymatic CNO⁻ pathway. Monitoring patterns of apoA-I carbamylation recovered from arterial tissues can provide insights into both apoA-I structure and the chemical environment within human atheroma.     

Characterization of the normal cardiac myofiber field in goat measured with MR-diffusion tensor imaging

Cardiac myofiber orientation is a crucial determinant of the distribution of myocardial wall stress. Myofiber orientation is commonly quantified by helix and transverse angles. Accuracy of reported helix angles is limited. Reported transverse angle data are incomplete. We measured cardiac myofiber orientation postmortem in five healthy goat hearts using magnetic resonance-diffusion tensor imaging. A novel local wall-bound coordinate system was derived from the characteristics of the fiber field. The transmural course of the helix angle corresponded to data reported in literature. The mean midwall transverse angle ranged from -12 +/- 4 degrees near the apex to +9.0 +/- 4 degrees near the base of the left ventricle, which is in agreement with the course predicted by Rijcken et al. (18) using a uniform load hypothesis. The divergence of the myofiber field was computed, which is a measure for the extent to which wall stress is transmitted through the myofiber alone. It appeared to be <0.07 mm(-1) throughout the myocardial walls except for the fusion sites between the left and right ventricles and the insertion sites of the papillary muscles.     

MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck

Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1–2 mm and with 10–50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named “MIDA”. The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community.     

Analysis of emergent patterns in crossing flows of pedestrians reveals an invariant of ‘stripe’ formation in human data

When two streams of pedestrians cross at an angle, striped patterns spontaneously emerge as a result of local pedestrian interactions. This clear case of self-organized pattern formation remains to be elucidated. In counterflows, with a crossing angle of 180°, alternating lanes of traffic are commonly observed moving in opposite directions, whereas in crossing flows at an angle of 90°, diagonal stripes have been reported. Naka (1977) hypothesized that stripe orientation is perpendicular to the bisector of the crossing angle. However, studies of crossing flows at acute and obtuse angles remain underdeveloped. We tested the bisector hypothesis in experiments on small groups (18-19 participants each) crossing at seven angles (30° intervals), and analyzed the geometric properties of stripes. We present two novel computational methods for analyzing striped patterns in pedestrian data: (i) an edge-cutting algorithm, which detects the dynamic formation of stripes and allows us to measure local properties of individual stripes; and (ii) a pattern-matching technique, based on the Gabor function, which allows us to estimate global properties (orientation and wavelength) of the striped pattern at a time T. We find an invariant property: stripes in the two groups are parallel and perpendicular to the bisector at all crossing angles. In contrast, other properties depend on the crossing angle: stripe spacing (wavelength), stripe size (number of pedestrians per stripe), and crossing time all decrease as the crossing angle increases from 30° to 180°, whereas the number of stripes increases with crossing angle. We also observe that the width of individual stripes is dynamically squeezed as the two groups cross each other. The findings thus support the bisector hypothesis at a wide range of crossing angles, although the theoretical reasons for this invariant remain unclear. The present results provide empirical constraints on theoretical studies and computational models of crossing flows.     

Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with Constrained Spherical Deconvolution

We propose two strategies to improve the quality of tractography results computed from diffusion weighted magnetic resonance imaging (DW-MRI) data. Both methods are based on the same PDE framework, defined in the coupled space of positions and orientations, associated with a stochastic process describing the enhancement of elongated structures while preserving crossing structures. In the first method we use the enhancement PDE for contextual regularization of a fiber orientation distribution (FOD) that is obtained on individual voxels from high angular resolution diffusion imaging (HARDI) data via constrained spherical deconvolution (CSD). Thereby we improve the FOD as input for subsequent tractography. Secondly, we introduce the fiber to bundle coherence (FBC), a measure for quantification of fiber alignment. The FBC is computed from a tractography result using the same PDE framework and provides a criterion for removing the spurious fibers. We validate the proposed combination of CSD and enhancement on phantom data and on human data, acquired with different scanning protocols. On the phantom data we find that PDE enhancements improve both local metrics and global metrics of tractography results, compared to CSD without enhancements. On the human data we show that the enhancements allow for a better reconstruction of crossing fiber bundles and they reduce the variability of the tractography output with respect to the acquisition parameters. Finally, we show that both the enhancement of the FODs and the use of the FBC measure on the tractography improve the stability with respect to different stochastic realizations of probabilistic tractography. This is shown in a clinical application: the reconstruction of the optic radiation for epilepsy surgery planning.     

Associating the mesoscale fiber organization of the tongue with local strain rate during swallowing

The tongue is an intricately configured muscular organ that undergoes a stereotypical set of deformations during the course of normal human swallowing. In order to demonstrate quantitatively the relationship between 3D aligned lingual fiber organization and mechanics during swallowing, the tissue's myoarchitecture and strain rate were imaged before and during the propulsive phase of a 3.0ml water bolus swallow. Mesoscale fiber organization was imaged with high-resolution diffusion tensor imaging (DTI) and multi-voxel myofiber tracts generated along maximum diffusion vectors. Tissue compression/expansion was obtained via lingual pressure-gated phase-contrast (PC) MRI, a method which determines local strain rate as a function of the phase shift occurring along an applied gradient vector. The co-alignment of myofiber tract direction and the localized principal strain rate vectors was obtained by translating the strain rate tensor into the reference frame with the primary axis parallel to the maximum diffusion vector using Mohr's circle, resulting in the generation of fiber-aligned strain rate (FASR). DTI tractography displayed the complete fiber anatomy of the tongue, consisting of a core region of orthogonally aligned fibers encased within a longitudinal sheath, which merge with the externally connected styloglossus, hyoglossus, and genioglossus fibers. FASR images obtained in the mid-sagittal plane demonstrated that bolus propulsion was associated with prominent compressive strain aligned with the genioglossus muscle combined with expansive strain aligned with the verticalis and geniohyoid muscles. These data demonstrate that lingual deformation during swallowing involves complex interactions involving intrinsic and extrinsic muscles, whose contractility is directed by the alignment of mesoscale fiber tracts.     

De Novo Mutations in the Beta-Tubulin Gene TUBB2A Cause Simplified Gyral Patterning and Infantile-Onset Epilepsy

Tubulins, and microtubule polymers into which they incorporate, play critical mechanical roles in neuronal function during cell proliferation, neuronal migration, and postmigrational development: the three major overlapping events of mammalian cerebral cortex development. A number of neuronally expressed tubulin genes are associated with a spectrum of disorders affecting cerebral cortex formation. Such “tubulinopathies” include lissencephaly/pachygyria, polymicrogyria-like malformations, and simplified gyral patterns, in addition to characteristic extracortical features, such as corpus callosal, basal ganglia, and cerebellar abnormalities. Epilepsy is a common finding in these related disorders. Here we describe two unrelated individuals with infantile-onset epilepsy and abnormalities of brain morphology, harboring de novo variants that affect adjacent amino acids in a beta-tubulin gene TUBB2A. Located in a highly conserved loop, we demonstrate impaired tubulin and microtubule function resulting from each variant in vitro and by using in silico predictive modeling. We propose that the affected functional loop directly associates with the alpha-tubulin-bound guanosine triphosphate (GTP) molecule, impairing the intradimer interface and correct formation of the alpha/beta-tubulin heterodimer. This study associates mutations in TUBB2A with the spectrum of “tubulinopathy” phenotypes. As a consequence, genetic variations affecting all beta-tubulin genes expressed at high levels in the brain (TUBB2B, TUBB3, TUBB, TUBB4A, and TUBB2A) have been linked with malformations of cortical development.     

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia

Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, “bi-modal comparison plots” show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using “worm plots”. Group differences in connections are examined with an existing visualization, the “connectogram”. These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the “Statistical Analysis of Minimum cost path based Structural Connectivity” method and the average fractional anisotropy along the fiber. The functional measures were Pearson’s correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.     

Multiscale Measurements Distinguish Cellular and Interstitial Hindrances to Diffusion In Vivo

Molecular cancer therapy relies on interstitial diffusion for drug distribution in solid tumors. A mechanistic understanding of how tumor components affect diffusion is necessary to advance cancer drug development. Yet, because of limitations in current techniques, it is unclear how individual tissue components hinder diffusion. We developed multiscale fluorescence recovery after photobleaching (MS-FRAP) to address this deficiency. Diffusion measurements facilitated by MS-FRAP distinguish the diffusive hindrance of the interstitial versus cellular constituents in living tissue. Using multiscale diffusion measurements in vivo, we resolved the contributions of these two major tissue components toward impeding diffusive transport in solid tumors and subcutaneous tissue in mice. We further used MS-FRAP in interstitial matrix-mimetic gels and in vivo to show the influence of physical interactions between collagen and hyaluronan on diffusive hindrance through the interstitium. Through these studies, we show that interstitial hyaluronan paradoxically improves diffusion and that reducing cellularity enhances diffusive macromolecular transport in solid tumors.     

Characterizing Brain Structures and Remodeling after TBI Based on Information Content,Diffusion Entropy

Background

To overcome the limitations of conventional diffusion tensor magnetic resonance imaging resulting from the assumption of a Gaussian diffusion model for characterizing voxels containing multiple axonal orientations, Shannon''s entropy was employed to evaluate white matter structure in human brain and in brain remodeling after traumatic brain injury (TBI) in a rat.

Methods

Thirteen healthy subjects were investigated using a Q-ball based DTI data sampling scheme. FA and entropy values were measured in white matter bundles, white matter fiber crossing areas, different gray matter (GM) regions and cerebrospinal fluid (CSF). Axonal densities'' from the same regions of interest (ROIs) were evaluated in Bielschowsky and Luxol fast blue stained autopsy (n = 30) brain sections by light microscopy. As a case demonstration, a Wistar rat subjected to TBI and treated with bone marrow stromal cells (MSC) 1 week after TBI was employed to illustrate the superior ability of entropy over FA in detecting reorganized crossing axonal bundles as confirmed by histological analysis with Bielschowsky and Luxol fast blue staining.

Results

Unlike FA, entropy was less affected by axonal orientation and more affected by axonal density. A significant agreement (r = 0.91) was detected between entropy values from in vivo human brain and histologically measured axonal density from post mortum from the same brain structures. The MSC treated TBI rat demonstrated that the entropy approach is superior to FA in detecting axonal remodeling after injury. Compared with FA, entropy detected new axonal remodeling regions with crossing axons, confirmed with immunohistological staining.

Conclusions

Entropy measurement is more effective in distinguishing axonal remodeling after injury, when compared with FA. Entropy is also more sensitive to axonal density than axonal orientation, and thus may provide a more accurate reflection of axonal changes that occur in neurological injury and disease.