Random noise in Diffusion Tensor Imaging, its Destructive Impact and Some Corrections

The empirical origin of random noise is described, its influence on DTI variables is illustrated by a review of numerical and in vivo studies supplemented by new simulations investigating high noise levels. A stochastic model of noise propagation is presented to structure noise impact in DTI. Finally, basics of voxelwise and spatial denoising procedures are presented. Recent denoising procedures are reviewed and consequences of the stochastic model for convenient denoising strategies are discussed

Measuring latency distribution of transcallosal fibers using transcranial magnetic stimulation

Background: Neuroimaging technology is being developed to enable non-invasive mapping of the latency distribution of cortical projection pathways in white matter, and correlative clinical neurophysiological techniques would be valuable for mutual verification. Interhemispheric interaction through the corpus callosum can be measured with interhemispheric facilitation and inhibition using transcranial magnetic stimulation. Objective: To develop a method for determining the latency distribution of the transcallosal fibers with transcranial magnetic stimulation. Methods: We measured the precise time courses of interhemispheric facilitation and inhibition with a conditioning-test paired-pulse magnetic stimulation paradigm. The conditioning stimulus was applied to the right primary motor cortex and the test stimulus was applied to the left primary motor cortex. The interstimulus interval was set at 0.1 ms resolution. The proportions of transcallosal fibers with different conduction velocities were calculated by measuring the changes in magnitudes of interhemispheric facilitation and inhibition with interstimulus interval. Results: Both interhemispheric facilitation and inhibition increased with increment in interstimulus interval. The magnitude of interhemispheric facilitation was correlated with that of interhemispheric inhibition. The latency distribution of transcallosal fibers measured with interhemispheric facilitation was also correlated with that measured with interhemispheric inhibition. Conclusions: The data can be interpreted as latency distribution of transcallosal fibers. Interhemispheric interaction measured with transcranial magnetic stimulation is a promising technique to determine the latency distribution of the transcallosal fibers. Similar techniques could be developed for other cortical pathways

An in vivo Comparison Study Between Strontium Nanoparticles and rhBMP2

The osteoinductive property of strontium was repeatedly proven in the last decades. Compelling in vitro data demonstrated that strontium hydroxyapatite nanoparticles exert a dual action, by promoting osteoblasts-driven matrix secretion and inhibiting osteoclasts-driven matrix resorption. Recombinant human bone morphogenetic protein 2 (rhBMP2) is a powerful osteoinductive biologic, used for the treatment of vertebral fractures and critically-sized bone defects. Although effective, the use of rhBMP2 has limitations due its recombinant morphogen nature. In this study, we examined the comparison between two osteoinductive agents: rhBMP2 and the innovative strontium-substituted hydroxyapatite nanoparticles. To test their effectiveness, we independently loaded Gelfoam sponges with the two osteoinductive agents and used the sponges as agent-carriers. Gelfoam are FDA-approved biodegradable medical devices used as delivery system for musculoskeletal defects. Their porous structure and spongy morphology make them attractive in orthopedic field. The abiotic characterization of the loaded sponges, involving ion release pattern and structure investigation, was followed by in vivo implantation onto the periosteum of healthy mice and comparison of the effects induced by each implant was performed. Abiotic analysis demonstrated that strontium was continuously released from the sponges over 28 days with a pattern similar to rhBMP2. Histological observations and gene expression analysis showed stronger endochondral ossification elicited by strontium compared to rhBMP2. Osteoclast activity was more inhibited by strontium than by rhBMP2. These results demonstrated the use of sponges loaded with strontium nanoparticles as potential bone grafts might provide better outcomes for complex fractures. Strontium nanoparticles are a novel and effective non-biologic treatment for bone injuries and can be used as novel powerful therapeutics for bone regeneration

Generalized Wishart processes for interpolation over diffusion tensor fields

Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive tool for watching the microstructure of fibrous nerve and muscle tissue. From dMRI, it is possible to estimate 2-rank diffusion tensors imaging (DTI) fields, that are widely used in clinical applications: tissue segmentation, fiber tractography, brain atlas construction, brain conductivity models, among others. Due to hardware limitations of MRI scanners, DTI has the difficult compromise between spatial resolution and signal noise ratio (SNR) during acquisition. For this reason, the data are often acquired with very low resolution. To enhance DTI data resolution, interpolation provides an interesting software solution. The aim of this work is to develop a methodology for DTI interpolation that enhance the spatial resolution of DTI fields. We assume that a DTI field follows a recently introduced stochastic process known as a generalized Wishart process (GWP), which we use as a prior over the diffusion tensor field. For posterior inference, we use Markov Chain Monte Carlo methods. We perform experiments in toy and real data. Results of GWP outperform other methods in the literature, when compared in different validation protocols

On Quantifying Local Geometric Structures of Fiber Tracts

International audienceIn diffusion MRI, fiber tracts, represented by densely distributed 3D curves, can be estimated from diffusion weighted images using tractography. The spatial geometric structure of white matter fiber tracts is known to be complex in human brain, but it carries intrinsic information of human brain. In this paper, inspired by studies of liquid crystals, we propose tract-based director field analysis (tDFA) with total six rotationally invariant scalar indices to quantify local geometric structures of fiber tracts. The contributions of tDFA include: 1) We propose orientational order (OO) and orientational dispersion (OD) indices to quantify the degree of alignment and dispersion of fiber tracts; 2) We define the local orthogonal frame for a set of unoriented curves, which is proved to be a generalization of the Frenet frame defined for a single oriented curve; 3) With the local orthogonal frame, we propose splay, bend, and twist indices to quantify three types of orientational distortion of local fiber tracts, and a total distortion index to describe distortions of all three types. The proposed tDFA for fiber tracts is a generalization of the voxel-based DFA (vDFA) which was recently proposed for a spherical function field (i.e., an ODF field). To our knowledge, this is the first work to quantify orientational distortion (splay, bend, twist, and total distortion) of fiber tracts. Experiments show that the proposed scalar indices are useful descriptors of local geometric structures to visualize and analyze fiber tracts

Fuzzy Fibers: Uncertainty in dMRI Tractography

Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and rendering probabilistic tractograms, which estimate precision in the face of measurement noise and artifacts. However, we also address aspects that have received less attention so far, such as model selection, partial voluming, and the impact of parameters, both in preprocessing and in fiber tracking itself. We conclude by giving impulses for future research

Retrospective Study of Serum Sclerostin Measurements in Bed Rest Subjects

Animal models and human studies suggest that osteocytes regulate the skeleton s response to mechanical unloading at the cellular level in part by an increase in sclerostin, an inhibitor of the anabolic Wnt pathway. However, few studies have reported changes in serum sclerostin in humans exposed to reduced mechanical loading. Thus, we determined changes in serum sclerostin and bone turnover markers in healthy adult men who participated in a controlled bed rest study. Seven healthy adult men (31 +/- 3 yrs old) underwent 90-day six-degree head down tilt bed rest at the University of Texas Medical Branch in Galveston's Institute for Translational Sciences - Clinical Research Center (ITS-CRC). Serum sclerostin, PTH, serum markers of bone turnover (bone specific alkaline phosphatase, RANKL/OPG, and osteocalcin), urinary calcium and phosphorus excretion, and 24 hour pooled urinary markers of bone resorption (NTX, DPD, PYD) were evaluated pre-bed rest (BL), bed rest day 28 (BR-28), bed rest day 60 (BR-60), and bed rest day 90 (BR-90). In addition, bone mineral density (BMD) was assessed by dual-energy X-ray absorptiometry (DXA) at BL, BR-60, and post bed rest day 5 (BR+5). Data are reported as mean +/- standard deviation. We used repeated measures ANOVA to compare baseline values to BR-28, BR-60, and BR-90. RESULTS Consistent with prior reports, BMD declined significantly (1-2% per month) at weight-bearing skeletal sites (spine, hip, femur neck, and calcaneus). Serum sclerostin levels were elevated above BL at BR-28 (+29% +/- 20%, p = 0.003), BR-60 (+42% +/- 31%, p < 0.001), and BR-90 (22% +/- 21%, p = 0.07). Serum PTH levels were reduced at BR-28 (-17% +/- 16%, p = 0.02), BR-60 (-24% +/- 14%, p = 0.03), and returned to baseline at BR-90 (-21% +/- 21%, p = 0.14). Serum bone turnover markers did not change, however urinary bone resorption markers and calcium were significantly elevated following bed rest (p < 0.01). CONCLUSION We observed an increase of serum sclerostin associated with decreased serum PTH and elevated bone resorption markers in otherwise healthy men subjected to long-term immobilization

Efficient Network Reconstruction from Dynamical Cascades Identifies Small-World Topology of Neuronal Avalanches

Cascading activity is commonly found in complex systems with directed interactions such as metabolic networks, neuronal networks, or disease spreading in social networks. Substantial insight into a system's organization can be obtained by reconstructing the underlying functional network architecture from the observed activity cascades. Here we focus on Bayesian approaches and reduce their computational demands by introducing the Iterative Bayesian (IB) and Posterior Weighted Averaging (PWA) methods. We introduce a special case of PWA, cast in nonparametric form, which we call the normalized count (NC) algorithm. NC efficiently reconstructs random and small-world functional network topologies and architectures from subcritical, critical, and supercritical cascading dynamics and yields significant improvements over commonly used correlation methods. With experimental data, NC identified a functional and structural small-world topology and its corresponding traffic in cortical networks with neuronal avalanche dynamics

Topological Strata of Weighted Complex Networks

The statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally defined quantities of nodes and edges, such as node degrees, edge weights and --more recently-- correlations between neighboring nodes. However, statistical methods quickly become cumbersome when dealing with many-body properties and do not capture the precise mesoscopic structure of complex networks. Here we introduce a novel method, based on persistent homology, to detect particular non-local structures, akin to weighted holes within the link-weight network fabric, which are invisible to existing methods. Their properties divide weighted networks in two broad classes: one is characterized by small hierarchically nested holes, while the second displays larger and longer living inhomogeneities. These classes cannot be reduced to known local or quasilocal network properties, because of the intrinsic non-locality of homological properties, and thus yield a new classification built on high order coordination patterns. Our results show that topology can provide novel insights relevant for many-body interactions in social and spatial networks. Moreover, this new method creates the first bridge between network theory and algebraic topology, which will allow to import the toolset of algebraic methods to complex systems.Comment: 26 pages, 19 figures, 1 tabl