COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography.

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.

Strontium ranelate and alendronate have differing effects on distal tibia bone microstructure in women with osteoporosis.

The structural basis of the antifracture efficacy of strontium ranelate and alendronate is incompletely understood. We compared the effects of strontium ranelate and alendronate on distal tibia microstructure over 2 years using HR-pQCT. In this pre-planned, interim, intention-to-treat analysis at 12 months, 88 osteoporotic postmenopausal women (mean age 63.7 +/- 7.4) were randomized to strontium ranelate 2 g/day or alendronate 70 mg/week in a double-placebo design. Primary endpoints were changes in microstructure. Secondary endpoints included lumbar and hip areal bone mineral density (aBMD), and bone turnover markers. This trial is registered with http://www.controlled-trials.com, number ISRCTN82719233. Baseline characteristics of the two groups were similar. Treatment with strontium ranelate was associated with increases in mean cortical thickness (CTh, 5.3%), cortical area (4.9%) and trabecular density (2.1%) (all P < 0.001, except cortical area P = 0.013). No significant changes were observed with alendronate. Between-group differences in favor of strontium ranelate were observed for CTh, cortical area, BV/TV and trabecular density (P = 0.045, 0.041, 0.048 and 0.035, respectively). aBMD increased to a similar extent with strontium ranelate and alendronate at the spine (5.7% versus 5.1%, respectively) and total hip (3.3% versus 2.2%, respectively). No significant changes were observed in remodeling markers with strontium ranelate, while suppression was observed with alendronate. Within the methodological constraints of HR-pQCT through its possible sensitivity to X-ray attenuation of different minerals, strontium ranelate had greater effects than alendronate on distal tibia cortical thickness and trabecular volumetric density.

Thrusting, extension, and doming during the polyphase tectonometamorphic evolution of the High Himalayan Crystalline Zone in NW India

In the NW Himalaya of India, high-grade metamorphic rocks of the High Himalayan Crystalline Zone (HHCZ) are exposed as a 50 km large dome along the Miyar and Gianbul valleys. This Gianbul dome is cored by migmatitic paragneiss formed at peak conditions around 750 degreesC and 8 kbar, and symmetrically surrounded by sillimanite, kyanite +/- staurolite, garnet, biotite, and chlorite Barrovian mineral zones. Thermobarometric and structural investigations reveal that the Gianbul dome results from a polyphase tectono-metamorphic evolution. The first phase corresponds to the NE-directed thrusting of the Shikar Beh nappe, that is responsible for the Barrovian prograde metamorphic field gradient in the southern limb of the dome. In the northern limb of the dome, the Barrovian prograde metamorphism is the consequence of a second tectonic phase, associated with the SW-directed thrusting of the Nyimaling-Tsarap nappe. Following these crustal thickening events, exhumation and doming of the HHCZ high-grade rocks were controlled by extension along the north-dipping Zanskar Shear Zone, in the frontal part of the Nyimaling-Tsarap nappe, as well as by coeval to late extension along the south-dipping Khanjar Shear Zone, in the southern limb of the Gianbul dome. Rapid syn-convergence extension along both of these detachments induced a nearly isothermal decompression, resulting in a high-temperature/low-pressure metamorphic overprint, as well as enhanced partial melting. Such a rapid exhumation within a compressional orogenic context appears unlikely to be controlled solely by granitic diapirism. Alternatively, large-scale doming in the Himalaya could reflect a sub-vertical ductile extrusion of partially melted rocks.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.

Effects of strontium ranelate and alendronate on bone microstructure in women with osteoporosis. Results of a 2-year study.

A Strontium ranelate appears to influence more than alendronate distal tibia bone microstructure as assessed by high-resolution peripheral quantitative computed tomography (HR-pQCT), and biomechanically relevant parameters as assessed by micro-finite element analysis (mu FEA), over 2 years, in postmenopausal osteoporotic women.Introduction Bone microstructure changes are a target in osteoporosis treatment to increase bone strength and reduce fracture risk.Methods Using HR-pQCT, we investigated the effects on distal tibia and radius microstructure of strontium ranelate (SrRan; 2 g/day) or alendronate (70 mg/week) for 2 years in postmenopausal osteoporotic women. This exploratory randomized, double-blind trial evaluated HR-pQCT and FEA parameters, areal bone mineral density (BMD), and bone turnover markers.Results In the intention-to-treat population (n = 83, age: 64 +/- 8 years; lumbar T-score: -2.8 +/- 0.8 [DXA]), distal tibia Cortical Thickness (CTh) and Density (DCort), and cancellous BV/TV increased by 6.3%, 1.4%, and 2.5%, respectively (all P < 0.005), with SrRan, but not with alendronate (0.9%, 0.4%, and 0.8%, NS) (P < 0.05 for all above between-group differences). Difference for CTh evaluated with a distance transformation method was close to significance (P = 0.06). The estimated failure load increased with SrRan (+2.1%, P < 0.005), not with alendronate (-0.6%, NS) (between-group difference, P < 0.01). Cortical stress was lower with SrRan (P < 0.05); both treatments decreased trabecular stress. At distal radius, there was no between-group difference other than DCort (P < 0.05). Bone turnover markers decreased with alendronate; bALP increased (+21%) and serum-CTX-I decreased (-1%) after 2 years of SrRan (between-group difference at each time point for both markers, P < 0.0001). Both treatments were well tolerated.Conclusions Within the constraints of HR-pQCT method, and while a possible artefactual contribution of strontium cannot be quantified, SrRan appeared to influence distal tibia bone microstructure and FEA-determined biomechanical parameters more than alendronate. However, the magnitude of the differences is unclear and requires confirmation with another method.

Widespread age-related differences in the human brain microstructure revealed by quantitative magnetic resonance imaging.

A pressing need exists to disentangle age-related changes from pathologic neurodegeneration. This study aims to characterize the spatial pattern and age-related differences of biologically relevant measures in vivo over the course of normal aging. Quantitative multiparameter maps that provide neuroimaging biomarkers for myelination and iron levels, parameters sensitive to aging, were acquired from 138 healthy volunteers (age range: 19-75 years). Whole-brain voxel-wise analysis revealed a global pattern of age-related degeneration. Significant demyelination occurred principally in the white matter. The observed age-related differences in myelination were anatomically specific. In line with invasive histologic reports, higher age-related differences were seen in the genu of the corpus callosum than the splenium. Iron levels were significantly increased in the basal ganglia, red nucleus, and extensive cortical regions but decreased along the superior occipitofrontal fascicle and optic radiation. This whole-brain pattern of age-associated microstructural differences in the asymptomatic population provides insight into the neurobiology of aging. The results help build a quantitative baseline from which to examine and draw a dividing line between healthy aging and pathologic neurodegeneration.

Modelling of iron-filled magneto-active polymers with a dispersed chain-like microstructure

Magneto-active polymers are a class of smart materials commonly manufactured by mixing micron-sized iron particles in a rubber-like matrix. When cured in the presence of an externally applied magnetic field, the iron particles arrange themselves into chain-like structures that lend an overall anisotropy to the material. It has been observed through electron micrographs and X-ray tomographs that these chains are not always perfect in structure, and may have dispersion due to the conditions present during manufacturing or some undesirable material properties. We model the response of these materials to coupled magneto-mechanical loading in this paper using a probability based structure tensor that accounts for this imperfect anisotropy. The response of the matrix material is decoupled from the chain phase, though still being connected through kinematic constraints. The latter is based on the definition of a 'chain deformation gradient' and a 'chain magnetic field'. We conclude with numerical examples that demonstrate the effect of chain dispersion on the response of the material to magnetoelastic loading.

En face optical coherence tomography of foveal microstructure in full-thickness macular hole: a model to study perifoveal müller cells.

PURPOSE: To characterize perifoveal intraretinal cavities observed around full-thickness macular holes (MH) using en face optical coherence tomography and to establish correlations with histology of human and primate maculae. DESIGN: Retrospective nonconsecutive observational case series. METHODS: Macular en face scans of 8 patients with MH were analyzed to quantify the areas of hyporeflective spaces, and were compared with macular flat mounts and sections from 1 normal human donor eye and 2 normal primate eyes (Macaca fascicularis). Immunohistochemistry was used to study the distribution of glutamine synthetase, expressed by Müller cells, and zonula occludens-1, a tight-junction protein. RESULTS: The mean area of hyporeflective spaces was lower in the inner nuclear layer (INL) than in the complex formed by the outer plexiform (OPL) and the Henle fiber layers (HFL): 5.0 × 10(-3) mm(2) vs 15.9 × 10(-3) mm(2), respectively (P < .0001, Kruskal-Wallis test). In the OPL and HFL, cavities were elongated with a stellate pattern, whereas in the INL they were rounded and formed vertical cylinders. Immunohistochemistry confirmed that Müller cells followed a radial distribution around the fovea in the frontal plane and a "Z-shaped" course in the axial plane, running obliquely in the OPL and HFL and vertically in the inner layers. In addition, zonula occludens-1 co-localized with Müller cells within the complex of OPL and HFL, indicating junctions in between Müller cells and cone axons. CONCLUSION: The dual profile of cavities around MHs correlates with Müller cell morphology and is consistent with the hypothesis of intra- or extracellular fluid accumulation along these cells.

Microstructure of the superior longitudinal fasciculus predicts stimulation-induced interference with on-line motor control.

A cortical visuomotor network, comprising the medial intraparietal sulcus (mIPS) and the dorsal premotor area (PMd), encodes the sensorimotor transformations required for the on-line control of reaching movements. How information is transmitted between these two regions and which pathways are involved, are less clear. Here, we use a multimodal approach combining repetitive transcranial magnetic stimulation (rTMS) and diffusion tensor imaging (DTI) to investigate whether structural connectivity in the 'reaching' circuit is associated to variations in the ability to control and update a movement. We induced a transient disruption of the neural processes underlying on-line motor adjustments by applying 1Hz rTMS over the mIPS. After the stimulation protocol, participants globally showed a reduction of the number of corrective trajectories during a reaching task that included unexpected visual perturbations. A voxel-based analysis revealed that participants exhibiting higher fractional anisotropy (FA) in the second branch of the superior longitudinal fasciculus (SLF II) suffered less rTMS-induced behavioral impact. These results indicate that the microstructural features of the white matter bundles within the parieto-frontal 'reaching' circuit play a prominent role when action reprogramming is interfered. Moreover, our study suggests that the structural alignment and cohesion of the white matter tracts might be used as a predictor to characterize the extent of motor impairments.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Mapping the microstructure properties of the local tissues in the brain is crucial to understand any pathological condition from a biological perspective. Most of the existing techniques to estimate the microstructure of the white matter assume a single axon orientation whereas numerous regions of the brain actually present a fiber-crossing configuration. The purpose of the present study is to extend a recent convex optimization framework to recover microstructure parameters in regions with multiple fibers.

Accelerated Microstructure Imaging via Convex Optimisation for regions with multiple fibres (AMICOx)

This paper reviews and extends our previous work to enable fast axonal diameter mapping from diffusion MRI data in the presence of multiple fibre populations within a voxel. Most of the existing mi-crostructure imaging techniques use non-linear algorithms to fit their data models and consequently, they are computationally expensive and usually slow. Moreover, most of them assume a single axon orientation while numerous regions of the brain actually present more complex configurations, e.g. fiber crossing. We present a flexible framework, based on convex optimisation, that enables fast and accurate reconstructions of the microstructure organisation, not limited to areas where the white matter is coherently oriented. We show through numerical simulations the ability of our method to correctly estimate the microstructure features (mean axon diameter and intra-cellular volume fraction) in crossing regions.

Predicting trabecular bone microdamage initiation and accumulation using a non-linear perfect damage model

Studies evaluating the mechanical behavior of the trabecular microstructure play an important role in our understanding of pathologies such as osteoporosis, and in increasing our understanding of bone fracture and bone adaptation. Understanding of such behavior in bone is important for predicting and providing early treatment of fractures. The objective of this study is to present a numerical model for studying the initiation and accumulation of trabecular bone microdamage in both the pre- and post-yield regions. A sub-region of human vertebral trabecular bone was analyzed using a uniformly loaded anatomically accurate microstructural three-dimensional finite element model. The evolution of trabecular bone microdamage was governed using a non-linear, modulus reduction, perfect damage approach derived from a generalized plasticity stress-strain law. The model introduced in this paper establishes a history of microdamage evolution in both the pre- and post-yield regions