MODIFIED TEST STATISTICS BY INTER-VOXEL VARIANCE SHRINKAGE WITH AN APPLICATION TO fMRI

Functional Magnetic Resonance Imaging (fMRI) is a non-invasive technique which is commonly used to quantify changes in blood oxygenation and flow coupled to neuronal activation. One of the primary goals of fMRI studies is to identify localized brain regions where neuronal activation levels vary between groups. Single voxel t-tests have been commonly used to determine whether activation related to the protocol differs across groups. Due to the generally limited number of subjects within each study, accurate estimation of variance at each voxel is difficult. Thus, combining information across voxels in the statistical analysis of fMRI data is desirable in order to improve efficiency. Here we construct a hierarchical model and apply an Empirical Bayes framework on the analysis of group fMRI data, employing techniques used in high throughput genomic studies. The key idea is to shrink residual variances by combining information across voxels, and subsequently to construct an improved test statistic in lieu of the classical t-statistic. This hierarchical model results in a shrinkage of voxel-wise residual sample variances towards a common value. The shrunken estimator for voxelspecific variance components on the group analyses outperforms the classical residual error estimator in terms of mean squared error. Moreover, the shrunken test-statistic decreases false positive rate when testing differences in brain contrast maps across a wide range of simulation studies. This methodology was also applied to experimental data regarding a cognitive activation task.

Cerebral correlates of muscle tone fluctuations in restless legs syndrome: A pilot study with combined functional magnetic resonance imaging and anterior tibial muscle electromyography

BACKGROUND: The pathology of restless legs syndrome (RLS) is still not understood. To investigate the pathomechanism of the disorder further we recorded a surface electromyogram (EMG) of the anterior tibial muscle during functional magnetic resonance imaging (fMRI) in patients with idiopathic RLS. METHODS: Seven subjects with moderate to severe RLS were investigated in the present pilot study. Patients were lying supine in the scanner for over 50min and were instructed not to move voluntarily. Sensory leg discomfort (SLD) was evaluated on a 10-point Likert scale. For brain image analysis, an algorithm for the calculation of tonic EMG values was developed. RESULTS: We found a negative correlation of tonic EMG and SLD (p <0.01). This finding provides evidence for the clinical experience that RLS-related subjective leg discomfort increases during muscle relaxation at rest. In the fMRI analysis, the tonic EMG was associated with activation in motor and somatosensory pathways and also in some regions that are not primarily related to motor or somatosensory functions. CONCLUSIONS: By using a newly developed algorithm for the investigation of muscle tone-related changes in cerebral activity, we identified structures that are potentially involved in RLS pathology. Our method, with some modification, may also be suitable for the investigation of phasic muscle activity that occurs during periodic leg movements.

Automatic extraction of femur contours from calibrated fluoroscopic images

Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity

A novel 2D-based approach to the discovery of candidate substrates for the metalloendopeptidase meprin

In the past, protease-substrate finding proved to be rather haphazard and was executed by in vitro cleavage assays using singly selected targets. In the present study, we report the first protease proteomic approach applied to meprin, an astacin-like metalloendopeptidase, to determine physiological substrates in a cell-based system of Madin-Darby canine kidney epithelial cells. A simple 2D IEF/SDS/PAGE-based image analysis procedure was designed to find candidate substrates in conditioned media of Madin-Darby canine kidney cells expressing meprin in zymogen or in active form. The method enabled the discovery of hitherto unknown meprin substrates with shortened (non-trypsin-generated) N- and C-terminally truncated cleavage products in peptide fragments upon LC-MS/MS analysis. Of 22 (17 nonredundant) candidate substrates identified, the proteolytic processing of vinculin, lysyl oxidase, collagen type V and annexin A1 was analysed by means of immunoblotting validation experiments. The classification of substrates into functional groups may propose new functions for meprins in the regulation of cell homeostasis and the extracellular environment, and in innate immunity, respectively.

Digital processing and data compilation approach for using remotely sensed imagery to identify geological lineaments in hard-rock terrains : an application for groundwater explorations in Nicaragua

Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

Dynamic properties of wood using the Split-Hopkinson Pressure Bar

Strain rate significantly affects the strength of a material. The Split-Hopkinson Pressure Bar (SHPB) was initially used to study the effects of high strain rate (~103 1/s) testing of metals. Later modifications to the original technique allowed for the study of brittle materials such as ceramics, concrete, and rock. While material properties of wood for static and creep strain rates are readily available, data on the dynamic properties of wood are sparse. Previous work using the SHPB technique with wood has been limited in scope to variability of only a few conditions and tests of the applicability of the SHPB theory on wood have not been performed. Tests were conducted using a large diameter (3.0 inch (75 mm)) SHPB. The strain rate and total strain applied to a specimen are dependent on the striker bar length and velocity at impact. Pulse shapers are used to further modify the strain rate and change the shape of the strain pulse. A series of tests were used to determine test conditions necessary to produce a strain rate, total strain, and pulse shape appropriate for testing wood specimens. Hard maple, consisting of sugar maple (Acer saccharum) and black maple (Acer nigrum), and eastern white pine (Pinus strobus) specimens were used to represent a dense hardwood and a low-density soft wood. Specimens were machined to diameters of 2.5 and 3.0 inches and an assortment of lengths were tested to determine the appropriate specimen dimensions. Longitudinal specimens of 1.5 inch length and radial and tangential specimens of 0.5 inch length were found to be most applicable to SHPB testing. Stress/strain curves were generated from the SHPB data and validated with 6061-T6 aluminum and wood specimens. Stress was indirectly corroborated with gaged aluminum specimens. Specimen strain was assessed with strain gages, digital image analysis, and measurement of residual strain to confirm the strain calculated from SHPB data. The SHPB was found to be a useful tool in accurately assessing the material properties of wood under high strain rates (70 to 340 1/s) and short load durations (70 to 150 μs to compressive failure).

Hierarchical Markov Random Fields Applied to Model Soft Tissue Deformations on Graphics Hardware

Many methodologies dealing with prediction or simulation of soft tissue deformations on medical image data require preprocessing of the data in order to produce a different shape representation that complies with standard methodologies, such as mass–spring networks, finite element method s (FEM). On the other hand, methodologies working directly on the image space normally do not take into account mechanical behavior of tissues and tend to lack physics foundations driving soft tissue deformations. This chapter presents a method to simulate soft tissue deformations based on coupled concepts from image analysis and mechanics theory. The proposed methodology is based on a robust stochastic approach that takes into account material properties retrieved directly from the image, concepts from continuum mechanics and FEM. The optimization framework is solved within a hierarchical Markov random field (HMRF) which is implemented on the graphics processor unit (GPU See Graphics processing unit ).

Novel autoantigens immunogenic in COPD patients

Background Chronic obstructive pulmonary disease (COPD) is a respiratory inflammatory condition with autoimmune features including IgG autoantibodies. In this study we analyze the complexity of the autoantibody response and reveal the nature of the antigens that are recognized by autoantibodies in COPD patients. Methods An array of 1827 gridded immunogenic peptide clones was established and screened with 17 sera of COPD patients and 60 healthy controls. Protein arrays were evaluated both by visual inspection and a recently developed computer aided image analysis technique. By this computer aided image analysis technique we computed the intensity values for each peptide clone and each serum and calculated the area under the receiver operator characteristics curve (AUC) for each clone and the separation COPD sera versus control sera. Results By visual evaluation we detected 381 peptide clones that reacted with autoantibodies of COPD patients including 17 clones that reacted with more than 60% of the COPD sera and seven clones that reacted with more than 90% of the COPD sera. The comparison of COPD sera and controls by the automated image analysis system identified 212 peptide clones with informative AUC values. By in silico sequence analysis we found an enrichment of sequence motives previously associated with immunogenicity. Conclusion The identification of a rather complex humoral immune response in COPD patients supports the idea of COPD as a disease with strong autoimmune features. The identification of novel immunogenic antigens is a first step towards a better understanding of the autoimmune component of COPD.

Tree phenology and carbon dioxide fluxes - use of digital photography for process-based interpretation at the ecosystem scale

Vegetation phenology is an important indicator of climate change and climate variability and it is strongly connected to biospheric–atmospheric gas exchange. We aimed to evaluate the applicability of phenological information derived from digital imagery for the interpretation of CO2 exchange measurements. For the years 2005–2007 we analyzed seasonal phenological development of 2 temperate mixed forests using tower-based imagery from standard RGB cameras. Phenological information was jointly analyzed with gross primary productivity (GPP) derived from net ecosystem exchange data. Automated image analysis provided reliable information on vegetation developmental stages of beech and ash trees covering all seasons. A phenological index derived from image color values was strongly correlated with GPP, with a significant mean time lag of several days for ash trees and several weeks for beech trees in early summer (May to mid-July). Leaf emergence dates for the dominant tree species partly explained temporal behaviour of spring GPP but were also masked by local meteorological conditions. We conclude that digital cameras at flux measurement sites not only provide an objective measure of the physiological state of a forest canopy at high temporal and spatial resolutions, but also complement CO2 and water exchange measurements, improving our knowledge of ecosystem processes.

Mitotic figure counts are significantly overestimated in resection specimens of invasive breast carcinomas

Several authors have demonstrated an increased number of mitotic figures in breast cancer resection specimen when compared with biopsy material. This has been ascribed to a sampling artifact where biopsies are (i) either too small to allow formal mitotic figure counting or (ii) not necessarily taken form the proliferating tumor periphery. Herein, we propose a different explanation for this phenomenon. Biopsy and resection material of 52 invasive ductal carcinomas was studied. We counted mitotic figures in 10 representative high power fields and quantified MIB-1 immunohistochemistry by visual estimation, counting and image analysis. We found that mitotic figures were elevated by more than three-fold on average in resection specimen over biopsy material from the same tumors (20±6 vs 6±2 mitoses per 10 high power fields, P=0.008), and that this resulted in a relative diminution of post-metaphase figures (anaphase/telophase), which made up 7% of all mitotic figures in biopsies but only 3% in resection specimen (P<0.005). At the same time, the percentages of MIB-1 immunostained tumor cells among total tumor cells were comparable in biopsy and resection material, irrespective of the mode of MIB-1 quantification. Finally, we found no association between the size of the biopsy material and the relative increase of mitotic figures in resection specimen. We propose that the increase in mitotic figures in resection specimen and the significant shift towards metaphase figures is not due to a sampling artifact, but reflects ongoing cell cycle activity in the resected tumor tissue due to fixation delay. The dwindling energy supply will eventually arrest tumor cells in metaphase, where they are readily identified by the diagnostic pathologist. Taken together, we suggest that the rapidly fixed biopsy material better represents true tumor biology and should be privileged as predictive marker of putative response to cytotoxic chemotherapy.

Geometric properties of the lung parenchyma after postnatal glucocorticoid treatment in rats

While glucocorticoid (GC) administration appears to be beneficial during the acute phase of treatment of neonates at risk of developing chronic lung disease, it is still not clear whether steroid application has an adverse long-term effect on the lung maturation. Thus, the goal of the present work was to analyze GC effects on the pulmonary structure in a rat model where dosage and timing of drug administration were adapted to the therapeutic situation in human neonatology. The animals received daily a maximum of 0.1 mg dexamethasone phosphate per kilogram body weight during the first 4 postnatal days. Investigations were performed at the light microscopic level by means of a digital image analysis system. While there were no differences in the lung architecture between experimental animals and controls on day 4, the earliest time point of observation, we found a widening of airspaces with a concomitant decrease in the alveolar surface area density, representing a loss of parenchymal complexity, on days 10 and 21 in treated rats. On days 36 and 60, however, no alterations in the pulmonary parenchyma could be detected in experimental animals. We conclude from these findings that the GC-induced initial inhibition of development (days 10 and 21) was completely reversed, so that a normal parenchymal architecture and also a normal alveolar surface area density were found in adult rats (days 36 and 60). From the results obtained using the regimen of GC administration described, mimicking more closely the steroid treatment in human neonatology, we conclude that the observed short-term adverse effects on lung development can be fully compensated until adult age.