Evaluation of texture features in hepatic tissue characterization from non-enhanced CT images

Aim of this paper is to evaluate the diagnostic contribution of various types of texture features in discrimination of hepatic tissue in abdominal non-enhanced Computed Tomography (CT) images. Regions of Interest (ROIs) corresponding to the classes: normal liver, cyst, hemangioma, and hepatocellular carcinoma were drawn by an experienced radiologist. For each ROI, five distinct sets of texture features are extracted using First Order Statistics (FOS), Spatial Gray Level Dependence Matrix (SGLDM), Gray Level Difference Method (GLDM), Laws' Texture Energy Measures (TEM), and Fractal Dimension Measurements (FDM). In order to evaluate the ability of the texture features to discriminate the various types of hepatic tissue, each set of texture features, or its reduced version after genetic algorithm based feature selection, was fed to a feed-forward Neural Network (NN) classifier. For each NN, the area under Receiver Operating Characteristic (ROC) curves (Az) was calculated for all one-vs-all discriminations of hepatic tissue. Additionally, the total Az for the multi-class discrimination task was estimated. The results show that features derived from FOS perform better than other texture features (total Az: 0.802+/-0.083) in the discrimination of hepatic tissue.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Transconvolution and the virtual positron emission tomograph--a new method for cross calibration in quantitative PET∕CT imaging

PURPOSE Positron emission tomography (PET)∕computed tomography (CT) measurements on small lesions are impaired by the partial volume effect, which is intrinsically tied to the point spread function of the actual imaging system, including the reconstruction algorithms. The variability resulting from different point spread functions hinders the assessment of quantitative measurements in clinical routine and especially degrades comparability within multicenter trials. To improve quantitative comparability there is a need for methods to match different PET∕CT systems through elimination of this systemic variability. Consequently, a new method was developed and tested that transforms the image of an object as produced by one tomograph to another image of the same object as it would have been seen by a different tomograph. The proposed new method, termed Transconvolution, compensates for differing imaging properties of different tomographs and particularly aims at quantitative comparability of PET∕CT in the context of multicenter trials. METHODS To solve the problem of image normalization, the theory of Transconvolution was mathematically established together with new methods to handle point spread functions of different PET∕CT systems. Knowing the point spread functions of two different imaging systems allows determining a Transconvolution function to convert one image into the other. This function is calculated by convolving one point spread function with the inverse of the other point spread function which, when adhering to certain boundary conditions such as the use of linear acquisition and image reconstruction methods, is a numerically accessible operation. For reliable measurement of such point spread functions characterizing different PET∕CT systems, a dedicated solid-state phantom incorporating (68)Ge∕(68)Ga filled spheres was developed. To iteratively determine and represent such point spread functions, exponential density functions in combination with a Gaussian distribution were introduced. Furthermore, simulation of a virtual PET system provided a standard imaging system with clearly defined properties to which the real PET systems were to be matched. A Hann window served as the modulation transfer function for the virtual PET. The Hann's apodization properties suppressed high spatial frequencies above a certain critical frequency, thereby fulfilling the above-mentioned boundary conditions. The determined point spread functions were subsequently used by the novel Transconvolution algorithm to match different PET∕CT systems onto the virtual PET system. Finally, the theoretically elaborated Transconvolution method was validated transforming phantom images acquired on two different PET systems to nearly identical data sets, as they would be imaged by the virtual PET system. RESULTS The proposed Transconvolution method matched different PET∕CT-systems for an improved and reproducible determination of a normalized activity concentration. The highest difference in measured activity concentration between the two different PET systems of 18.2% was found in spheres of 2 ml volume. Transconvolution reduced this difference down to 1.6%. In addition to reestablishing comparability the new method with its parameterization of point spread functions allowed a full characterization of imaging properties of the examined tomographs. CONCLUSIONS By matching different tomographs to a virtual standardized imaging system, Transconvolution opens a new comprehensive method for cross calibration in quantitative PET imaging. The use of a virtual PET system restores comparability between data sets from different PET systems by exerting a common, reproducible, and defined partial volume effect.

Classification of interstitial lung disease patterns using local DCT features and random forest.

Over the last decade, a plethora of computer-aided diagnosis (CAD) systems have been proposed aiming to improve the accuracy of the physicians in the diagnosis of interstitial lung diseases (ILD). In this study, we propose a scheme for the classification of HRCT image patches with ILD abnormalities as a basic component towards the quantification of the various ILD patterns in the lung. The feature extraction method relies on local spectral analysis using a DCT-based filter bank. After convolving the image with the filter bank, q-quantiles are computed for describing the distribution of local frequencies that characterize image texture. Then, the gray-level histogram values of the original image are added forming the final feature vector. The classification of the already described patches is done by a random forest (RF) classifier. The experimental results prove the superior performance and efficiency of the proposed approach compared against the state-of-the-art.

Generic detection of coronaviruses and differentiation at the prototype strain level by reverse transcription-PCR and nonfluorescent low-density microarray

A nonfluorescent low-cost, low-density oligonucleotide array was designed for detecting the whole coronavirus genus after reverse transcription (RT)-PCR. The limit of detection was 15.7 copies/reaction. The clinical detection limit in patients with severe acute respiratory syndrome was 100 copies/sample. In 39 children suffering from coronavirus 229E, NL63, OC43, or HKU1, the sensitivity was equal to that of individual real-time RT-PCRs.

Ventral striatum gray matter density reduction in patients with schizophrenia and psychotic emotional dysregulation

INTRODUCTION: Substantial heterogeneity remains across studies investigating changes in gray matter in schizophrenia. Differences in methodology, heterogeneous symptom patterns and symptom trajectories may contribute to inconsistent findings. To address this problem, we recently proposed to group patients by symptom dimensions, which map on the language, the limbic and the motor systems. The aim of the present study was to investigate whether patients with prevalent symptoms of emotional dysregulation would show structural neuronal abnormalities in the limbic system. METHOD: 43 right-handed medicated patients with schizophrenia were assessed with the Bern Psychopathology Scale (BPS). The patients and a control group of 34 healthy individuals underwent structural imaging at a 3T MRI scanner. Whole brain voxel-based morphometry (VBM) was compared between patient subgroups with different severity of emotional dysregulation. Group comparisons (comparison between patients with severe emotional dysregulation, patients with mild emotional dysregulation, patients with no emotional dysregulation and healthy controls) were performed using a one way ANOVA and ANCOVA respectively. RESULTS: Patients with severe emotional dysregulation had significantly decreased gray matter density in a large cluster including the right ventral striatum and the head of the caudate compared to patients without emotional dysregulation. Comparing patients with severe emotional dysregulation and healthy controls, several clusters of significant decreased GM density were detected in patients, including the right ventral striatum, head of the caudate, left hippocampus, bilateral thalamus, dorsolateral prefrontal and orbitofrontal cortex. The significant effect in the ventral striatum was lost when patients with and without emotional dysregulation were pooled and compared with controls. DISCUSSION: Decreased gray matter density in a large cluster including the right ventral striatum was associated with severe symptoms of emotional dysregulation in patients with schizophrenia. The ventral striatum is an important part of the limbic system, and was indicated to be involved in the generation of incentive salience and psychotic symptoms. Only patients with severe emotional dysregulation had decreased gray matter in several brain structures associated with emotion and reward processing compared to healthy controls. The results support the hypothesis that grouping patients according to specific clinical symptoms matched to the limbic system allows identifying patient subgroups with structural abnormalities in the limbic network.

Tree-level contribution to B[over ¯]→X_{d}γ using fragmentation functions

We evaluate the most important tree-level contributions connected with the b→uu ¯ ¯ dγ transition to the inclusive radiative decay B ¯ ¯ ¯ →X d γ using fragmentation functions. In this framework the singularities arising from collinear photon emission from the light quarks (u , u ¯ ¯ , and d ) can be absorbed into the (bare) quark-to-photon fragmentation function. We use as input the fragmentation function extracted by the ALEPH group from the two-jet cross section measured at the large electron positron (LEP) collider, where one of the jets is required to contain a photon. To get the quark-to-photon fragmentation function at the fragmentation scale μ F ∼m b , we use the evolution equation, which we solve numerically. We then calculate the (integrated) photon energy spectrum for b→uu ¯ ¯ dγ related to the operators P u 1,2 . For comparison, we also give the corresponding results when using nonzero (constituent) masses for the light quarks.

The CFTR frameshift mutation 3905insT and its effect at transcript and protein level

Cystic fibrosis (CF) is one of the most common genetic diseases in the Caucasian population and is characterized by chronic obstructive pulmonary disease, exocrine pancreatic insufficiency, and elevation of sodium and chloride concentrations in the sweat and infertility in men. The disease is caused by mutations in the CF transmembrane conductance regulator (CFTR) gene, which encodes a protein that functions as chloride channel at the apical membrane of different epithelia. Owing to the high genotypic and phenotypic disease heterogeneity, effects and consequences of the majority of the CFTR mutations have not yet been studied. Recently, the frameshift mutation 3905insT was identified as the second most frequent mutation in the Swiss population and found to be associated with a severe phenotype. The frameshift mutation produces a premature termination codon (PTC) in exon 20, and transcripts bearing this PTC are potential targets for degradation through nonsense-mediated mRNA decay (NMD) and/or for exon skipping through nonsense-associated alternative splicing (NAS). Using RT-PCR analysis in lymphocytes and different tissue types from patients carrying the mutation, we showed that the PTC introduced by the mutation does neither elicit a degradation of the mRNA through NMD nor an alternative splicing through NAS. Moreover, immunocytochemical analysis in nasal epithelial cells revealed a significantly reduced amount of CFTR at the apical membrane providing a possible molecular explanation for the more severe phenotype observed in F508del/3905insT compound heterozygotes compared with F508del homozygotes. However, further experiments are needed to elucidate the fate of the 3905insT CFTR in the cell after its biosynthesis.

Stocking of captive-bred fish can cause long-term population decline and gene pool replacement: predictions from a population dynamics model incorporating density-dependent mortality

Releasing captive-bred fish into natural environments (stocking) is common in fisheries worldwide. Although stocking is believed to have a positive effect on fish abundance over the short term, little is known about the long-term consequences of recurrent stocking and its influence on natural populations. In fact, there are growing concerns that genetically maladapted captive-bred fish can eventually reduce the abundance of natural population. In this study, we develop a simple model to quantitatively investigate the condition under which recurrent stocking has long-term effects on the natural population. Using a population dynamics model that takes into account a density-dependent recruitment, a gene responsible for the fitness difference between wild and captive-bred fish, and hybridization between them, we show that there is little or no contribution of recurrent stocking to the stock enhancement without a replacement of the wild gene pool by the captive-bred gene pool. The model further predicted that stocking of an intermediate level causes a reduction, rather than enhancement, of population size over the long term. The population decline due to stocking was attributed to the fitness disadvantage of captive-bred fish and strong overcompensation at recruitment stage. These results suggest that it would be difficult to simultaneously attain population size recovery and conservation of the local gene pool when captive-bred fish have fitness disadvantage in the wild, although caution is needed when applying the predictions from the simplified model to a specific species or population.

Reduced Cerebral Blood Flow Within the Default-Mode Network and Within Total Gray Matter in Major Depression

The default-mode network (DMN) was shown to have aberrant blood oxygenation-level-dependent (BOLD) activity in major depressive disorder (MDD). While BOLD is a relative measure of neural activity, cerebral blood flow (CBF) is an absolute measure. Resting-state CBF alterations have been reported in MDD. However, the association of baseline CBF and CBF fluctuations is unclear in MDD. Therefore, the aim was to investigate the CBF within the DMN in MDD, applying a strictly data-driven approach. In 22 MDD patients and 22 matched healthy controls, CBF was acquired using arterial spin labeling (ASL) at rest. A concatenated independent component analysis was performed to identify the DMN within the ASL data. The perfusion of the DMN and its nodes was quantified and compared between groups. The DMN was identified in both groups with high spatial similarity. Absolute CBF values within the DMN were reduced in MDD patients (p<0.001). However, after controlling for whole-brain gray matter CBF and age, the group difference vanished. In patients, depression severity was correlated with reduced perfusion in the DMN in the posterior cingulate cortex and the right inferior parietal lobe. Hypoperfusion within the DMN in MDD is not specific to the DMN. Still, depression severity was linked to DMN node perfusion, supporting a role of the DMN in depression pathobiology. The finding has implications for the interpretation of BOLD functional magnetic resonance imaging data in MDD.

Expression of antagonists of WNT and BMP signaling after non-rigid fixation of osteotomies

Delayed fracture healing and non-unions represent rare but severe complications in orthopedic surgery. Further knowledge on the mechanisms of the bone repair process and of the development of a pseudoarthrosis is essential to predict and prevent impaired healing of fractures. The present study aimed at elucidating differences in gene expression during the repair of rigidly and non-rigidly fixed osteotomies. For this purpose, the MouseFix™ and the FlexiPlate™ systems (AO Development Institute, Davos, CH), allowing the creation of well defined osteotomies in mouse femora, were employed. A time course following the healing process of the osteotomy was performed and bones and periimplant tissues were analyzed by high-resolution X-ray, MicroCT and by histology. For the assessment of gene expression, Low Density Arrays (LDA) were done. In animals with rigid fixation, X-ray and MicroCT revealed healing of the osteotomy within 3 weeks. Using the FlexiPlate™ system, the osteotomy was still visible by X-ray after 3 weeks and a stabilizing cartilaginous callus was formed. After 4.5 weeks, the callus was remodeled and the osteotomy was, on a histological level, healed. Gene expression studies revealed levels of transcripts encoding proteins associated with inflammatory processes not to be altered in tissues from bones with rigid and non-rigid fixation, respectively. Levels of transcripts encoding proteins of the extracellular matrix and essential for bone cell functions were not increased in the rigidly fixed group when compared to controls without osteotomy. In the FlexiPlate™ group, levels of transcripts encoding the same set of genes were significantly increased 3 weeks after surgery. Expression of transcripts encoding BMPs and BMP antagonists was increased after 3 weeks in repair tissues from bones fixed with FlexiPlate™, as were inhibitors of the WNT signaling pathways. Little changes only were detected in transcript levels of tissues from rigidly fixed bones. The data of the present study suggest that rigid fixation enables accelerated healing of an experimental osteotomy as compared to non-rigid fixation. The changes in the healing process after non-rigid fixation are accompanied by an increase in the levels of transcripts encoding inhibitors of osteogenic pathways and, probably as a consequence, by temporal changes in bone matrix synthesis.

The future of osteoporosis treatment - a research update

Osteoporosis is characterised by a progressive loss of bone mass and microarchitecture which leads to increased fracture risk. Some of the drugs available to date have shown reductions in vertebral and non-vertebral fracture risk. However, in the ageing population of industrialised countries, still more fractures happen today than are avoided, which highlights the large medical need for new treatment options, models, and strategies. Recent insights into bone biology, have led to a better understanding of bone cell functions and crosstalk between osteoblasts, osteoclasts, and osteocytes at the molecular level. In the future, the armamentarium against osteoporotic fractures will likely be enriched by (1.) new bone anabolic substances such as antibodies directed against the endogenous inhibitors of bone formation sclerostin and dickkopf-1, PTH and PTHrp analogues, and possibly calcilytics; (2.) new inhibitors of bone resorption such as cathepsin K inhibitors which may suppress osteoclast function without impairing osteoclast viability and thus maintain bone formation by preserving the osteoclast-osteoblast crosstalk, and denosumab, an already widely available antibody against RANKL which inhibits osteoclast formation, function, and survival; and (3.) new therapeutic strategies based on an extended understanding of the pathophysiology of osteoporosis which may include sequential therapies with two or more bone active substances aimed at optimising the management of bone capital acquired during adolescence and maintained during adulthood in terms of both quantity and quality. Finally, one of the future challenges will be to identify those patients and patient populations expected to benefit the most from a given drug therapy or regimen. The WHO fracture risk assessment tool FRAX® and improved access to bone mineral density measurements by DXA will play a key role in this regard.

Imaging emotional brain functions: conceptual and methodological issues

This article reviews the psychophysiological and brain imaging literature on emotional brain function from a methodological point of view. The difficulties in defining, operationalising and measuring emotional activation and, in particular, aversive learning will be considered. Emotion is a response of the organism during an episode of major significance and involves physiological activation, motivational, perceptual, evaluative and learning processes, motor expression, action tendencies and monitoring/subjective feelings. Despite the advances in assessing the physiological correlates of emotional perception and learning processes, a critical appraisal shows that functional neuroimaging approaches encounter methodological difficulties regarding measurement precision (e.g., response scaling and reproducibility) and validity (e.g., response specificity, generalisation to other paradigms, subjects or settings). Since emotional processes are not only the result of localised but also of widely distributed activation, a more representative model of assessment is needed that systematically relates the hierarchy of high- and low-level emotion constructs with the corresponding patterns of activity and functional connectivity of the brain.