Atlas-based Segmentation of Tumor-bearing Brain Images

In diagnostic neuroradiology as well as in radiation oncology and neurosurgery, there is an increasing demand for accurate segmentation of tumor-bearing brain images. Atlas-based segmentation is an appealing automatic technique thanks to its robustness and versatility. However, atlas-based segmentation of tumor-bearing brain images is challenging due to the confounding effects of the tumor in the patient image. In this article, we provide a brief background on brain tumor imaging and introduce the clinical perspective, before we categorize and review the state of the art in the current literature on atlas-based segmentation for tumor-bearing brain images. We also present selected methods and results from our own research in more detail. Finally, we conclude with a short summary and look at new developments in the field, including requirements for future routine clinical use.

Ice-Core Based Assessment of Historical Anthropogenic Heavy Metal (Cd, Cu, Sb, Zn) Emissions in the Soviet Union

The development of strategies and policies aiming at the reduction of environmental exposure to air pollution requires the assessment of historical emissions. Although anthropogenic emissions from the extended territory of the Soviet Union (SU) considerably influenced concentrations of heavy metals in the Northern Hemisphere, Pb is the only metal with long-term historical emission estimates for this region available, whereas for selected other metals only single values exist. Here we present the first study assessing long-term Cd, Cu, Sb, and Zn emissions in the SU during the period 1935–1991 based on ice-core concentration records from Belukha glacier in the Siberian Altai and emission data from 12 regions in the SU for the year 1980. We show that Zn primarily emitted from the Zn production in Ust-Kamenogorsk (East Kazakhstan) dominated the SU heavy metal emission. Cd, Sb, Zn (Cu) emissions increased between 1935 and the 1970s (1980s) due to expanded non-ferrous metal production. Emissions of the four metals in the beginning of the 1990s were as low as in the 1950s, which we attribute to the economic downturn in industry, changes in technology for an increasing metal recovery from ores, the replacement of coal and oil by gas, and air pollution control.

The influence of sampling design on tree-ring-based quantification of forest growth

Tree-rings offer one of the few possibilities to empirically quantify and reconstruct forest growth dynamics over years to millennia. Contemporaneously with the growing scientific community employing tree-ring parameters, recent research has suggested that commonly applied sampling designs (i.e. how and which trees are selected for dendrochronological sampling) may introduce considerable biases in quantifications of forest responses to environmental change. To date, a systematic assessment of the consequences of sampling design on dendroecological and-climatological conclusions has not yet been performed. Here, we investigate potential biases by sampling a large population of trees and replicating diverse sampling designs. This is achieved by retroactively subsetting the population and specifically testing for biases emerging for climate reconstruction, growth response to climate variability, long-term growth trends, and quantification of forest productivity. We find that commonly applied sampling designs can impart systematic biases of varying magnitude to any type of tree-ring-based investigations, independent of the total number of samples considered. Quantifications of forest growth and productivity are particularly susceptible to biases, whereas growth responses to short-term climate variability are less affected by the choice of sampling design. The world's most frequently applied sampling design, focusing on dominant trees only, can bias absolute growth rates by up to 459% and trends in excess of 200%. Our findings challenge paradigms, where a subset of samples is typically considered to be representative for the entire population. The only two sampling strategies meeting the requirements for all types of investigations are the (i) sampling of all individuals within a fixed area; and (ii) fully randomized selection of trees. This result advertises the consistent implementation of a widely applicable sampling design to simultaneously reduce uncertainties in tree-ring-based quantifications of forest growth and increase the comparability of datasets beyond individual studies, investigators, laboratories, and geographical boundaries.

A novel universal DNA labeling and amplification system for rapid microarray-based detection of 117 antibiotic resistance genes in Gram-positive bacteria.

A rapid and simple DNA labeling system has been developed for disposable microarrays and has been validated for the detection of 117 antibiotic resistance genes abundant in Gram-positive bacteria. The DNA was fragmented and amplified using phi-29 polymerase and random primers with linkers. Labeling and further amplification were then performed by classic PCR amplification using biotinylated primers specific for the linkers. The microarray developed by Perreten et al. (Perreten, V., Vorlet-Fawer, L., Slickers, P., Ehricht, R., Kuhnert, P., Frey, J., 2005. Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria. J.Clin.Microbiol. 43, 2291-2302.) was improved by additional oligonucleotides. A total of 244 oligonucleotides (26 to 37 nucleotide length and with similar melting temperatures) were spotted on the microarray, including genes conferring resistance to clinically important antibiotic classes like β-lactams, macrolides, aminoglycosides, glycopeptides and tetracyclines. Each antibiotic resistance gene is represented by at least 2 oligonucleotides designed from consensus sequences of gene families. The specificity of the oligonucleotides and the quality of the amplification and labeling were verified by analysis of a collection of 65 strains belonging to 24 species. Association between genotype and phenotype was verified for 6 antibiotics using 77 Staphylococcus strains belonging to different species and revealed 95% test specificity and a 93% predictive value of a positive test. The DNA labeling and amplification is independent of the species and of the target genes and could be used for different types of microarrays. This system has also the advantage to detect several genes within one bacterium at once, like in Staphylococcus aureus strain BM3318, in which up to 15 genes were detected. This new microarray-based detection system offers a large potential for applications in clinical diagnostic, basic research, food safety and surveillance programs for antimicrobial resistance.

Symptom-based subtypes of depression and their psychosocial correlates: A person-centered approach focusing on the influence of sex

BACKGROUND: Reducing the complexity of major depressive disorder by symptom-based subtypes constitutes the basis of more specific treatments. To date, few studies have empirically derived symptom subtypes separated by sex, although the impact of sex has been widely accepted in depression research. METHODS: The community-based sample included 373 males and 443 females from the Zurich Program for Sustainable Development of Mental Health Services (ZInEP) manifesting depressive symptoms in the past 12 months. Latent Class Analysis (LCA) was performed separately by sex to extract sex-related depression subtypes. The subtypes were characterized by psychosocial characteristics. RESULTS: Three similar subtypes were found in both sexes: a severe typical subtype (males: 22.8%; females: 35.7%), a severe atypical subtype (males: 17.4%; females: 22.6%), and a moderate subtype (males: 25.2%; females: 41.8%). In males, two additional subgroups were identified: a severe irritable/angry-rejection sensitive (IARS) subtype (30%) comprising the largest group, and a small psychomotor retarded subtype (4%). Males belonging to the severe typical subtype exhibited the lowest masculine gender role orientation, while females of the typical subtype showed more anxiety disorders. The severe atypical subtype was associated with eating disorders in both sexes and with alcohol/drug abuse/dependence in females. In contrast, alcohol/drug abuse/dependence was associated with the severe IARS subtype in males. LIMITATIONS:The study had a cross-sectional design, allowing for no causal inferences. CONCLUSIONS:This study contributes to a better understanding of sex-related depression subtypes, which can be well distinguished on the basis of symptom profiles. This provides the base for future research investigating the etiopathogenesis and effective treatment of the heterogeneous depression disorder.

DNA-based diagnosis of rare diseases in veterinary medicine: a 4.4 kb deletion of ITGB4 is associated with epidermolysis bullosa in Charolais cattle.

BACKGROUND Rare diseases in livestock animals are traditionally poorly diagnosed. Other than clinical description and pathological examination, the underlying causes have, for the most part, remained unknown. A single case of congenital skin fragility in cattle was observed, necropsy, histological and ultrastructural examinations were carried out and whole genome sequencing was utilized to identify the causative mutation. RESULTS A single purebred female Charolais calf with severe skin lesions was delivered full-term and died spontaneously after birth. The clinical and pathological findings exactly matched the gross description given by previous reports on epitheliogenesis imperfecta and epidermolysis bullosa (EB) in cattle. Histological and ultrastructural changes were consistent with EB junctionalis (EBJ). Genetic analysis revealed a previously unpublished ITGB4 loss-of-function mutation; the affected calf was homozygous for a 4.4 kb deletion involving exons 17 to 22, and the dam carried a single copy of the deletion indicating recessive inheritance. The homozygous mutant genotype did not occur in healthy controls of various breeds but some heterozygous carriers were found among Charolais cattle belonging to the affected herd. The mutant allele was absent in a representative sample of unrelated sires of the German Charolais population. CONCLUSION This is the first time in which a recessively inherited ITGB4 associated EBJ has been reported in cattle. The identification of heterozygous carriers is of importance in avoiding the transmission of this defect in future. Current DNA sequencing methods offer a powerful tool for understanding the genetic background of rare diseases in domestic animals having a reference genome sequence available.

Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here we present a graphics processor unit (GPU) based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to auto-regressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and 4 times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a 7-day high-resolution ECG is computed within less than 3 seconds. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

Video-based quantification of body movement indicates negative symptoms: a replication

Objective: In schizophrenia, abnormalities in nonverbal behaviors have always been considered as highly relevant. However, due to methodological limitations, nonverbal behavior was rarely quantified objectively. Recent methodological advances now allow a quantification of body movement from ordinary video recordings. We showed that patients’ objectively measured amount of movement in social role-play interactions was closely associated with their symptom profiles (Kupper, Ramseyer, Hoffmann, & Tschacher, Schizophrenia Research 2010). In the present study, a replication of these results in the context of semi-standardized PANSS (Positive and Negative Syndrome Scale) interviews was intended. Methods: 17 patients with schizophrenia were analyzed during the initial 15-min sequence of a videotaped PANSS interview using Motion Energy Analysis (MEA). The amount of patients’ movement was then correlated with their PANSS symptom scores. Results: Sizeable and significant correlations between negative symptoms and reduced movements (r = -.68, p<0.01) and reduced movement speed (r = -.80, p<0.001) were found. Moreover, cognitive symptoms were related to reduced movement speed (r = -.70, p<.01). Conclusion: Negative symptoms were reliably indicated by patients’ nonverbal behavior in psychopathology interviews. Hence, the main result of our earlier study, examining patients’ nonverbal behavior in role play tests, was replicated for the less structured interactions in psychopathological interviews. Results could encourage the use of MEA in a wide range of videotaped social interactions of patients with schizophrenia and other psychiatric disorders.

First continuous ground-based observations of long period oscillations in strato-/mesospheric wind profiles

Direct measurements of middle-atmospheric wind oscillations with periods between 5 and 50 days in the altitude range between mid-stratosphere (5 hPa) and upper mesosphere (0.02 hPa) have been made using a novel ground-based Doppler wind radiometer. The oscillations were not inferred from measurements of tracers, as the radiometer offers the unique capability of near-continuous horizontal wind profile measurements. Observations from four campaigns at high, mid and low latitudes with an average duration of 10 months have been analyzed. The dominant oscillation has mostly been found to lie in the extra-long period range (20–40 days), while the well-known atmospheric normal modes around 5, 10 and 16 days have also been observed. Comparisons of our results with ECMWF operational analysis model data revealed remarkably good agreement below 0.3 hPa but discrepancies above.

2D-3D Reconstruction-Based Planning of Total Hip Arthroplasty

This chapter proposed a personalized X-ray reconstruction-based planning and post-operative treatment evaluation framework called iJoint for advancing modern Total Hip Arthroplasty (THA). Based on a mobile X-ray image calibration phantom and a unique 2D-3D reconstruction technique, iJoint can generate patient-specific models of hip joint by non-rigidly matching statistical shape models to the X-ray radiographs. Such a reconstruction enables a true 3D planning and treatment evaluation of hip arthroplasty from just 2D X-ray radiographs whose acquisition is part of the standard diagnostic and treatment loop. As part of the system, a 3D model-based planning environment provides surgeons with hip arthroplasty related parameters such as implant type, size, position, offset and leg length equalization. With this newly developed system, we are able to provide true 3D solutions for computer assisted planning of THA using only 2D X-ray radiographs, which is not only innovative but also cost-effective.