A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk.

We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates - one via a weighted PCa 'risk' score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.

Mixed spectral-structural classification of very high resolution images with summation kernels

In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.

Quantitative multi-parameter mapping of R1, PD(*), MT, and R2(*) at 3T: a multi-center validation.

Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD(*)), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2(*) = 1/T2(*)). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2(*) (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

Patient doses in CT examinations in Switzerland: implementation of national diagnostic reference levels.

Diagnostic reference levels (DRLs) were established for 21 indication-based CT examinations for adults in Switzerland. One hundred and seventy-nine of 225 computed tomography (CT) scanners operated in hospitals and private radiology institutes were audited on-site and patient doses were collected. For each CT scanner, a correction factor was calculated expressing the deviation of the measured weighted computed tomography dose index (CTDI) to the nominal weighted CTDI as displayed on the workstation. Patient doses were corrected by this factor providing a realistic basis for establishing national DRLs. Results showed large variations in doses between different radiology departments in Switzerland, especially for examinations of the petrous bone, pelvis, lower limbs and heart. This indicates that the concept of DRLs has not yet been correctly applied for CT examinations in clinical routine. A close collaboration of all stakeholders is mandatory to assure an effective radiation protection of patients. On-site audits will be intensified to further establish the concept of DRLs in Switzerland.

ADC mapping of chronic cerebral hypoperfusion induced by carotid artery stenosis.

BACKGROUND: Carotid artery stenosis is associated with the occurrence of acute and chronic ischemic lesions that increase with age in the elderly population. Diffusion Imaging and ADC mapping may be an appropriate method to investigate patients with chronic hypoperfusion consecutive to carotid stenosis. This non-invasive technique allows to investigate brain integrity and structure, in particular hypoperfusion induced by carotid stenosis diseases. The aim of this study was to evaluate the impact of a carotid stenosis on the parenchyma using ADC mapping. METHODS: Fifty-nine patients with symptomatic (33) and asymptomatic (26) carotid stenosis were recruited from our multidisciplinary consultation. Both groups demonstrated a similar degree of stenosis. All patients underwent MRI of the brain including diffusion-weighted MR imaging with ADC mapping. Regions of interest were defined in the anterior and posterior paraventricular regions both ipsilateral and contralateral to the stenosis (anterior circulation). The same analysis was performed for the thalamic and occipital regions (posterior circulation). RESULTS: ADC values of the affected vascular territory were significantly higher on the side of the stenosis in the periventricular anterior (P<0.001) and posterior (P<0.01) area. There was no difference between ipsilateral and contralateral ADC values in the thalamic and occipital regions. CONCLUSIONS: We have shown that carotid stenosis is associated with significantly higher ADC values in the anterior circulation, probably reflecting an impact of chronic hypoperfusion on the brain parenchyma in symptomatic and asymptomatic patients. This is consistent with previous data in the literature.

Local optima networks of hard combinatorial landscapes

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.

Inferring ultraviolet anatomical exposure patterns while distinguishing the relative contribution of radiation components

Exposure to solar ultraviolet (UV) radiation is the main causative factor for skin cancer. UV exposure depends on environmental and individual factors, but individual exposure data remain scarce. UV irradiance is monitored via different techniques including ground measurements and satellite observations. However it is difficult to translate such observations into human UV exposure or dose because of confounding factors (shape of the exposed surface, shading, behavior, etc.) A collaboration between public health institutions, a meteorological office and an institute specialized in computing techniques developed a model predicting the dose and distribution of UV exposure on the basis of ground irradiation and morphological data. Standard 3D computer graphics techniques were adapted to develop this tool, which estimates solar exposure of a virtual manikin depicted as a triangle mesh surface. The amount of solar energy received by various body locations is computed for direct, diffuse and reflected radiation separately. The radiation components are deduced from corresponding measurements of UV irradiance, and the related UV dose received by each triangle of the virtual manikin is computed accounting for shading by other body parts and eventual protection measures. The model was verified with dosimetric measurements (n=54) in field conditions using a foam manikin as surrogate for an exposed individual. Dosimetric results were compared to the model predictions. The model predicted exposure to solar UV adequately. The symmetric mean absolute percentage error was 13%. Half of the predictions were within 17% range of the measurements. This model allows assessing outdoor occupational and recreational UV exposures, without necessitating time-consuming individual dosimetry, with numerous potential uses in skin cancer prevention and research. Using this tool, we investigated solar UV exposure patterns with respect to the relative contribution of the direct, diffuse and reflected radiation. We assessed exposure doses for various body parts and exposure scenarios of a standing individual (static and dynamic postures). As input, the model used erythemally-weighted ground irradiance data measured in 2009 at Payerne, Switzerland. A year-round daily exposure (8 am to 5 pm) without protection was assumed. For most anatomical sites, mean daily doses were high (typically 6.2-14.6 SED) and exceeded recommended exposure values. Direct exposure was important during specific periods (e.g. midday during summer), but contributed moderately to the annual dose, ranging from 15 to 24% for vertical and horizontal body parts, respectively. Diffuse irradiation explained about 80% of the cumulative annual exposure dose. Acute diffuse exposures were also obtained for cloudy summer days. The importance of diffuse UV radiation should not be underestimated when advocating preventive measures. Messages focused on avoiding acute direct exposures may be of limited efficiency to prevent skin cancers associated with chronic exposure (e.g., squamous cell carcinomas).

Anatomical exposure patterns of skin to sunlight: relative contributions of direct, diffuse and reflected ultraviolet radiation

Summary Background  The dose-response between ultraviolet (UV) exposure patterns and skin cancer occurrence is not fully understood. Sun-protection messages often focus on acute exposure, implicitly assuming that direct UV radiation is the key contributor to the overall UV exposure. However, little is known about the relative contribution of the direct, diffuse and reflected radiation components. Objective  To investigate solar UV exposure patterns at different body sites with respect to the relative contribution of the direct, diffuse and reflected radiation. Methods  A three-dimensional numerical model was used to assess exposure doses for various body parts and exposure scenarios of a standing individual (static and dynamic postures). The model was fed with erythemally weighted ground irradiance data for the year 2009 in Payerne, Switzerland. A year-round daily exposure (08:00-17:00 h) without protection was assumed. Results  For most anatomical sites, mean daily doses were high (typically 6·2-14·6 standard erythemal doses) and exceeded the recommended exposure values. Direct exposure was important during specific periods (e.g. midday during summer), but contributed moderately to the annual dose, ranging from 15% to 24% for vertical and horizontal body parts, respectively. Diffuse irradiation explained about 80% of the cumulative annual exposure dose. Acute diffuse exposures were also observed during cloudy summer days. Conclusions  The importance of diffuse UV radiation should not be underestimated when advocating preventive measures. Messages focused on avoiding acute direct exposures may be of limited efficiency to prevent skin cancers associated with chronic exposure.

Robust Estimators of the Generalized Log-Gamma Distribution

We propose robust estimators of the generalized log-gamma distribution and, more generally, of location-shape-scale families of distributions. A (weighted) Q tau estimator minimizes a tau scale of the differences between empirical and theoretical quantiles. It is n(1/2) consistent; unfortunately, it is not asymptotically normal and, therefore, inconvenient for inference. However, it is a convenient starting point for a one-step weighted likelihood estimator, where the weights are based on a disparity measure between the model density and a kernel density estimate. The one-step weighted likelihood estimator is asymptotically normal and fully efficient under the model. It is also highly robust under outlier contamination. Supplementary materials are available online.

Effect of water velocity on the uptake of polychlorinatedd biphenyls (PCBs) by silicone rubber (SR) and low-density polyethylene (LDPE) passive samplers: an assessment of the efficiency of performance reference compounds (PRCs) in river-like flow conditions

One aim of this study is to determine the impact of water velocity on the uptake of indicator polychlorinated biphenyls (iPCBs) by silicone rubber (SR) and low-density polyethylene (LDPE) passive samplers. A second aim is to assess the efficiency of performance reference compounds (PRCs) to correct for the impact of water velocity. SR and LDPE samplers were spiked with 11 or 12 PRCs and exposed for 6 weeks to four different velocities (in the range of 1.6 to 37.7 cm s−1) in river-like flow conditions using a channel system supplied with river water. A relationship between velocity and the uptakewas found for each iPCB and enables to determine expected changes in the uptake due to velocity variations. For both samplers, velocity increases from 2 to 10 cm s−1, 30 cm s−1 (interpolated data) and 100 cm s−1 (extrapolated data) lead to increases of the uptake which do not exceed a factor of 2, 3 and 4.5, respectively. Results also showed that the influence of velocity decreased with increasing the octanol-water coefficient partition (log Kow) of iPCBs when SR is used whereas the opposite effect was observed for LDPE. Time-weighted average (TWA) concentrations of iPCBs in water were calculated from iPCB uptake and PRC release. These calculations were performed using either a single PRC or all the PRCs. The efficiency of PRCs to correct the impact of velocity was assessed by comparing the TWA concentrations obtained at the four tested velocities. For SR, a good agreement was found among the four TWA concentrations with both methods (average RSD b 10%). Also for LDPE, PRCs offered a good correction of the impact of water velocity (average RSD of about 10 to 20%). These results contribute to the process of acceptance of passive sampling in routine regulatory monitoring programs.

A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Justice and Court Administrations, Their Workings and Efficiency in Switzerland : Aspects of Sentencing And Its Outcome In Swiss Cantons

The comparison of the operations of the administration of justice among cantons shows on one side large differences in the three major types of sentencing, in the use of pre-trial detention and the unsuspended prison sanction. When combined, one finds however very weak relationships when considering absolute, percentage or weighted results. On the other side, the outcome of these different policies is much paradoxical as there are no differences when comparing recidivism rates among cantons, despite strong differences in the use of pre-trial detention and the sentencing with prison sanctions. The paradoxical outcome of crime policies in terms of recidivism - e.g. the absence of differences of the outcome based on sanctions in the domain of less severe delinquency - suggests the need for more empirically informed crime policies. The role of justice administrators could be to participate in the dissemination of those findings as well as the dissemination of best practices among cantons with regard to outcomes and the use of resources - especially with consideration to the use of the prison sanction as it is the most costly and the most inefficient of all sanctions. Furthermore, the observance of the principle of equality before the law would be most likely be promoted.

Is magnetic resonance imaging of hepatic hemangioma any different in liver fibrosis and cirrhosis compared to normal liver?

PURPOSE: To compare qualitative and quantitative magnetic resonance (MR) imaging characteristics of hepatic hemangiomas in patients with normal, fibrotic and cirrhotic livers. MATERIALS AND METHODS: Retrospective, institutional review board approved study (waiver of informed consent). Eighty-nine consecutive patients with 231 hepatic hemangiomas who underwent liver MR imaging for lesion characterization were included. Lesions were classified into three groups according to the patients' liver condition: no underlying liver disease (group 1), fibrosis (group 2) and cirrhosis (group 3). Qualitative and quantitative characteristics (number, size, signal intensities on T1-, T2-, and DW MR images, T2 shine-through effect, enhancement patterns (classical, rapidly filling, delayed filling), and ADC values) were compared. RESULTS: There were 160 (69%), 45 (20%), and 26 (11%) hemangiomas in groups 1, 2 and 3, respectively. Lesions were larger in patients with normal liver (group 1 vs. groups 2 and 3; P=.009). No difference was found between the groups on T2-weighted images (fat-suppressed fast spin-echo (P=.82) and single-shot (P=.25)) and in enhancement patterns (P=.56). Mean ADC values of hemangiomas were similar between groups 1, 2 and 3 (2.11±.52×10(-3)mm(2)/s, 2.1±.53×10(-3)mm(2)/s and 2.14±.44×10(-3)mm(2)/s, P=87, respectively). T2 shine-through effect was less frequently observed in cirrhosis (P=.02). CONCLUSION: MR imaging characteristics of hepatic hemangioma were similar in patients with normal compared to fibrotic and cirrhotic livers. Smaller lesion size was observed with liver disease and less T2 shine-through effect was seen in hemangiomas developed on cirrhosis, the latter being an important finding to highlight in these patients at risk of developing hepatocellular carcinoma.

The importance of sonographer experience and machine quality with regards to the role of musculoskeletal ultrasound in routine care of rheumatoid arthritis patients.

OBJECTIVES: Regarding recent progress, musculoskeletal ultrasound (US) will probably soon be integrated in standard care of patient with rheumatoid arthritis (RA). However, in daily care, quality of US machines and level of experience of sonographers are varied. We conducted a study to assess reproducibility and feasibility of an US scoring for RA, including US devices of different quality and rheumatologist with various levels of expertise in US as it would be in daily care. METHODS: The Swiss Sonography in Arthritis and Rheumatism (SONAR) group has developed a semi-quantitative score using OMERACT criteria for synovitis and erosion in RA. The score was taught to 108 rheumatologists trained in US. One year after the last workshop, 19 rheumatologists participated in the study. Scans were performed on 6 US machines ranging from low to high quality, each with a different patient. Weighted kappa was calculated for each pair of readers. RESULTS: Overall, the agreement was fair to moderate. Quality of device, experience of the sonographers and practice of the score before the study improved substantially the agreement. Agreement assessed on higher quality machine, among sonographers with good experience in US increased to substantial (median kappa for B-mode and Doppler: 0.64 and 0.41 for erosion). CONCLUSIONS: This study demonstrated feasibility and reproducibility of the Swiss US SONAR score for RA. Our results confirmed importance of the quality of US machine and the training of sonographers for the implementation of US scoring in the routine daily care of RA.

Do we need to revise the tripartite subdivision hypothesis of the human subthalamic nucleus (STN)? Response to Alkemade and Forstmann.

Recently in this journal, Alkemade and Forstmann again challenged the evidence for a tripartite organisation to the subthalamic nucleus (STN) (Alkemade & Forstmann 2014). Additionally, they raised specific issues with the earlier published results using 3T MRI to perform in vivo diffusion weighted imaging (DWI) based segmentation of the STN (Lambert et al. 2012). Their comments reveal a common misconception related to the underlying methodologies used, which we clarify in this reply, in addition to highlighting how their current conclusions are synonymous with our original paper. The ongoing debate, instigated by the controversies surrounding STN parcellation, raises important implications for the assumptions and methodologies employed in mapping functional brain anatomy, both in vivo and ex vivo, and reveals a fundamental emergent problem with the current techniques. These issues are reviewed, and potential strategies that could be developed to manage them in the future are discussed further.