MASCG: Multi-Atlas Segmentation Constrained Graph method for accurate segmentation of hip CT images

This paper addresses the issue of fully automatic segmentation of a hip CT image with the goal to preserve the joint structure for clinical applications in hip disease diagnosis and treatment. For this purpose, we propose a Multi-Atlas Segmentation Constrained Graph (MASCG) method. The MASCG method uses multi-atlas based mesh fusion results to initialize a bone sheetness based multi-label graph cut for an accurate hip CT segmentation which has the inherent advantage of automatic separation of the pelvic region from the bilateral proximal femoral regions. We then introduce a graph cut constrained graph search algorithm to further improve the segmentation accuracy around the bilateral hip joint regions. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 15-fold cross validation. When the present approach was compared to manual segmentation, an average surface distance error of 0.30 mm, 0.29 mm, and 0.30 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. A further look at the bilateral hip joint regions demonstrated an average surface distance error of 0.16 mm, 0.21 mm and 0.20 mm for the acetabulum, the left femoral head, and the right femoral head, respectively.

Variations of clinopyroxene/melt element partitioning during assimilation of olivine/peridotite by low-Mg diorite magma

The effects of crystal chemistry and melt composition on the control of clinopyroxene/melt element partitioning (D) during the assimilation of olivine/peridotite by felsic magma have been investigated in Mesozoic high-Mg diorites from North China. The assimilation resulted in significant increase of Mg, Cr and Ni and only slight (< 30%) decrease of incompatible elements of the magma, and the compositional variations have been mirrored by the normally and reversely zoned clinopyroxene microphenocrysts formed at the early stage of the magma evolution. The Mg# [100 × Mg / (Mg + Fe)] values of the reversely zoned clinopyroxenes increase from 65 to 75 in the core to 85–90 in the high-Mg midsection, and reduce back to 73–79 at the rim. Trace element profiles across all these clinopyroxene domains have been measured by LA-ICP-MS. The melt trace element composition has been constrained from bulk rock analyses of the fine-grained low- and high-Mg diorites. Clinopyroxene/melt partition coefficients for rare earth elements (REE) and Y in the high-Mg group zonings (Mg# > 73–79, DDy < 1.2) are positively correlated with tetrahedral IVAl and increase by a factor of 3–4 as tetrahedral IVAl increases from 0.01 to 0.1 per formula unit (pfu). These systematic variations are interpreted to be controlled by the clinopyroxene composition. In contrast, partition coefficients for low-Mg group zonings (Mg# < 75–79, DDy > 1.2) are elevated by up to an order of magnitude (for REE and Y) or more (for Zr and Hf) at similar IVAl, indicating dominant control of melt composition/structure. DZr and DHf show a larger sensitivity to the compositional change of crystal and melt than DREE. DTi values for the low- and high-Mg zonings show a uniform dependence on IVAl. DSr and DLi are insensitive to the compositional change of clinopyroxene and melt, resulting in Sr depletions in the clinopyroxene zonings with elevated REE without crystallization of plagioclase. Our observations show that crystal chemistry and melt composition/structure may alternatively control clinopyroxene/melt partitioning during the assimilation of peridotite by felsic magma, and may be useful for deciphering clinopyroxene compositions and related crust–mantle processes.

Partitioning the Choice Task Makes Starbucks Coffee Taste Better

Consumers are often less satisfied with a product chosen from a large assortment than a limited one. Experienced choice difficulty presumably causes this as consumers have to engage in a great number of individual comparisons. In two studies we tested whether partitioning the choice task so that consumers decided sequentially on each individual attribute may provide a solution. In a Starbucks coffee house, consumers who chose from the menu rated the coffee as less tasty when chosen from a large rather than a small assortment. However, when the consumers chose it by sequentially deciding about one attribute at a time, the effect reversed. In a tailored-suit customization, consumers who chose multiple attributes at a time were less satisfied with their suit, compared to those who chose one attribute at a time. Sequential attribute-based processing proves to be an effective strategy to reap the benefits of a large assortment.

The enduring effects of psychodynamic treatments vis-à-vis alternative treatments: A multilevel longitudinal meta-analysis

Although evidence suggests that the benefits of psychodynamic treatments are sustained over time, presently it is unclear whether these sustained benefits are superior to non-psychodynamic treatments. Additionally, the extant literature comparing the sustained benefits of psychodynamic treatments compared to alternative treatments is limited with methodological shortcomings. The purpose of the current study was to conduct a rigorous test of the growth of the benefits of psychodynamic treatments relative to alternative treatments across distinct domains of change (i.e., all outcome measures, targeted outcome measures, non-targeted outcome measures, and personality outcome measures). To do so, the study employed strict inclusion criteria to identify randomized clinical trials that directly compared at least one bona fide psychodynamic treatment and one bona fide non-psychodynamic treatment. Hierarchical linear modeling (Raudenbush, Bryk, Cheong, Congdon, & du Toit, 2011) was used to longitudinally model the impact of psychodynamic treatments compared to non-psychodynamic treatments at post-treatment and to compare the growth (i.e., slope) of effects beyond treatment completion. Findings from the present meta-analysis indicated that psychodynamic treatments and non-psychodynamic treatments were equally efficacious at post-treatment and at follow-up for combined outcomes (k=20), targeted outcomes (k=19), non-targeted outcomes (k=17), and personality outcomes (k=6). Clinical implications, directions for future research, and limitations are discussed.

Apatite as an indicator of fluid salinity: An experimental study of chlorine and fluorine partitioning in subducted sediments

In order to constrain the salinity of subduction zone fluids, piston-cylinder experiments have been conducted to investigate the partitioning behaviour of Cl and F in subducted sediments. These experiments were performed at H2O-undersaturated conditions with a synthetic pelite starting composition containing 800 ppm Cl, over a pressure and temperature range of 2.5–4.5 GPa and 630–900 °C. Repetitive experiments were conducted with 1900 ppm Cl + 1000 ppm F, and 2100 ppm Cl. Apatite represents the most Cl-abundant mineral phase, with Cl concentration varying in the range 0.1–2.82 wt%. Affinity for Cl decreases over the following sequence: aqueous fluid > apatite ⩾ melt > other hydrous minerals (phengite, biotite and amphibole). It was found that addition of F to the Cl-bearing starting composition significantly lowers the Cl partition coefficients between apatite and melt (DClAp–melt) and apatite and aqueous fluid (DClAp–aq). Cl–OH exchange coefficients between apatite and melt (KdCl–OHAp–melt) and apatite and aqueous fluid (KdCl–OHAp–aq) were subsequently calculated. KdCl–OHAp–melt was found to vary from 1 to 58, showing an increase with temperature and a decrease with pressure and displaying a regular decrease with increasing H2O content in melt. Mole fractions of Cl and OH in melt were calculated based on an ideal mixing model for H2O, OH, O, Cl and F. The Cl contents of other hydrous minerals (phengite, biotite and amphibole) fall between 200 and 800 ppm, with resultant Cl partition coefficients from 0.02 to 0.49, appearing independent of the bulk Cl and F content. Preliminary data from this study show that the partitioning behaviour of F is strongly in favour of apatite relative to melt and phengite, with DFAp–melt = 15–51. Apatites from representative eclogite facies metasediments were examined and found to have low Cl contents close to ∼100 ppm. Calculations using our experimentally determined KdCl–OHAp–aq of 0.004 at 2.5 GPa, 630 °C indicate a low salinity character (0.5–2 wt% NaCleq) for the fluid formed during dehydration of subducted oceanic sediment at ∼80 km depth.

PSHARE: Stata module to compute and graph percentile shares

-pshare- computes and graphs percentile shares from individual level data. Percentile shares are often used in inequality research to study the distribution of income or wealth. They are defined as differences between Lorenz ordinates of the outcome variable. Technically, the observations are sorted in increasing order of the outcome variable and the specified percentiles are computed from the running sum of the outcomes. Percentile shares are then computed as differences between percentiles, divided by total outcome. pshare requires moremata to be installed on the system; see ssc describe moremata.

Multilevel analysis for a longitudinal clinical trial

This study applies the multilevel analysis technique to longitudinal data of a large clinical trial. The technique accounts for the correlation at different levels when modeling repeated blood pressure measurements taken throughout the trial. This modeling allows for closer inspection of the remaining correlation and non-homogeneity of variance in the data. Three methods of modeling the correlation were compared. ^

Comparison of a traditional and a multilevel Cox Proportional Hazards model

Hierarchically clustered populations are often encountered in public health research, but the traditional methods used in analyzing this type of data are not always adequate. In the case of survival time data, more appropriate methods have only begun to surface in the last couple of decades. Such methods include multilevel statistical techniques which, although more complicated to implement than traditional methods, are more appropriate. ^ One population that is known to exhibit a hierarchical structure is that of patients who utilize the health care system of the Department of Veterans Affairs where patients are grouped not only by hospital, but also by geographic network (VISN). This project analyzes survival time data sets housed at the Houston Veterans Affairs Medical Center Research Department using two different Cox Proportional Hazards regression models, a traditional model and a multilevel model. VISNs that exhibit significantly higher or lower survival rates than the rest are identified separately for each model. ^ In this particular case, although there are differences in the results of the two models, it is not enough to warrant using the more complex multilevel technique. This is shown by the small estimates of variance associated with levels two and three in the multilevel Cox analysis. Much of the differences that are exhibited in identification of VISNs with high or low survival rates is attributable to computer hardware difficulties rather than to any significant improvements in the model. ^

The association of area socioeconomic status and cancer screening: A systematic review and multilevel study

Background. The gap between actual and ideal rates of routine cancer screening in the U.S., particularly for colorectal cancer screening (CRCS) (1;2), is responsible for an unnecessary burden of morbidity and mortality, particularly for disadvantaged groups. Knowledge about the effects of individual and area influences is being advanced by a growing body of research that has examined the association of area socioeconomic status (SES) and cancer screening after controlling for individual SES. The findings from this emerging and heterogeneous research in the cancer screening literature have been mixed. Moreover, multilevel studies in this area have not yet adequately explored the possibility of differential associations by population subgroup, despite some evidence suggesting gender-specific effects. ^ Objectives and methods. This dissertation reports on a systematic review of studies on the association of area SES and cancer screening and a multilevel study of the association between area SES and CRCS. The specific aims of the systematic review are to: (1) describe the study designs, constructs, methods, and measures; (2) describe the association of area SES and cancer screening; and (3) identify neglected areas of research. ^ The empiric study linked a pooled sample of respondents aged ≥50 years without a personal history of colorectal cancer from the 2003 and 2005 California Health Interview Surveys with a comprehensive set of census-tract level area SES measures from the 2000 U.S. Census. Two-level random intercept models were used to test 2 hypotheses: (1) area SES will be associated with adherence to two modalities of CRCS after controlling for individual SES; and (2) gender will moderate the relationship between area socioeconomic status and adherence to both modalities of CRCS. ^ Results. The systematic review identified 19 eligible studies that demonstrated variability in study designs, methods, constructs, and measures. The majority of tested associations were either not statistically significant or significant and in the positive direction, indicating that as area SES increased, the odds of CRCS increased. The multilevel study demonstrated that while multiple aspects of area SES were associated with CRCS after controlling for individual SES, associations differed by screening modality and in the case of endoscopy, they also differed by gender. ^ Conclusions. Conceptual and methodologic heterogeneity and weaknesses in the literature to date limit definitive conclusions about the underlying relationships between area SES and cancer screening. The multilevel study provided partial support for both hypotheses. Future research should continue to explore the role of gender as a moderating influence with the aim of identifying the mechanisms linking area SES and cancer prevention behaviors. ^

Single nucleotide polymorphisms (SNPs) associated with TGF-beta pathway and their significance in systemic sclerosis - A multilevel analysis

Systemic sclerosis (SSc) or Scleroderma is a complex disease and its etiopathogenesis remains unelucidated. Fibrosis in multiple organs is a key feature of SSc and studies have shown that transforming growth factor-β (TGF-β) pathway has a crucial role in fibrotic responses. For a complex disease such as SSc, expression quantitative trait loci (eQTL) analysis is a powerful tool for identifying genetic variations that affect expression of genes involved in this disease. In this study, a multilevel model is described to perform a multivariate eQTL for identifying genetic variation (SNPs) specifically associated with the expression of three members of TGF-β pathway, CTGF, SPARC and COL3A1. The uniqueness of this model is that all three genes were included in one model, rather than one gene being examined at a time. A protein might contribute to multiple pathways and this approach allows the identification of important genetic variations linked to multiple genes belonging to the same pathway. In this study, 29 SNPs were identified and 16 of them located in known genes. Exploring the roles of these genes in TGF-β regulation will help elucidate the etiology of SSc, which will in turn help to better manage this complex disease. ^

HPV vaccine coverage in Texas counties: An application of multilevel, small area estimation

Health departments, research institutions, policy-makers, and healthcare providers are often interested in knowing the health status of their clients/constituents. Without the resources, financially or administratively, to go out into the community and conduct health assessments directly, these entities frequently rely on data from population-based surveys to supply the information they need. Unfortunately, these surveys are ill-equipped for the job due to sample size and privacy concerns. Small area estimation (SAE) techniques have excellent potential in such circumstances, but have been underutilized in public health due to lack of awareness and confidence in applying its methods. The goal of this research is to make model-based SAE accessible to a broad readership using clear, example-based learning. Specifically, we applied the principles of multilevel, unit-level SAE to describe the geographic distribution of HPV vaccine coverage among females aged 11-26 in Texas.^ Multilevel (3 level: individual, county, public health region) random-intercept logit models of HPV vaccination (receipt of ≥ 1 dose Gardasil® ) were fit to data from the 2008 Behavioral Risk Factor Surveillance System (outcome and level 1 covariates) and a number of secondary sources (group-level covariates). Sampling weights were scaled (level 1) or constructed (levels 2 & 3), and incorporated at every level. Using the regression coefficients (and standard errors) from the final models, I simulated 10,000 datasets for each regression coefficient from the normal distribution and applied them to the logit model to estimate HPV vaccine coverage in each county and respective demographic subgroup. For simplicity, I only provide coverage estimates (and 95% confidence intervals) for counties.^ County-level coverage among females aged 11-17 varied from 6.8-29.0%. For females aged 18-26, coverage varied from 1.9%-23.8%. Aggregated to the state level, these values translate to indirect state estimates of 15.5% and 11.4%, respectively; both of which fall within the confidence intervals for the direct estimates of HPV vaccine coverage in Texas (Females 11-17: 17.7%, 95% CI: 13.6, 21.9; Females 18-26: 12.0%, 95% CI: 6.2, 17.7).^ Small area estimation has great potential for informing policy, program development and evaluation, and the provision of health services. Harnessing the flexibility of multilevel, unit-level SAE to estimate HPV vaccine coverage among females aged 11-26 in Texas counties, I have provided (1) practical guidance on how to conceptualize and conduct modelbased SAE, (2) a robust framework that can be applied to other health outcomes or geographic levels of aggregation, and (3) HPV vaccine coverage data that may inform the development of health education programs, the provision of health services, the planning of additional research studies, and the creation of local health policies.^

Bayesian estimation of multilevel item response model with missing data

This study proposed a novel statistical method that modeled the multiple outcomes and missing data process jointly using item response theory. This method follows the "intent-to-treat" principle in clinical trials and accounts for the correlation between outcomes and missing data process. This method may provide a good solution to chronic mental disorder study. ^ The simulation study demonstrated that if the true model is the proposed model with moderate or strong correlation, ignoring the within correlation may lead to overestimate of the treatment effect and result in more type I error than specified level. Even if the within correlation is small, the performance of proposed model is as good as naïve response model. Thus, the proposed model is robust for different correlation settings if the data is generated by the proposed model.^

Combined effects of CO2 and temperature on carbon uptake and partitioning by the marine diatoms Thalassiosira weissflogii and Dactyliosolen fragilissimus

Carbon uptake and partitioning of two globally abundant diatom species, Thalassiosira weissflogii and Dactyliosolen fragilissimus, was investigated in batch culture experiments under four conditions: ambient (15°C, 400 µatm), high CO2 (15°C, 1000 µatm), high temperature (20°C, 400 µatm), and combined (20°C, 1000 µatm). The experiments were run from exponential growth into the stationary phase (six days after nitrogen depletion), allowing us to track biogeochemical dynamics analogous to bloom situations in the ocean. Elevated CO2 had a fertilizing effect and enhanced uptake of dissolved inorganic carbon (DIC) by about 8% for T. weissflogii and by up to 39% for D. fragilissimus. This was also reflected in higher cell numbers, build-up of particulate and dissolved organic matter, and transparent exopolymer particles. The CO2 effects were most prominent in the stationary phase when nitrogen was depleted and CO2(aq) concentrations were low. This indicates that diatoms in the high CO2 treatments could take up more DIC until CO2 concentrations in seawater became so low that carbon limitation occurs. These results suggest that, contrary to common assumptions, diatoms could be highly sensitive to ongoing changes in oceanic carbonate chemistry, particularly under nutrient limitation. Warming from 15 to 20 °C had a stimulating effect on one species but acted as a stressor on the other species, highlighting the importance of species-specific physiological optima and temperature ranges in the response to ocean warming. Overall, these sensitivities to CO2 and temperature could have profound impacts on diatoms blooms and the biological pump.

Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.