Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks

Extent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of residual tumor from post-operative MR images is essential. The current standard method for estimating it is subject to high inter- and intra-rater variability, and an automated method for segmentation of residual tumor in early post-operative MRI could lead to a more accurate estimation of extent of resection. In this study, two state-of-the-art neural network architectures for pre-operative segmentation were trained for the task. The models were extensively validated on a multicenter dataset with nearly 1000 patients, from 12 hospitals in Europe and the United States. The best performance achieved was a 61% Dice score, and the best classification performance was about 80% balanced accuracy, with a demonstrated ability to generalize across hospitals. In addition, the segmentation performance of the best models was on par with human expert raters. The predicted segmentations can be used to accurately classify the patients into those with residual tumor, and those with gross total resection

Reliability of Eye Tracking and Pupillometry Measures in Individuals with Fragile X Syndrome

Recent insight into the underlying molecular and cellular mechanisms of fragile X syndrome (FXS) has led to the proposal and development of new pharmaceutical treatment strategies, and the initiation of clinical trials aimed at correcting core symptoms of the developmental disorder. Consequently, there is an urgent and critical need for outcome measures that are valid for quantifying specific symptoms of FXS and that are consistent across time. We used eye tracking to evaluate test–retest reliability of gaze and pupillometry measures in individuals with FXS and we demonstrate that these measures are viable options for assessing treatment-specific outcomes related to a core behavioral feature of the disorder

Monoculture of Leafcutter Ant Gardens

Background -- Leafcutter ants depend on the cultivation of symbiotic Attamyces fungi for food, which are thought to be grown by the ants in single-strain, clonal monoculture throughout the hundreds to thousands of gardens within a leafcutter nest. Monoculture eliminates cultivar-cultivar competition that would select for competitive fungal traits that are detrimental to the ants, whereas polyculture of several fungi could increase nutritional diversity and disease resistance of genetically variable gardens. Methodology/Principal Findings -- Using three experimental approaches, we assessed cultivar diversity within nests of Atta leafcutter ants, which are most likely among all fungus-growing ants to cultivate distinct cultivar genotypes per nest because of the nests' enormous sizes (up to 5000 gardens) and extended lifespans (10–20 years). In Atta texana and in A. cephalotes, we resampled nests over a 5-year period to test for persistence of resident cultivar genotypes within each nest, and we tested for genetic differences between fungi from different nest sectors accessed through excavation. In A. texana, we also determined the number of Attamyces cells carried as a starter inoculum by a dispersing queens (minimally several thousand Attamyces cells), and we tested for genetic differences between Attamyces carried by sister queens dispersing from the same nest. Except for mutational variation arising during clonal Attamyces propagation, DNA fingerprinting revealed no evidence for fungal polyculture and no genotype turnover during the 5-year surveys. Conclusions/Significance -- Atta leafcutter ants can achieve stable, fungal monoculture over many years. Mutational variation emerging within an Attamyces monoculture could provide genetic diversity for symbiont choice (gardening biases of the ants favoring specific mutational variants), an analog of artificial selection.The research was supported by National Science Foundation awards DEB-0920138, DEB-0639879, and DEB-0110073 to UGM; DEB-0949689 to T.R. Schultz, N. Mehdiabadi, and UGM; and a Fellowship (02/05) from the Conselho Nacional de Desenvolvimento Científico e Tecnológico to AR. The funding agencies had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o

Assessing ADHD symptoms in children and adults:Evaluating the role of objective measures

Background: Diagnostic guidelines recommend using a variety of methods to assess and diagnose ADHD. Applying subjective measures always incorporates risks such as informant biases or large differences between ratings obtained from diverse sources. Furthermore, it has been demonstrated that ratings and tests seem to assess somewhat different constructs. The use of objective measures might thus yield valuable information for diagnosing ADHD. This study aims at evaluating the role of objective measures when trying to distinguish between individuals with ADHD and controls. Our sample consisted of children (n = 60) and adults (n = 76) diagnosed with ADHD and matched controls who completed self- and observer ratings as well as objective tasks. Diagnosis was primarily based on clinical interviews. A popular pattern recognition approach, support vector machines, was used to predict the diagnosis. Results: We observed relatively high accuracy of 79% (adults) and 78% (children) applying solely objective measures. Predicting an ADHD diagnosis using both subjective and objective measures exceeded the accuracy of objective measures for both adults (89.5%) and children (86.7%), with the subjective variables proving to be the most relevant. Conclusions: We argue that objective measures are more robust against rater bias and errors inherent in subjective measures and may be more replicable. Considering the high accuracy of objective measures only, we found in our study, we think that they should be incorporated in diagnostic procedures for assessing ADHD

Different patient subgroup, different ranking? Which quality indicators do patients find important when choosing a hospital for hip- or knee arthroplasty?

<p>Abstract</p> <p>Background</p> <p>Patients are increasingly expected to become active, critical consumers in healthcare. They can use comparative healthcare information presented on websites to make informed choices for healthcare providers. However, the use of this information has been limited so far. An obstacle can be that the information is not perceived as relevant by patients. Presenting only the most important quality indicators might improve the usefulness of this information. The aim of this study was to explore which quality indicators different subgroups of patients find important when choosing a hospital for total hip arthroplasty (THA) or total knee arthroplasty (TKA).</p> <p>Methods</p> <p>In this explorative, cross-sectional study, questionnaires were distributed to 265 patients who underwent or had to undergo THA/TKA. Participants were asked to rank the importance of three types of quality indicators: patient experience indicators, clinical performance indicators, and indicators about hospital services. We used random effects regression analyses to assess the relative importance of the indicators in different subgroups of patients.</p> <p>Results</p> <p>110 patients (response rate 41.5%) who underwent or had to undergo THA/TKA participated. Conduct of doctors, the presence of procedures to prevent adverse effects of thrombosis and information about the specialist area of orthopaedists were the most important patient experience indicator, clinical performance indicator and indicator about hospital services, respectively. We found a few differences between patient subgroups in the importance attached to the quality indicators.</p> <p>Conclusions</p> <p>This study provides a first insight into which quality indicators patients find important when choosing a hospital for THA/TKA, and shows that subgroups of patients differ in the value they attach to these indicators. More extended research is needed to establish the indicators that should at least be presented in succinct overviews of comparative healthcare information for patients choosing a hospital for THA/TKA.</p

Flanker performance in female college students with ADHD: a diffusion model analysis

Attention-deficit hyperactivity disorder (ADHD) is characterized by poor adaptation to environmental demands, which leads to various everyday life problems. The present study had four aims: (1) to compare performance in a flanker task in female college students with and without ADHD (N = 39) in a classical analyses of reaction time and error rate and studying the underlying processes using a diffusion model, (2) to compare the amount of focused attention, (3) to explore the adaptation of focused attention, and (4) to relate adaptation to psychological functioning. The study followed a 2-between (group: ADHD vs. control) × 2-within (flanker conflict: incongruent vs. congruent) × 2-within (conflict frequency: 20 vs. 80 %) design. Compared to a control group, the ADHD group displayed prolonged response times accompanied by fewer errors in a flanker task. Results from the diffusion model analyses revealed that the members of the ADHD group showed deficits in non-decisional processes (i.e., higher non-decision time) and leaned more toward accuracy than participants without ADHD (i.e., setting higher boundaries). The ADHD group showed a more focused attention and less adaptation to the task conditions which is related to psychological functioning. Deficient non-decisional processes and poor adaptation are in line with theories of ADHD and presumably typical for the ADHD population, although this has not been shown using a diffusion model. However, we assume that the cautious strategy of trading speed of for accuracy is specific to the subgroup of female college students with ADHD and might be interpreted as a compensation mechanism