Domain and Geometry Agnostic CNNs for Left Atrium Segmentation in 3D Ultrasound

Segmentation of the left atrium and deriving its size can help to predict and detect various cardiovascular conditions. Automation of this process in 3D Ultrasound image data is desirable, since manual delineations are time-consuming, challenging and observer-dependent. Convolutional neural networks have made improvements in computer vision and in medical image analysis. They have successfully been applied to segmentation tasks and were extended to work on volumetric data. In this paper we introduce a combined deep-learning based approach on volumetric segmentation in Ultrasound acquisitions with incorporation of prior knowledge about left atrial shape and imaging device. The results show, that including a shape prior helps the domain adaptation and the accuracy of segmentation is further increased with adversarial learning

Temporal and spatial dynamics of brain structure changes during extensive learning

The current view regarding human long-term memory as an active process of encoding and retrieval includes a highly specific learning-induced functional plasticity in a network of multiple memory systems. Voxel-based morphometry was used to detect possible structural brain changes associated with learning. Magnetic resonance images were obtained at three different time points while medical students learned for their medical examination. During the learning period, the gray matter increased significantly in the posterior and lateral parietal cortex bilaterally. These structural changes did not change significantly toward the third scan during the semester break 3 months after the exam. The posterior hippocampus showed a different pattern over time: the initial increase in gray matter during the learning period was even more pronounced toward the third time point. These results indicate that the acquisition of a great amount of highly abstract information may be related to a particular pattern of structural gray matter changes in particular brain areas

Premotor Gray Matter Volume is Associated with Clinical Findings in Idiopathic and Genetically Determined Parkinson’s Disease

In the present voxel-based morphometric study, we investigated whether the severity and duration of disease are associated with alterations in gray matter volume (GMV) in symptomatic Parkin mutation carriers (sPARKIN-MC) and patients with idiopathic Parkinson’s disease (iPD). Regression analyses revealed different negative correlations between GMV in cortical motor areas and the severity as well as the disease duration in sPARKIN-MC and iPD patients. SPARKIN-MC showed a less involvement of cortical motor areas, in particular in the supplementary motor area (SMA) than iPD patients. Specifically, in iPD patients, but not in sPARKIN-MC, there was a negative correlation between the SMA degeneration and the UPDRS-II item freezing. The different degeneration patterns may mirror diverse kinetics of the disease progress in these two groups of PD patients with different underlying etiologies

Reproducible resistive switching in nonvolatile organic memories

Resistive switching in nonvolatile, two terminal organic memories can be due to the presence of a native oxide layer at an aluminum electrode. Reproducible solid state memories can be realized by deliberately adding a thin sputtered Al2O3 layer to nominal electron-only, hole-only, and bipolar organic diodes. Before memory operation, the devices have to be formed at an electric field of 10(9) V/m, corresponding to soft breakdown of Al2O3. After forming, the structures show pronounced negative differential resistance and the local maximum in the current scales with the thickness of the oxide layer. The polymer acts as a current limiting series resistance

fMRI of reward processing in a community-based longitudinal study

Up to 40% of youth with autism spectrum disorder (ASD) also suffer from anxiety, and this comorbidity is linked with significant functional impairment. However, the mechanisms of this overlap are poorly understood. We investigated the interplay between ASD traits and anxiety during reward processing, known to be affected in ASD, in a community sample of 1472 adolescents (mean age=14.4 years) who performed a modified monetary incentive delay task as part of the Imagen project. Blood-oxygen-level dependent (BOLD) responses to reward anticipation and feedback were compared using a 2x2 analysis of variance test (ASD traits: low/high; anxiety symptoms: low/high), controlling for plausible covariates. In addition, we used a longitudinal design to assess whether neural responses during reward processing predicted anxiety at 2-year follow-up. High ASD traits were associated with reduced BOLD responses in dorsal prefrontal regions during reward anticipation and negative feedback. Participants with high anxiety symptoms showed increased lateral prefrontal responses during anticipation, but decreased responses following feedback. Interaction effects revealed that youth with combined ASD traits and anxiety, relative to other youth, showed high right insula activation when anticipating reward, and low right-sided caudate, putamen, medial and lateral prefrontal activations during negative feedback (all clusters PFWE<0.05). BOLD activation patterns in the right dorsal cingulate and right medial frontal gyrus predicted new-onset anxiety in participants with high but not low ASD traits. Our results reveal both quantitatively enhanced and qualitatively distinct neural correlates underlying the comorbidity between ASD traits and anxiety. Specific neural responses during reward processing may represent a risk factor for developing anxiety in ASD youth

More Intense Experiences, Less Intense Forecasts: Why People Overweight Probability Specifications in Affective Forecasts

We propose that affective forecasters overestimate the extent to which experienced hedonic responses to an outcome are influenced by the probability of its occurrence. The experience of an outcome (e.g., winning a gamble) is typically more affectively intense than the simulation of that outcome (e.g., imagining winning a gamble) upon which the affective forecast for it is based. We suggest that, as a result, experiencers allocate a larger share of their attention toward the outcome (e.g., winning the gamble) and less to its probability specifications than do affective forecasters. Consequently, hedonic responses to an outcome are less sensitive to its probability specifications than are affective forecasts for that outcome. The results of 6 experiments provide support for our theory. Affective forecasters overestimated how sensitive experiencers would be to the probability of positive and negative outcomes (Experiments 1 and 2). Consistent with our attentional account, differences in sensitivity to probability specifications disappeared when the attention of forecasters was diverted from probability specifications (Experiment 3) or when the attention of experiencers was drawn toward probability specifications (Experiment 4). Finally, differences in sensitivity to probability specifications between forecasters and experiencers were diminished when the forecasted outcome was more affectively intense (Experiments 5 and 6)

Low-dose CT from myocardial perfusion SPECT/CT allows the detection of anemia in preoperative patients

BACKGROUND To assess whether low-dose CT for attenuation correction of myocardial perfusion single-photon emission computed tomography (SPECT) allows for identification of anemic patients and grading anemia severity. METHODS AND RESULTS Patients who underwent a preoperative blood-test and low-dose CT scan, as a part of a cardiac SPECT exam, between 01 January 2015 and 31 December 2017 were enrolled in this retrospective study. Hemoglobin (Hb) levels and hematocrit were derived from clinical records. CT images were visually assessed (qualitative analysis) for the detection of inter-ventricular septum sign (IVSS) and aortic rim sign (ARS) and quantitative analysis were performed. The diagnostic accuracy for detecting anemia was compared using Hb values as the standard of reference. A total of 229 patients were included (110 with anemia; 57 mild; 46 moderate; 7 severe). The AUC of IVSS and ARS were 0.830 and 0.669, respectively (p<0.0001). The quantitative analysis outperformed ARS and IVSS; (AUC of 0.893, p=0.29). The optimal anemia cut-off using Youden index was 4.5 HU. CONCLUSION Quantitative analysis derived from low-dose CT images, as a part of cardiac SPECT exams, have a diagnostic accuracy similar to that of hematocrit for the detection of anemia and may allow discriminating different anemia severities

Clinical practice guidelines for laboratory diagnosis of epidermolysis bullosa

This guideline were initiated by DEBRA International; financial support was provided by DEBRA Austria. The generous assistance of Rebecca Bodan, Lisa Brains, Sharon Cassidy and Kelsey Townsend-Miller is gratefully acknowledged in providing patient or lay input into this guideline. The authors acknowledge the guidance of Kattya Mayre-Chilton (DEDRA International). Johann Bauer (Paracelsus University and EB House, Salzburg, Austria), Christine Bodemer (Hôpital Universitaire Necker, Paris, France), Judith Fischer (Institute of Human Genetics, University of Freiburg, Germany), Jemima Mellerio (St John's Institute of Dermatology, Guy's and St Thomas' NHS Foundation Trust, London, U.K.), Francis Palisson (Universidad del Desarrollo and DEBRA, Chile), Eli Sprecher (Department of Dermatology, Tel Aviv Sourasky Medical Center, Israel) and Jouni Uitto, Leila Youssefian and Hassan Vahidnezhad (all from the Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, PA, U.S.A.) are acknowledged as reviewers