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

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

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)

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

Non-Invasive Assessment of Endothelial Shear Stress in Myocardial Bridges Using Coronary Computed Tomography Angiography

Myocardial bridging (MB) is a segment of coronary arteries with an intramural course, typically spared from atherosclerosis, while the adjacent proximal segment is reported to be atherosclerosis-prone, a phenomenon contributed to local endothelial shear stress (ESS). We aimed to describe the ESS milieu in coronaries with MBs combining coronary computed tomography angiography with computational fluid dynamics and to investigate the association of atherosclerosis presence proximal to MBs with hemorheological characteristics. Patients (n = 36) were identified and 36 arteries with MBs (11 deep and 25 superficial) were analyzed. ESS did not fluctuate 5 mm proximally to MBs vs 5 mm within MBs (0.94 vs 1.06 Pa, p = .56). There was no difference when comparing ESS in the proximal versus mid versus distal MB segments (1.48 vs 1.37 vs 1.9 Pa, p = ns). In arteries with plaques (n = 12), no significant ESS variances were observed around the MB entrance, when analyzing all arteries (p = .81) and irrespective of morphological features of the bridged segment (deep MBs; p = .65, superficial MBs; p = .84). MBs are characterized by homogeneous, atheroprotective ESS, possibly explaining the absence of atherosclerosis within bridged segments. The interplay between ESS and atherosclerosis is potentially not different in arteries with MB compared with arteries without bridges