Model-Based Shape and Motion Analysis: Left Ventricle of a Heart

The accurate and clinically useful estimation of the shape, motion, and deformation of the left ventricle of a heart (LV) is an important yet open research problem. Recently, computer vision techniques for reconstructing the 3-D shape and motion of the LV have been developed. The main drawback of these techniques, however, is that their models are formulated in terms of either too many local parameters that require non-trivial processing to be useful for close to real time diagnosis, or too few parameters to offer an adequate approximation to the LV motion. To address the problem, we present a new class of volumetric primitives for a compact and accurate LV shape representation in which model parameters are functions. Lagrangian dynamics are employed to convert geometric models into dynamic models that can deform according to the forces manifested in the data points. It is thus possible to make a precise estimation of the deformation of the LV shape endocardial, epicardial and anywhere in between with a small number of intuitive parameter functions. We believe that the proposed technique has a wide range of potential applications. In this thesis, we demonstrate the possibility by applying it to the 3-D LV shape and motion characterization from magnetic tagging data (MRI-SPAMM). We show that the results of our experiments with normal and abnormal heart data enable us to quantitatively verify the physicians\u27 qualitative conception of the left ventricular wall motion

Hybrid-Fusion Transformer for Multisequence MRI

Medical segmentation has grown exponentially through the advent of a fully convolutional network (FCN), and we have now reached a turning point through the success of Transformer. However, the different characteristics of the modality have not been fully integrated into Transformer for medical segmentation. In this work, we propose the novel hybrid fusion Transformer (HFTrans) for multisequence MRI image segmentation. We take advantage of the differences among multimodal MRI sequences and utilize the Transformer layers to integrate the features extracted from each modality as well as the features of the early fused modalities. We validate the effectiveness of our hybrid-fusion method in three-dimensional (3D) medical segmentation. Experiments on two public datasets, BraTS2020 and MRBrainS18, show that the proposed method outperforms previous state-of-the-art methods on the task of brain tumor segmentation and brain structure segmentation.Comment: 10 pages, 4 figure

Deformable Models with Parameter Functions: Application to Heart Wall Modeling

This paper develops a new class of physics-based deformable models which can deform both globally and locally. Their global parameters are functions allowing the definition of new parameterized primitives and parameterized global deformations. These new global parameter functions improve the accuracy of shape description through the use of a few intuitive parameters such as functional bending and twisting. Using a physics-based approach we convert these geometric models into deformable models that deform due to forces exerted from the datapoints so as to conform to the given dataset. We present an experiment involving the extraction of shape and motion of the Left Ventricle (LV) of a heart from MRI-SPAMM data based on a few global parameter functions

Model-based Analysis of Cardiac Motion from Tagged MRI Data

We develop a new method for analyzing the motion of the left ventricle (LV) of a heart from tagged MRI data. Our technique is based on the development of a new class of physics-based deformable models whose parameters are functions allowing the definition of new parameterized primitives and parameterized deformations. These parameter functions improve the accuracy of shape description through the use of a few intuitive parameters such as functional twisting. Furthermore, these parameters require no complex post-processing in order to be used by a physician. Using a physics-based approach, we convert these geometric models into deformable models that deform due to forces exerted from the datapoints and conform to the given dataset. We present experiments involving the extraction of shape and motion of the LV from MRI-SPAMM data based on a few parameter functions. Furthermore, by plotting the variations over time of the extracted model parameters from normal and abnormal heart data we are able to characterize quantitatively their differences

The Contribution of Posttraumatic Stress Disorder and Depression to Insomnia in North Korean Refugee Youth

Refugees are exposed to multiple traumatic and stressful events and thereby are at higher risk for developing a variety of psychological sequelae including posttraumatic stress disorder (PTSD). However, the relation of PTSD to other mental health conditions has not been fully revealed in refugee populations. The present study investigated relationships among trauma exposure, PTSD, depression, and insomnia in North Korean refugee youth. Seventy-four refugee youth were assessed for exposure to traumatic events, PTSD, depression, and insomnia symptoms. The results showed high rates of multiple trauma exposures among the refugee youth and high incidences of co-occurring symptoms of PTSD and insomnia in those who have multiple trauma. Furthermore, the overall symptoms and four cluster symptoms of PTSD were strongly correlated with insomnia in addition to depression. In the path model to predict insomnia, PTSD affected insomnia only through depression, indicating that the greater the levels of PTSD suffered, the greater the likelihood for developing sleep problems via depression. The present study indicates how sleep problems relate to trauma-related symptoms, i.e., PTSD and depression in refugee populations, and highlights the need for further investigation of the specific relation between sleep problems and trauma-related symptoms for effective evaluation and intervention

2-Cys Peroxiredoxins: Emerging Hubs Determining Redox Dependency of Mammalian Signaling Networks

Mammalian cells have a well-defined set of antioxidant enzymes, which includes superoxide dismutases, catalase, glutathione peroxidases, and peroxiredoxins. Peroxiredoxins are the most recently identified family of antioxidant enzymes that catalyze the reduction reaction of peroxides, such as H2O2. In particular, typical 2-Cys peroxiredoxins are the featured peroxidase enzymes that receive the electrons from NADPH by coupling with thioredoxin and thioredoxin reductase. These enzymes distribute throughout the cellular compartments and, therefore, are thought to be broad-range antioxidant defenders. However, recent evidence demonstrates that typical 2-Cys peroxiredoxins play key signal regulatory roles in the various signaling networks by interacting with or residing near a specific redox-sensitive molecule. These discoveries help reveal the redox signaling landscape in mammalian cells and may further provide a new paradigm of therapeutic approaches based on redox signaling

Ethanol and Reactive Species Increase Basal Sequence Heterogeneity of Hepatitis C Virus and Produce Variants with Reduced Susceptibility to Antivirals

Hepatitis C virus (HCV) exhibits a high level of genetic variability, and variants with reduced susceptibility to antivirals can occur even before treatment begins. In addition, alcohol decreases efficacy of antiviral therapy and increases sequence heterogeneity of HCV RNA but how ethanol affects HCV sequence is unknown. Ethanol metabolism and HCV infection increase the level of reactive species that can alter cell metabolism, modify signaling, and potentially act as mutagen to the viral RNA. Therefore, we investigated whether ethanol and reactive species affected the basal sequence variability of HCV RNA in hepatocytes. Human hepatoma cells supporting a continuous replication of genotype 1b HCV RNA (Con1, AJ242652) were exposed to ethanol, acetaldehyde, hydrogen peroxide, or L-buthionine-S,R-sulfoximine (BSO) that decreases intracellular glutathione as seen in patients. Then, NS5A region was sequenced and compared with genotype 1b HCV sequences in the database. Ethanol and BSO elevated nucleotide and amino acid substitution rates of HCV RNA by 4–18 folds within 48 hrs which were accompanied by oxidative RNA damage. Iron chelator and glutathione ester decreased both RNA damage and mutation rates. Furthermore, infectious HCV and HCV core gene were sufficient to induce oxidative RNA damage even in the absence of ethanol or BSO. Interestingly, the dn/ds ratio and percentage of sites undergoing positive selection increased with ethanol and BSO, resulting in an increased detection of NS5A variants with reduced susceptibility to interferon alpha, cyclosporine, and ribavirin and others implicated in immune tolerance and modulation of viral replication. Therefore, alcohol is likely to synergize with virus-induced oxidative/nitrosative stress to modulate the basal mutation rate of HCV. Positive selection induced by alcohol and reactive species may contribute to antiviral resistance