Session E2: Interdisciplinary Condensed Matter

Analysis of Image Segmentation Algorithms for Auto-Contouring of Kidney Lesions in Adaptive Radiotherapy

In external beam radiotherapy, planning images are acquired and a treatment plan is composed at the time of diagnosis. However, when the first dose fraction is administered weeks later, patient anatomy typically differs significantly. Adaptive radiotherapy (ART) is a developing modality in which updated images are acquired on the day of treatment and new contours are established. Manual intervention is typically not feasible during ART, due to time constraints, and lesion identification must be automated. Image segmentation, a common tool in computer vision applications, has been applied to auto-contouring in recent years. This study examined the optimization of parameters used in various automated organ contouring algorithms. Several edge detection techniques were investigated as applied to segmentation of cross-sectional CT images. The accuracy of organ delineation was quantified using the Pearson Correlation Coefficient and compared to manually-contoured regions of interest in order to quantitatively assess their accuracy. Auto-segmentation results will be presented using the Roberts, Canny, Prewitt, and Sobel techniques. These algorithms will be compared and evaluated, based on their performance in identifying the kidneys and malignant lesions present in neighboring anatomical regions. Results will be presented and analyzed for both kilovoltage CT and cone-beam CT. The applicability of this technique to ART will be discussed.   

Computational model of mechanical forces effects on epithelial cell proliferation

Epithelia are sheets of cells that line the surfaces of organs and carry out important functional and structural roles for the multicellular organisms, including as barriers protecting internal cells from mechanical damage or infection. Understanding the regulation of epithelial cell mechanics is critical in defining the underlying basis of cancer development as well as for wound healing. In computational models, cells are typically approximated as polygons to simplify computation efforts, often resulting in incomplete descriptions of many morphogenetic processes including mitotic rounding during cellular division. Here we have developed a cell-based subcellular element (SCE) computational model implemented on high performance Graphical Processing Units (GPUs) clusters. The model represents mechanical properties of both the internal cytoplasm and outer membrane with subcellular nodes. The numerical results are compared with experimental data obtained from developing Drosophila wing imaginal discs, a genetic model system used to investigate the regulation of epithelial tissue growth. This work provides a computational framework that can be extended toward investigation the underlying mechanics of tissue size control at unprecedented levels of geometric detail.   

Effects of nanoparticle size on mechanisms of Cd sorption to hematite

Hematite nanoparticles (NPs) are ubiquitous in soil and have high sorption capacities for cationic and anionic contaminants. We investigate the effects of hematite NP size (8 nm and 40 nm) on sorption mechanisms of cadmium. Because 8 and 40 nm hematite NPs have substantially different specific surface areas, experiments were run in two ways: normalized to NP mass (MN) or to total NP surface area (SAN). Cd (II) sorption increased as the particle size was decreased with increasing pH environment. X ray absorption spectroscopy (XAS) results suggested Cd was adsorbed to 8nm particles at pH 7.5 but did not form a precipitate whereas at pH 9, minor amounts of Cd precipitation was present. In SAN experiments, particle size did not substantially affect the sorption mechanism of 40 nm NPs at pH 7.5 whereas Cd precipitate dominated at pH 9. In MN experiments, Cd precipitation dominated in 40 nm NPs at both pH values. In conclusion, NP size affects both the extent and mechanism of Cd sorption on hematite NPs and attention must be paid for differences in NP mineral surface area in experimental design. .   

Parameterization of lattice spacings for lipid multilayers in lithium salts

Lipids, which are molecules found in biological cells, form highly regular layered structures called multilamellar lipid vesicles (MLVs). The repeat lattice spacings of MLVs depend on van der Waals and electrostatic forces between neighboring membranes and are sensitive to the presence of salt. For example, addition of salt ions such as sodium and potassium makes the MLVs swell, primarily due to changes in electrical polarizabilities. However, a more complicated behavior is found in the presence of lithium ions. Using x-ray scattering, we show experimentally how the interactions between membranes depend on the type of monovalent ions and construct parameterizations of MLVs swelling curves that can help analyze van der Waals interactions.   

First-Principles Study of Photocatalytic Activation of CO$_{\mathrm{2}}$ on Graphene-Semiconductor Heterostructures

The effective capture and conversion of solar energy is of critical importance for sustainable energy development. Photocatalysts are a key component in harnessing solar energy and facilitating chemical reactions to produce high-energy content chemicals. It has been reported recently that by adding graphene to semiconductor nanostructures to form composites, their photocatalytic activities can be significantly enhanced. In this work, we investigate the adsorption and initial activation of CO$_{\mathrm{2}}$ on free-standing ZnO nanoclusters, and ZnO nanoclusters supported on graphene using the first-principles approach. A variety of binding configurations of CO$_{\mathrm{2}}$ on different binding sites on ZnO and the activation of CO$_{\mathrm{2}}$ will be presented and the effect of the substrate graphene will be discussed.