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Despite significant advances in digital pathology and automation sciences, current diagnostic practice for cancer detection primarily relies on a qualitative manual inspection of tissue architecture and cell and nuclear morphology in stained biopsies using low-magnification, two-dimensional (2D) brightfield microscopy. The efficacy of this process is limited by inter-operator variations in

Despite significant advances in digital pathology and automation sciences, current diagnostic practice for cancer detection primarily relies on a qualitative manual inspection of tissue architecture and cell and nuclear morphology in stained biopsies using low-magnification, two-dimensional (2D) brightfield microscopy. The efficacy of this process is limited by inter-operator variations in sample preparation and imaging, and by inter-observer variability in assessment. Over the past few decades, the predictive value quantitative morphology measurements derived from computerized analysis of micrographs has been compromised by the inability of 2D microscopy to capture information in the third dimension, and by the anisotropic spatial resolution inherent to conventional microscopy techniques that generate volumetric images by stacking 2D optical sections to approximate 3D. To gain insight into the analytical 3D nature of cells, this dissertation explores the application of a new technology for single-cell optical computed tomography (optical cell CT) that is a promising 3D tomographic imaging technique which uses visible light absorption to image stained cells individually with sub-micron, isotropic spatial resolution. This dissertation provides a scalable analytical framework to perform fully-automated 3D morphological analysis from transmission-mode optical cell CT images of hematoxylin-stained cells. The developed framework performs rapid and accurate quantification of 3D cell and nuclear morphology, facilitates assessment of morphological heterogeneity, and generates shape- and texture-based biosignatures predictive of the cell state. Custom 3D image segmentation methods were developed to precisely delineate volumes of interest (VOIs) from reconstructed cell images. Comparison with user-defined ground truth assessments yielded an average agreement (DICE coefficient) of 94% for the cell and its nucleus. Seventy nine biologically relevant morphological descriptors (features) were computed from the segmented VOIs, and statistical classification methods were implemented to determine the subset of features that best predicted cell health. The efficacy of our proposed framework was demonstrated on an in vitro model of multistep carcinogenesis in human Barrett's esophagus (BE) and classifier performance using our 3D morphometric analysis was compared against computerized analysis of 2D image slices that reflected conventional cytological observation. Our results enable sensitive and specific nuclear grade classification for early cancer diagnosis and underline the value of the approach as an objective adjunctive tool to better understand morphological changes associated with malignant transformation.
ContributorsNandakumar, Vivek (Author) / Meldrum, Deirdre R (Thesis advisor) / Nelson, Alan C. (Committee member) / Karam, Lina J (Committee member) / Ye, Jieping (Committee member) / Johnson, Roger H (Committee member) / Bussey, Kimberly J (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Due to heterogeneity at the cellular level, single cell analysis (SCA) has become a necessity to study cellomics for the early detection of diseases like cancer. Development of single cell manipulation systems is very critical for performing SCA. In this thesis, electrorotation (ROT) chips to trap and rotate single cells

Due to heterogeneity at the cellular level, single cell analysis (SCA) has become a necessity to study cellomics for the early detection of diseases like cancer. Development of single cell manipulation systems is very critical for performing SCA. In this thesis, electrorotation (ROT) chips to trap and rotate single cells using electrokinetic forces have been developed. The ROT chip mainly consists of a set of closely spaced metal electrodes (60µm interspacing between opposite electrodes) that forms a closed electric field cage (electrocage) when driven with high frequency AC voltages. Cells were flowed through a microchannel to the electrocage where they could be precisely trapped, levitated and rotated in 3-D along the axis of interest. The dielectrophoresis based ROT chip design and relevant electrokinetic effects have been simulated using COMSOL 3.4 to optimize the design parameters. Also, various semiconductor technology fabrication process steps have been developed and optimized for better yield and repeatability in the manufacture of the ROT chip. The ROT chip thus fabricated was used to characterize rotation of single cells with respect to the control parameters namely excitation voltage, frequency and cell line. The longevity of cell rotation under electric fields has been probed. Also, the Joule heating inside the ROT chip due to applied voltage has been characterized to know the thermal stress on the cells. The major advantages of the ROT chip developed are precise electrorotation of cells, simple design and straight forward fabrication process.
ContributorsSoundappa Elango, Iniyan (Author) / Meldrum, Deirdre R (Thesis advisor) / Christen, Jennifer Blain (Committee member) / Johnson, Roger H (Committee member) / Arizona State University (Publisher)
Created2012