Volumetric cell imaging using 3D optical Computed Tomography (cell CT) is advantageous for identification and characterization of cancer cells. Many diseases arise from genomic changes, some of which are manifest at the cellular level in cytostructural and protein expression (functional) features which can be resolved, captured and quantified in 3D far more sensitively and specifically than in traditional 2D microscopy. Live single cells were rotated about an axis perpendicular to the optical axis to facilitate data acquisition for functional live cell CT imaging. The goal of this thesis research was to optimize and characterize the microvortex rotation chip. Initial efforts concentrated on optimizing the microfabrication process in terms of time (6-8 hours v/s 12-16 hours), yield (100% v/s 40-60%) and ease of repeatability. This was done using a tilted exposure lithography technique, as opposed to the backside diffuser photolithography (BDPL) method used previously (Myers 2012) (Chang and Yoon 2004). The fabrication parameters for the earlier BDPL technique were also optimized so as to improve its reliability. A new, PDMS to PDMS demolding process (soft lithography) was implemented, greatly improving flexibility in terms of demolding and improving the yield to 100%, up from 20-40%. A new pump and flow sensor assembly was specified, tested, procured and set up, allowing for both pressure-control and flow-control (feedback-control) modes; all the while retaining the best features of a previous, purpose-built pump assembly. Pilot experiments were performed to obtain the flow rate regime required for cell rotation. These experiments also allowed for the determination of optimal trapezoidal neck widths (opening to the main flow channel) to be used for cell rotation characterization. The optimal optical trap forces were experimentally estimated in order to minimize the required optical power incident on the cell. Finally, the relationships between (main channel) flow rates and cell rotation rates were quantified for different trapezoidal chamber dimensions, and at predetermined constant values of laser trapping strengths, allowing for parametric characterization of the system.

In the frenzy of next generation genetic sequencing and proteomics, single-cell level analysis has begun to find its place in the crux of personalized medicine and cancer research. Single live cell 3D imaging technology is one of the most useful ways of providing spatial and morphological details inside living single cells. It provides a window to uncover the mysteries of protein structure and folding, as well as genetic expression over time, which will tremendously improve the state of the fields of biophysics and biomedical research. This thesis project specifically demonstrates a method for live single cell rotation required to image them in the single live cell CT imaging platform. The method of rotation proposed in this thesis uses dynamic optical traps generated by a phase-only spatial light modulator (SLM) to exert torque on a single mammalian cell. Laser patterns carrying the holographic information of the traps are delivered from the SLM through a transformation telescope into the objective lens and onto its focal plane to produce the desired optical trap "image". The phase information in the laser patterns being delivered are continuously altered by the SLM such that the structure of the wavefront produces two foci at opposite edges of the cell of interest that each moves along the circumference of the cell in opposite axial directions. Momentum generated by the motion of the foci exerts a torque on the cell, causing it to rotate. The viability of this method was demonstrated experimentally. Software was written using LabVIEW to control the display panel of the SLM.

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.

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.