Integration Of Hyperspectral Imaging System For Optimized Data Acquisition And Control To Revolutionized Pathology Applications

Detecting and measuring the interactions and expression levels of tumor markers in a cancerous cell are quintessential in prognosis and management of cancer. These have propagated the need to develop better microscopic imaging techniques to understand the cellular structure and its functional behavior. Pathologist use techniques such immunohistochemistry and in situ hybridization to measure and detect these tumor marker expression levels. Fluorophores are used in these techniques as fluorescent tags to identify the tumor markers. These fluorophores have unique absorption and emission spectrum, making them useful to not only identify but also quantify the concentration levels of these markers. This allows us to tag multiple fluorophores within a single cell. Although useful it is limited by the ability to resolve the overlapping emission spectra of multiplexed fluorophores. This limits the total number of fluorophores that can be used to identify different components within a single cell. Hyperspectral imaging used in astronomy for remote sensing of earth collects contiguous band of wavelengths over each pixel in image. This ability to provide spectral signatures associated with spatial resolution can be used to deconvolve the overlapping spectra of multiplexed fluorophores. This can be achieved by matching the standard emission spectrum of each multiplexed fluorophore with spectra at each pixel in image. This enables to not only deconvolve the fluorophores but also quantify the contribution of each fluorophore at any pixel in an image. At the center of hyperspectral imaging system is a microscope coupled with an imaging spectrograph to disperse the incoming light into its components, a CCD camera focused at exit port of an imaging spectrograph is used to record the information and a stage motor positioned onto microscope helps to move the sample across the optical path to cover the entire region of interest. This propels the need to precisely control the major components of the hyperspectral imaging system through application software to provide high resolution data. This software also needed to provide a dynamic user interface along with complete automated control over all these components to emulate actions of a trained microscope operator thus making it commercially viable and ready to transition into a pathology lab.This thesis works describes the integration of such a hyperspectral imaging system to provide a complete automated control and data acquisition software named Xanoscope®. It validates the features and functionality of Xanoscope by comparing it against the specifications from individual hardware components. It further demonstrates that the Xanoscope® can repetitively used to identify and quantify the expression levels of up to 10 fluorophores conjugated to tumor markers of breast cancer cell lines as well as samples from breast cancer patients along with normal cells. Xanoscope® thus aids to revolutionize the diagnoses and monitoring of cancer and its response to therapeutic regimes.