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Master Thesis Defense

Master Thesis Defense

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  • M.S Thesis Defense 24 th November 2008 Dipen Rana Graduate Student Translational Research, Garner Lab UT Southwestern Medical Center at Dallas Integration of Hyperspectral Imaging Microscopy for Pathology Applications
  • Outline
  • Reasons for using optical imaging in Medical Diagnostics
    • Every material responds uniquely to light at different wavelengths, emitting a unique spectrum permitting simultaneous detection of multiple targets in a single cell
    • Optical imaging is non-destructive, non-ionizing, responsive in real time, and rich in information.
    Action at Cellular Level Cellular Interactions Non -destructive Changes at cellular level occur well before anatomic changes Generates the need to study structural and functional state of individual cells
  • Fluorescence: The Basic Principle 1= absorbance of light (excitation) 2= vibrational relaxation (stokes shift ) 3= emission of light http://www.olympusmicro.com/primer/techniques/fluorescence/introduction.html; invitrogen Interactions of molecules with light
    • Fluorophores - a fluorescent compound used as a dye to mark protein with a fluorescent label.
    Fluorophores – Cell Labeling
  • Fluorophores – Cell Labeling
  • Fluorophores – Cell Labeling
    • Advantages
    • Highly specific in attachment
    • High quantum yield: ratio of photon absorption to emission
    • Unique spectrum
    • Quantitative measurements
    • pH insensitive
    • Wide color selection
    • Fluorophores - a fluorescent compound used as a dye to mark protein with a fluorescent label.
    Fluorophores – Cell Labeling
  • Imaging with fluorophores- A pathology perspective
    • Highly specific in target attachment
    • Every fluorophore has a unique emission spectrum
    • Targeting multiple cellular components
    • High sensitivity
    • Number of fluorophores that can be simultaneously used is limited by ability to resolve them
    • Need to unmix overlapping spectra of fluorophores within each pixel of an image
    • Selecting appropriate absorption and emission band for simultaneous viewing of multiple fluorophores
    Multi- Color Labeling Obstacles
  • Multispectral Imaging
    • Basic Idea:
    • Collect an image at two or few more spectral bands
    • Perform a computation at each pixel to identify individual components
    • Inability to generate images over continuous band of wavelengths
    True, Lawrence et al., Quantum Dots for Molecular Pathology
  • Hyperspectral Imaging: Voluminous data!
    • The Hyperspectral imaging system collects light waves over contiguous band of wavelengths for each pixel in an image
    photometrics
        • Hyperspectral Imaging: Voluminous data!
    • The Hyperspectral imaging system collects light waves over contiguous band of wavelengths for each pixel in an image
  • Hyperspectral Imaging Microscopy (HMI) System Workstation Overview
  • Outline
  • Hypothesis for Integration of Hyperspectral Imaging Microscopy System
    • We hypothesize that pathology can be revolutionized through development of a highly robust and dynamic data acquisition and control system that can be transitioned to a pathology lab
    • It can be used to identify and measure the expression levels of highly multiplexed fluorophores within a single cell
  • Outline
  • Hyperspectral Imaging Microscopy System
  • System specifications for visible range
    • Olympus IX70 Epi- fluorescence inverted microscope
    • U-MWU Filter Cube – absorption – 300-385nm emission > 420nm
    • Spectra Pro500i imaging spectrograph with 50groves/mm grating and center wavelength of 600nm for applications in range of 400-800nm
    • Quantix1602E CCD camera with 1536X1024 pixel array, 9X9 μ m pixel size and 12 bit @ 5 MHz digitization
    • Ludl electronics micro-mover stage with maximum speed of up to 30mm/sec
  • Hyperspectral data cube provides 3 dimensional data Collecting a stack of Y- λ images by moving the stage incrementally in X direction creates a 3 dimensional “hyperspectral data cube”
  • Efficiency of Camera and spectrograph for generating high resolution hyperspectral data Slit Width
  • Specifications of a data acquisition for HMI system
    • Highly dynamic process
    • Fast data acquisition system for collecting contiguous band of wavelengths at each pixel
    • Dynamic control over CCD camera to reproduce nearly true one to one representation of microscope image
    • High precision movement control over stage to avoid overlapping of images
    • Preserve the large amount of raw data files and track it changes
  • Outline
  • Xanoscope: The Hyperspectral Imaging microscopy system
    • Xanoscope® is the brand name of the data acquisition and control system that provides complete automated control over hyperspectral imaging microscopy
    • Xanoscope is build using MFC and VC++ of Visual Studio Package
  • Architecture of Xanoscope
  • Initializing Xanoscope with default or last saved parameters
  • Adjusting the parameters of individual components for dynamic control
  • Dynamic control over CCD camera
    • Exposure time - amount of light incident on CCD
    • Gain - magnitude of amplification a given system will produce
    • Exposure mode - how each exposure takes place
    • Clear cycles - how many time CCD is cleaned before each exposure
  • Controlling resolution to improve SNR and frame readout speed
  • Controlling resolution to improve SNR and frame readout speed 1X1 binning 1536X1024 pixels 2X2 binning 768X512 pixels 2X2 SNR = 4* Signal/ sqrt(4*Noise) = 2 [Signal/sqrt(Noise)] 1X1 SNR = Signal/ sqrt(Noise)
  • Custom settings for scan parameters
  • Sample scan preview along with scan information & Image Intensity values for quick reference
  • Sample scan preview along with scan information & Image Intensity values for quick reference
  • Saving the raw data files at user defined location for further analysis Raw data files are in binary format
  • Composite hyperspectral image cube build using raw data files along with quick analysis from composite image
  • Point spectrum and row spectrum for quick review of composite images
  • Outline
  • Determination of Spatial Resolution of Xanoscope images
  • Fast and Furious: 40 images in ~ 3minute for a 3sec exposure
    • Xanoscope uses VARIABLE TIMED and High gain and stage speed which helped reduce a prior typical scan time of ~47 minutes to mere ~3 minutes.
  • Validating CCD linearity for quantitative measurements made using Xanoscope
  • Validating the gain settings for Xanoscope
  • Validating accumulations used in Xanoscope for improving Signal to noise ratio in low light imaging
  • Validating accumulations used in Xanoscope for improving Signal to noise ratio in low light imaging mimicking smoothness First image with low SNR ratio Accumulated images with smoothness effect
  • High precision control over stage to avoid overlapping of images 1 2 3 4 5 Image is captured at 80µm slit width and 40X objective lens Minimum stage step resolution= 0.2µm Total number steps moved for each image= (80/40)/0.2= 10 steps Total number steps moved for 5 images = 50 steps = 50 * 0.2 =10 μ m each division = 10µm
  • Performance Evaluation of Xanoscope by scanning 10 multiplexed fluorophores in different cell lines Samples provided by Uhr lab at Cancer immunobiology center, UTSW MCF7 – breast cancer Daudi- Human Burkitt's lymphoma cell line TP – patient breast cancer cells Normal breast cells from breast cancer reduction
  • Linear unmixing of multiplexed fluorophores to measure its individual contribution …………………………………………………… .2
  • Analysis of multiplexed fluorophores by linear unmixing of its overlapping spectra Standard emission spectrum of 10 fluorophores Contributions of each fluorophore at a pixel in an image
  • Visualization of individual contribution of 10 fluorophore-antibody conjugates in cell lines & touch preps
  • Statistical analysis of individual contribution of 10 fluorophore-antibody conjugates in cell lines & touch preps
  • Summary
    • Integration of hyperspectral imaging microscopy system for dynamic and optimized data acquisition and control
    • Validated the software components in Xanoscope for quantitative and qualitative measurements
    • Xanoscope allows fast data acquisition with non-overlapping high resolution images reducing manpower time for pathologists and technicians in the laboratory and is at the same time cost-saving
  • Future Work
    • Increase the number of multiplexed fluorophores that can be scanned in a single-pass
    • Provide morphological measurements to better selection and analysis of multiple cells
    • Develop Xanoscope to further provide digital staining of unstained tissue sample using spectral signatures
    • All these data and its analysis can be accessed online at http://discovery.swmed.edu/xanapath/
  • Acknowledgements
    • Garner Lab : Committee members
    • Dr. Harold “Skip” Garner – Mentor Dr.Hanli Liu
    • Dr. Michael Huebschman- Co-Mentor Dr. George Alexandrakis
    • Sashidhar Katari
    • Alice Lin
    • Kenny Long
    • Dr.Wayne Fisher
    • Linda Gunn
    • Kay Emerson
    • David Trusty
    • Johny Sun
    • All Garner lab memebers and friends at UTA
    • Collaborator : (Cancer Immunobiology center, UTSW)
    • Dr. Jonathan Uhr
    • Nancy Lane
    • Huaying Liu
  •