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Master Thesis Defense

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  1. 1. 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
  2. 2. Outline
  3. 3. Reasons for using optical imaging in Medical Diagnostics <ul><li> </li></ul><ul><li>Every material responds uniquely to light at different wavelengths, emitting a unique spectrum permitting simultaneous detection of multiple targets in a single cell </li></ul><ul><li>Optical imaging is non-destructive, non-ionizing, responsive in real time, and rich in information. </li></ul>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
  4. 4. 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
  5. 5. <ul><li>Fluorophores - a fluorescent compound used as a dye to mark protein with a fluorescent label. </li></ul>Fluorophores – Cell Labeling
  6. 6. Fluorophores – Cell Labeling
  7. 7. Fluorophores – Cell Labeling
  8. 8. <ul><li>Advantages </li></ul><ul><li>Highly specific in attachment </li></ul><ul><li>High quantum yield: ratio of photon absorption to emission </li></ul><ul><li>Unique spectrum </li></ul><ul><li>Quantitative measurements </li></ul><ul><li>pH insensitive </li></ul><ul><li>Wide color selection </li></ul><ul><li>Fluorophores - a fluorescent compound used as a dye to mark protein with a fluorescent label. </li></ul>Fluorophores – Cell Labeling
  9. 9. Imaging with fluorophores- A pathology perspective <ul><li>Highly specific in target attachment </li></ul><ul><li>Every fluorophore has a unique emission spectrum </li></ul><ul><li>Targeting multiple cellular components </li></ul><ul><li>High sensitivity </li></ul><ul><li>Number of fluorophores that can be simultaneously used is limited by ability to resolve them </li></ul><ul><li>Need to unmix overlapping spectra of fluorophores within each pixel of an image </li></ul><ul><li>Selecting appropriate absorption and emission band for simultaneous viewing of multiple fluorophores </li></ul>Multi- Color Labeling Obstacles
  10. 10. Multispectral Imaging <ul><li>Basic Idea: </li></ul><ul><li>Collect an image at two or few more spectral bands </li></ul><ul><li>Perform a computation at each pixel to identify individual components </li></ul><ul><li>Inability to generate images over continuous band of wavelengths </li></ul>True, Lawrence et al., Quantum Dots for Molecular Pathology
  11. 11. Hyperspectral Imaging: Voluminous data! <ul><li>The Hyperspectral imaging system collects light waves over contiguous band of wavelengths for each pixel in an image </li></ul>photometrics
  12. 12. <ul><ul><ul><li>Hyperspectral Imaging: Voluminous data! </li></ul></ul></ul><ul><li>The Hyperspectral imaging system collects light waves over contiguous band of wavelengths for each pixel in an image </li></ul>
  13. 13. Hyperspectral Imaging Microscopy (HMI) System Workstation Overview
  14. 14. Outline
  15. 15. Hypothesis for Integration of Hyperspectral Imaging Microscopy System <ul><li>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 </li></ul><ul><li>It can be used to identify and measure the expression levels of highly multiplexed fluorophores within a single cell </li></ul>
  16. 16. Outline
  17. 17. Hyperspectral Imaging Microscopy System
  18. 18. System specifications for visible range <ul><li>Olympus IX70 Epi- fluorescence inverted microscope </li></ul><ul><li>U-MWU Filter Cube – absorption – 300-385nm emission > 420nm </li></ul><ul><li>Spectra Pro500i imaging spectrograph with 50groves/mm grating and center wavelength of 600nm for applications in range of 400-800nm </li></ul><ul><li>Quantix1602E CCD camera with 1536X1024 pixel array, 9X9 μ m pixel size and 12 bit @ 5 MHz digitization </li></ul><ul><li>Ludl electronics micro-mover stage with maximum speed of up to 30mm/sec </li></ul>
  19. 19. 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”
  20. 20. Efficiency of Camera and spectrograph for generating high resolution hyperspectral data Slit Width
  21. 21. Specifications of a data acquisition for HMI system <ul><li>Highly dynamic process </li></ul><ul><li>Fast data acquisition system for collecting contiguous band of wavelengths at each pixel </li></ul><ul><li>Dynamic control over CCD camera to reproduce nearly true one to one representation of microscope image </li></ul><ul><li>High precision movement control over stage to avoid overlapping of images </li></ul><ul><li>Preserve the large amount of raw data files and track it changes </li></ul>
  22. 22. Outline
  23. 23. Xanoscope: The Hyperspectral Imaging microscopy system <ul><li>Xanoscope® is the brand name of the data acquisition and control system that provides complete automated control over hyperspectral imaging microscopy </li></ul><ul><li>Xanoscope is build using MFC and VC++ of Visual Studio Package </li></ul>
  24. 24. Architecture of Xanoscope
  25. 25. Initializing Xanoscope with default or last saved parameters
  26. 26. Adjusting the parameters of individual components for dynamic control
  27. 27. Dynamic control over CCD camera <ul><li>Exposure time - amount of light incident on CCD </li></ul><ul><li>Gain - magnitude of amplification a given system will produce </li></ul><ul><li>Exposure mode - how each exposure takes place </li></ul><ul><li>Clear cycles - how many time CCD is cleaned before each exposure </li></ul>
  28. 28. Controlling resolution to improve SNR and frame readout speed
  29. 29. 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)
  30. 30. Custom settings for scan parameters
  31. 31. Sample scan preview along with scan information & Image Intensity values for quick reference
  32. 32. Sample scan preview along with scan information & Image Intensity values for quick reference
  33. 33. Saving the raw data files at user defined location for further analysis Raw data files are in binary format
  34. 34. Composite hyperspectral image cube build using raw data files along with quick analysis from composite image
  35. 35. Point spectrum and row spectrum for quick review of composite images
  36. 36. Outline
  37. 37. Determination of Spatial Resolution of Xanoscope images
  38. 38. Fast and Furious: 40 images in ~ 3minute for a 3sec exposure <ul><li>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. </li></ul>
  39. 39. Validating CCD linearity for quantitative measurements made using Xanoscope
  40. 40. Validating the gain settings for Xanoscope
  41. 41. Validating accumulations used in Xanoscope for improving Signal to noise ratio in low light imaging
  42. 42. 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
  43. 43. 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
  44. 44. 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
  45. 45. Linear unmixing of multiplexed fluorophores to measure its individual contribution …………………………………………………… .2
  46. 46. 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
  47. 47. Visualization of individual contribution of 10 fluorophore-antibody conjugates in cell lines & touch preps
  48. 48. Statistical analysis of individual contribution of 10 fluorophore-antibody conjugates in cell lines & touch preps
  49. 49. Summary <ul><li>Integration of hyperspectral imaging microscopy system for dynamic and optimized data acquisition and control </li></ul><ul><li>Validated the software components in Xanoscope for quantitative and qualitative measurements </li></ul><ul><li>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 </li></ul>
  50. 50. Future Work <ul><li>Increase the number of multiplexed fluorophores that can be scanned in a single-pass </li></ul><ul><li>Provide morphological measurements to better selection and analysis of multiple cells </li></ul><ul><li>Develop Xanoscope to further provide digital staining of unstained tissue sample using spectral signatures </li></ul><ul><li>All these data and its analysis can be accessed online at http://discovery.swmed.edu/xanapath/ </li></ul>
  51. 51. Acknowledgements <ul><li>Garner Lab : Committee members </li></ul><ul><li>Dr. Harold “Skip” Garner – Mentor Dr.Hanli Liu </li></ul><ul><li>Dr. Michael Huebschman- Co-Mentor Dr. George Alexandrakis </li></ul><ul><li>Sashidhar Katari </li></ul><ul><li>Alice Lin </li></ul><ul><li>Kenny Long </li></ul><ul><li>Dr.Wayne Fisher </li></ul><ul><li>Linda Gunn </li></ul><ul><li>Kay Emerson </li></ul><ul><li>David Trusty </li></ul><ul><li>Johny Sun </li></ul><ul><li>All Garner lab memebers and friends at UTA </li></ul><ul><li>Collaborator : (Cancer Immunobiology center, UTSW) </li></ul><ul><li>Dr. Jonathan Uhr </li></ul><ul><li>Nancy Lane </li></ul><ul><li>Huaying Liu </li></ul>

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