1. Fuhai Li, Ph.D. BBP-TMHRI, Feb 7 2011 3D Tumor Stem Cell Niche Image Analysis http://www.methodisthealth.com/icbp NCI-ICBP CMCD U54 Progress Report

2. Tumor Stem Cell Niche J Rosen, BCM

3. From 2D to 3D From center grant proposal DAPIGFP DextranSuperimposed.44 μm X.44 μm X 1 μm

4. Specific Aim Digitize 3D images of tumor stem cell niche & provide quantitative data for Tumor modeling Blood vessel tracing Nuclei segmentation

5. What information is expected? Anything we can see, image, and imagine! E.g., Spatial distributions (in normal and tumor, before and after treatment) of blood vessels, stem cells, stroma, etc. Cell morphology, proliferation and death From John, Tegy, Mei Zhang, Michael T. Lewis

6. Blood Vessel and Nuclei Segmentation

7. Blood Vessel Segmentation (Tracing) Technical Challenges: Noise Signal Broken Points and Vessel Crossing

8. 3D Blood Vessel Image

9. Maximum Intensity Projection (MIP)

10. Validation of Available Segmentation Software http://research.mssm.edu/cnic/tools-ns.html

11. NeuronStudio http://research.mssm.edu/cnic/tools-ns.html

12. V3D http://penglab.janelia.org/proj/v3d/V3D/About_V3D.html

13. FARSIGHT http://www.farsight-toolkit.org/wiki/Main_Page

14. Multi-scale Filtering and Optimal Linking Based Approach

15. Multiscale Vessel Enhancement Filtering Hessian Matrix Multiscale means image filtering with Gaussian filters (with different sigmas) The eigenvalues of Hessian matrix tell us where are the vessels A. Frangi, et. al, MICCAI, 1998

16. Binary Image of MIP (Original)

17. Multiscale Vessel Enhancement Filtering

18. Removal of Debris

19. Skeleton Extraction T.C. Lee, et. al, GVGIP, 1994

20. Binary 3D View

21. Optimal Linking by Integer Programming (ongoing) Cost function: can only be linked to at most to once!subject to: Fitness term smoothness term Solving:

22. Nuclei Segmentation Technical Challenges: Uneven Intensity and Cell Clustering

23. 3D View

24. FARSIGHT 3D Analysis

25. Flowchart of Nuclei Segmentation Z-Series 2D Images Adaptive Thresholding Distance Transform (Shape Info.) Seed Image (Non-Maximum Suppression) LoG Filtering (Intensity Info.) Level Set Segmentation

26. 2D Image Analysis

27. TT Proposed 3D Analysis

28. Refine & Define Nuclei by Ellipsoid Fitting Low Z resolution digital 3D tumor stem cell niche nucleus = {o, a, b, c, α, β}

29. Ongoing Work 1.Blood vessel smoothing & broken points linking 2.Nuclei ellipsoid fitting, Image quantification & dividing cell identification 3.Process large volumes of image data to derive information for tumor modeling 4.Graphic user interface (GUI) tools for image analysis, visualization & tumor simulation

30. TT Normal Breast Tissue From Dr. Michael T. Lewis (John David Acquired)

31. Acknowledgements BBP-TMHRI: Stephen Wong Xiaofeng Xia Hong Zhao Derek Cridebring BCM: Michael Lewis Mei Zhang Mary Dickinson John Landua Tegy Vadakkan Wei NIH NCI-ICBP U54 Grant Support