1. Trans-rectal near-infrared optical tomography reconstruction of a regressing experimental tumor in a canine prostate by using the prostate shape profile synthesized from sparse 2- dimentional trans-rectal ultrasound images Dhanashree Palande, Daqing Piao School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK 74078, USA

2. Outline  Objective Methods Results Conclusion and future work 2

3. Objective Near infrared(NIR) optical imaging: –well suited for non-invasive quantification of hemoglobin oxygen saturation(StO2) –provides unique information regarding optical properties Limitation of NIR: –low spatial resolution due to high scattering in tissue Solution: –compensate optical imaging with spatial prior information extracted from high resolution trans-rectal ultrasound (TRUS) images to improve the reconstruction outcome of trans-rectal DOT –obtain a 3D prostate profile from 2D TRUS images using segmentation which is used as a structural spatial prior in optical tomography reconstruction 3

4. Outline Objective  Methods Results Conclusion and future work 4

5. NIR Optical Tomography(DOT) Non-invasive imaging technique: aims to reconstruct images of tissue function and physiology Biological tissue is highly scattering at NIR wavelengths (650-900 nm) Also known as diffuse optical tomography(DOT) NIR light is applied through optical fibers positioned to surface of the tissue Emergent light is measured at other locations on the same tissue surface NIR optical tomography along with reconstruction algorithm, produces images of tissue physiology for detection and characterization of malignancy 5

6. HbT and StO2 measurement 6

7. 7

8. NIR Reconstruction Geometry Outer rectangular mesh: –equivalent to tissue surrounding the prostate –Required to match NIR reconstruction geometry 8

9. The Forward Model 9

10. The Inverse Model 10

11. The Inverse Model 11

12. The Inverse Model 12

13. TRUS Images of a Canine Prostate A canine prostate was used for study Transmissible Venereal Tumor(TVT) cells was injected in right lobe of a prostate Dog was monitored over the 63-days period, at weekly intervals TRUS images were taken at: –Right edge plane –Right middle plane –Middle sagittal plane –Left middle plane –Left edge plane 13

14. TRUS Images of a Canine Prostate Axial viewSagittal view rectum Left lobe Right lobe Caudal side Cranial side 14

15. TRUS Images of a Canine Prostate Axial viewSagittal view rectum Left lobe Right lobe Caudal side Cranial side 15

16. TRUS Image Segmentation TRUS image segmentation is challenging due to –Complexity in contrast –Image artifacts –Morphological features –Variation in prostate shape and size Manual contour tracking –Interactive program takes input from user –Sagittal images segmented manually –Used as reference for 3D profile 16

17. Approximating Axial Plane Positions We have set of sparsely acquired axial images We use 3 images at cranial side, middle and caudal side of the prostate A program is written to find approximate positions of these axial planes 17

18. 3D Profiling of a Prostate Interpolation –Spline type of interpolation for smooth profile along the curve –Using the points on axial contours –New data points are interpolated depending on required mesh density 18

19. Mesh Generation Mesh Generation Generation of a 3D mesh prostate profile using Delaunay triangulation –Input: interpolated data points from 3D profile –Output: elements of all the tetrahedrons This mesh is now used as a spatial prior for NIR image reconstruction 19

20. Prostate Mesh within Rectangular Mesh Mesh used for reconstruction 20

21. Outline Objective Methods  Results Conclusion and future work 21

22. Manually Segmented Images For axial images For sagittal images 22

23. 3D Prostate Profile 3D profile of prostate 3D mesh profile of a prostate 23

24. Rectangular Mesh With spatial priorWithout spatial prior 24

25. Reconstruction: Right Lobe Baseline With spatial prior Without spatial prior 25 90 40 90 40 60 mm 40 mm Ultrasound image HbT StO2

26. Reconstruction: Right Lobe Day 49 With spatial priorWithout spatial prior 26 90 40 90 40 60 mm 40 mm Ultrasound image HbT StO2

27. Reconstruction: Right Lobe Day 56 With spatial priorwithout spatial prior 27 90 40 90 40 60 mm 40 mm Ultrasound image HbT StO2

28. Right Lobe 40

29. 29 Right Lobe (weeks) 7 8 97 8 9 (weeks)

30. Reconstruction: Left Lobe Day 49 With spatial priorwithout spatial prior 30 90 40 90 40 60 mm 40 mm Ultrasound image HbT StO2

31. Left Lobe Day 63 With spatial priorwithout spatial prior 31 90 40 90 40 60 mm 40 mm Ultrasound image HbT StO2

32. Left Lobe 32 90 10 90 10 40

33. Outline Objective Methods Results  Conclusion and future work 33

34. Conclusion and future work -Contribution of this work This work explores combination of structural and functional imaging for the study of prostate cancer 3D prostate profile was generated from sparse 2D axial TRUS images of a canine prostate A prostate mesh developed was used a spatial prior to NIR optical tomography for image reconstruction Reconstructed images with and without prior were compared qualitatively This approach helps to interpret results for good understanding of position of tumor lesion developed in prostate. To our knowledge, this is the first attempt to use TRUS guided structural spatial prior for image reconstruction of a prostate using NIR optical tomography 34

35. Conclusion and future work -Future directions Extending this study to other animals and eventually to human prostates Applying spectral prior information along with spatial prior To make this system work real-time, so as to be used during clinical exams 35

36. Thank you Questions/suggestions 36