Dhanashree Palande , Daqing Piao

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 DhanashreePalande, DaqingPiao School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK 74078, USA

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

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

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

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

6. HbT and StO2 measurement • In the range 700-900nm, absorption of water is much lower than that of oxygenated hemoglobin and deoxygenated hemoglobin • Multi-wavelength data: • Rendered extracting oxygen saturation and hemoglobin concentration. • 705 nm, 785 nm, 808 nm • Absorption coefficients recovered at 3 specific bands are: ()

7. HbT and StO2 measurement • They are used to calculate HbO and Hb as Where, was matrix of molar extinction coefficients • Total hemoglobin: HbT= HbO+Hb (in milliMole) • Oxygen saturation: StO2=HbO/HbT x 100 (in %)

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

9. The Forward Model • The technique to determine what a given sensor would measure in given environment by using theoretical equations for sensor response • Diffusion approximation in frequency domain Where : absorption coefficient : reduced scattering coefficient : isotropic source term : photon fluence rate at position r and modulation frequency : diffusion coefficient : speed of light in medium

10. The Inverse Model • Using the results of actual observations to infer the values of the parameters characterizing the system under investigation. • Goal: recovery of optical properties at each spatial element • Tikhonov minimization: : measured fluence at tissue surface : calculated data using forward solver Where, NM: number of measurements from imaging device NN: number of spatial elements : regularization parameter : initial estimate of optical properties

11. The Inverse Model • The minimization with respect to μ in equation : Jacobian matrix, J Using linear approximation and solving it as iterative scheme, Where, : update of optical properties : data-model misfit at current iteration I I: identity matrix Slight modification gives, Where, and

12. The Inverse Model • NIRFAST is used for inverse problem solving

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

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

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

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

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

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

19. 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

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

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

22. Manually Segmented Images For axial images For sagittal images

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

24. Rectangular Mesh With spatial prior Without spatial prior

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

26. Reconstruction: Right Lobe Day 49 With spatial prior Without spatial prior 40 mm Ultrasound image 40 mm HbT 90 90 StO2 40 40 60 mm 60 mm

27. Reconstruction: Right Lobe Day 56 With spatial prior without spatial prior Ultrasound image 40 mm 40 mm HbT 90 90 StO2 40 40 60 mm 60 mm

28. Right Lobe 40 40

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

30. Reconstruction: Left Lobe Day 49 With spatial prior without spatial prior Ultrasound image 40 mm 40 mm HbT 90 90 StO2 40 40 60 mm 60 mm

31. Left Lobe Day 63 With spatial prior without spatial prior Ultrasound image 40 mm 40 mm HbT 90 90 StO2 40 40 60 mm 60 mm

32. Left Lobe 90 10 40 90 10 40

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

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

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

36. Thank you Questions/suggestions