1. Professor Brian F Hutton Institute of Nuclear Medicine University College London brian.hutton@uclh.nhs.uk Emission Tomography Principles and Reconstruction

2. Outline imaging in nuclear medicine basic principles of SPECT basic principles of PET factors affecting emission tomography

3. SPECT History Anger camera 1958 Positron counting, Brownell 1966 Tomo reconstruction; Kuhl & Edwards 1968 First rotating SPECT camera 1976 PET: Ter-Pogossian, Phelps 1975

4. Anger gamma camera Detector: 400x500mm~9mm thick Energy resn~10% Intrinsic resn3-4mm Radionuclides: Tc-99m 140keV, 6hr I -123 159keV, 13hr Ga-68 93-296keV, 3.3dy I-131 360keV, 8dy Collimator Designed to suit energy HR: hole size 1.4mm length 33mm septa0.15mm

5. parallel fanbeam conebeam pinhole slit-slatcrossed slit Organ-specific options specialized collimators for standard cameras

6. Single Photon Emission Computed Tomography (SPECT) Single Photon Emission Computed Tomography (SPECT) relatively low resolution; long acquisition time (movement) noisy images due to random nature of radioactive decay tracer remains in body for ~24hrs: radiation dose ~ standard x-ray function rather than anatomy

7. SPECT Reconstruction 1 angle2 angles 4 angles 16 angles 128 angles Filtered back projection sinogram for each transaxial slice

8. Organ-specific systems specialised system designs, with use limited to a specific application

9. Positron Annihilation IsotopeE max (keV) Max range (mm) FWHM (mm) 18 F 11 C 13 N 15 O 82 Rb 6632.60.22 9604.20.28 12005.40.35 17408.41.22 320017.12.6

10. Coincidence Detection detector 1 detector 2 coincidence window time (ns)

11. PET "Block" Detector Scintillator array PMTs Histogram A B C Images courtesy of CTI BGO (bismuth germanate)

12. Attenuation Correction in PET attenuation for activity in body N = N 0 e -  x. e -  (D-x) = N 0 e -  D attenuation for external source N = N 0 e -  D (D=body thickness) (for 511 keV  ~ 0.096/cm attenuation factors: 25-50)

13. Coincidence Lines of Response (LoR) parallel fanbeam sinogram

14. PET Reconstruction 1 angle2 angles 4 angles 16 angles 128 angles conventional filtered back projection iterative reconstruction sinogram

15. Understanding iterative reconstruction Objective Find the activity distribution whose estimated projections match the measurements. Modelling the system (system matrix) What is the probability that a photon emitted from location X will be detected at detector location Y. - detector geometry, collimators - attenuation - scatter, randoms detector (measurement) object  estimated projection  X Y X Y1Y1 Y2Y2

16. 0 0 0 0 0 0 1 0 0 0 0000000100 0000010000 System matrix voxel j pixel i

17. ML-EM reconstruction original projections estimated projections current estimate original estimate update (x ratio) FP BP NO CHANGE patient

18. Image courtesy of Bettinardi et al, Milan

19. stop at an early iteration use of smoothing between iterations post-reconstruction smoothing penalise ‘rough’ solutions (MAP) use correct and complete system model Noise control

20. Factors affecting quantification courtesy Ben Tsui, John Hopkins

21. + - transmission without attenuation correction with attenuation correction detector

22. 0 0 0 0 0 0 0.9 0 0 0 00000000.200 000000.50000  System matrix: with attenuation

23. Partial volume effects effect of resolution and/or motion problems for both PET and SPECT similar approaches to correction scale of problem different due to resolution some different motion effects due to timing: ring versus rotating planar detector

24. Modelling resolution Gamma camera resolution depends on distance SPECT resolution need radius of rotation PET resolution position dependent

25. 0 0 0 0 0 0.3 0.9 0.3 0 0 0000000.10.20.10 00000.20.50.2000  System matrix: including resolution model

26. FWHM total 2 = FWHM det 2 + FWHM range 2 + FWHM  180 2 positron range colinearity detector PET resolution depth of interaction results in asymmetric point spread function tangential radial intradial ext

27. detector (projection) object  Courtesy: Panin et al IEEE Trans Med Imaging 2006; 25:907-921 potentially improves resolution requires many iterations slow to compute Modelling resolution w/o resn model with resn model stabilises solution better noise properties

28. detector object Scatter correction multiple energy windows for SPECT; PETCT standard models SPECT local effects; PET more distributed Can we consider measurements to be quantitative? Scatter fraction SPECT ~35% PET 2D ~15%; 3D ~40%

29. scatter models analytical, Monte Carlo, approximate models measurement triple energy window (TEW), multi-energy subtract from projections: measured proj – TEW or combine with projector in reconstruction: compare (forward proj + TEW) with measured proj Scatter influenced by photon energy, source location, scatter medium reduces contrast measured Monte Carlo

30. 3D reconstruction Approaches rebin data followed by 2D reconstruction single slice rebinning (SSRB) multi-slice rebinning (MSRB) Fourier rebinning (FORE) full 3D reconstruction 3D OSEM 3D RAMLA limits for FORE

31. Courtesy V Bettinardi, M Gilardi, Milan 2D 4min 3D 4min 2D 2min 3D 2min FORE 2D-OSEM 28subsets 5 iter VUE Point 3D-OSEM 28subsets 2iter FORE 2D-OSEM 28subsets 2 iter

32. Summary Emission tomography functional rather than anatomical single photon versus dual photon (PET) main difference is ‘collimation’ Iterative reconstruction very similar approach for SPECT and PET currently most popular is OSEM (or similar) the better the system model the better the reconstruction