Image Reconstruction Methods for Dedicated Nuclear Medicine Detectors for Prostate Imaging

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1 Image Reconstruction Methods for Dedicated Nuclear Medicine Detectors for Prostate Imaging Mark F. Smith, Ph.D. Detector and Imaging Group, Physics Division Thomas Jefferson National Accelerator Facility Newport News, Virginia, USA

2 Outline General Principles for Image Reconstruction for Dedicated Detectors Image Reconstruction for Specific Dedicated Prostate Imaging Devices Future Perspectives Summary

3 General Principles: Image Reconstruction with Dedicated Detectors Iterative statistical methods are broadly applicable - Solution of the matrix equation d=as, d = observed data, A = system matrix, s = discretized source distribution - Analytic solutions may be possible for favorable geometries More acquired data information is good - Smaller crystal elements for pixellated detectors BUT need to consider effects on energy resolution, total device sensitivity - Depth of interaction (DOI; better raytracing for gamma events/lors) - Energy resolution (reduced scatter) - Improved time resolution (reduced randoms) - Time of Flight (TOF; better event localization) Modeling physics of photon transport and detector as best possible is good - Guiding principle: make the best use of the information that is acquired - Example: even if DOI information is not available, can model crystal thickness in system matrix

4 Image Reconstruction for Dedicated Prostate Imaging Devices Dedicated PET tomograph Rotating planar detectors Compton probe and camera Flexible detector positioning Recent algorithmic innovations

5 Dedicated PET Prostate Tomograph Lawrence Berkeley National Laboratory Incomplete elliptical ring of HR+ PET block detector modules 3-D iterative penalized maximum likelihood (MAP) algorithm System matrix models: - Detector block position, orientation, gaps, crystal penetration - Object attenuation (optional) - Crystal subsampling as desired Partial Assembly Centered planar phantom for LOR efficiency normalization Modular program structure uses Assembled with mock patient initialization files for description of detector blocks and detector block positioning Hu et al., 3-D 2005 Huber et al., IEEE MIC 2005

6 Dedicated PET Prostate Tomograph Lawrence Berkeley National Laboratory uber et al., IEEE MIC line source phantom Single lines 2, 4, 6, 8 cm from center Lines in clusters 4, 5, 6, 8 mm apart 4 and 8 cm from center Dual cylinder experiment Outer: 19 cm diam., 20 cm long, 0.11 µci/ml F-18 Inner: 4 cm diam., 20 cm long, 0.04 µci/ml F-18 One hour scan, 68 M events No scatter correction Only coincidences from opposed detector banks => incomplete angular sampling artifacts

7 High Resolution Prostate Imager Jefferson Lab / Duke University Medical Center Prostate imaging feasibility studies 3-D Limited Angle Tomography 15 x 20 cm 2 LGSO, 3x3x10mm 3 crystals, R C8 PSPMTs Elliptical phantom, 21cm x 36 cm, 40 cm long 2.2 cm sphere, two 1.3 cm spheres 10:1sphere:bkgd, total phantom activity ~9 MBq F degree increment, 3 min/angle, 42 cm detector dist. 3-D MLEM image reconstruction, no attn correction pecial-purpose prostate gantry (no detectors) Turkington et al., IEEE MIC 2004

8 Compton Probe for Prostate Imaging Instituto de Fisica Corpuscular, Valencia, Spain Compton Imaging Principle Backprojection onto Blurred Conical Shells Lacasta et al. IEEE MIC 2005 Prostate Imager Concept with Intra-rectal Probe

9 Compton Probe for Prostate Imaging University of Michigan Zhang et al. IEEE MIC 2004 In-111 Prostascint Simulation Collimated SPECT Imaging FBP Reconstruction Compton Imaging with Intra-rectal Probe MLEM Reconstruction

10 Flexible Detector Positioning for Prostate Imaging Flexible coincidence detector positioning for prototype cardiac imager (UF/Jefferson Lab) Articulated arm for breast/pediatric imaging (Dilon Technologies) Multiple degree of freedom gantry for breast (Tornai et al., Duke University, IEEE MIC 2001) Extend LBNL approach: add detector modules orthogonal to elliptical detector banks, e.g. between legs (Huber et al., IEEE MIC 2005)

11 Recent Algorithmic Innovations Analytic image reconstruction algorithm for dual circular arc detectors (2D) - Fast Hilbert transform-based filtered backprojection formula (no rebinning) original dual linear dual linear pair Kazantsev et al., IEEE MIC 2005 dual curvilinear Filtered backprojection algorithm for Compton cameras - Intersection of Compton scatter cone with a sphere is a circle - Stereographic projection sphere to 2-D plane for application of Fourier methods (ramp filter, debluring of Doppler broadening) - Reprojection onto sphere for 3-D activity estimation Gunter et al., IEEE MIC 2005

12 Future Perspectives (I) Algorithms and data analysis - What could conceivably be done better? EM and variations are robust, model statistics and detector physics well - Is there anything new on horizon beyond histogrammed or list-mode image reconstruction with appropriate regularization? - Spatial-dependent kinetic rate constants/uptake-washout parameterization - Track torso motion and perform motion correction in image reconstruction - Multi-modality imaging: Bayesian priors from other modalities (US, MRI) - Move beyond just image reconstruction to further data analysis Automated detection probabilities What is the task, i.e. the desired information from the study?

13 Multimodality Prostate Imaging Lawrence Berkeley National Laboratory, UCSF Mock Patient Positioning PET and TRUS 3-D Transrectal Ultrasound (TRUS) TRUS can be used to provide boundary constraints for image reconstruction for a dedicated prostate PET imager Huber et al., IEEE MIC 2005

14 Future Perspectives (II) Computational Challenges - Lower cost of computer clusters: better modeling of detector physics GATE (based on GEANT) or other simulation code - At what point is better modeling of the system matrix not justified based on the observed number of events? Advantages/disadvantages of computed, parameterized/analytically approximated, experimental PSFs - Model depth of interaction (if not measured), motion-correction

15 GATE Prostate Imaging Simulation Detectors: 15 x 20 cm 2, 2 x 2 x 30 mm 3 LYSO, 40 cm detector separation Phantom: 30 cm diam. water-filled cylinder, 2.5 cm diam. sphere, 5 cm off-center Axial View Perspective View Tran, Jefferson Lab

16 Future Perspectives (III) Image reconstruction to aid instrumentation design and use - What could be the benefit of really novel detector configurations? e.g. combine pinhole and converging beam collimation, novel orbits? - Multiple pinhole/coded aperture imaging for prostate SPECT Reconstructions are straightforward - what are SNR/sensitivity gains, if any? Are there advantages vs. optimally designed parallel hole or fan beam collimators? - Methodological approaches for design and characterization of imaging systems NECR, Fisher information matrix, linearized local impulse response, Cramer-Rao bounds e.g. septa design for dedicated prostate imager (Qi et al., IEEE MIC 2003)

17 Summary Current iterative statistical algorithms provide a framework for reconstructing prostate images from a wide variety of detectors and acquisition geometries for PET and SPECT Analytic image reconstruction methods can be fast and useful for favorable acquisition geometries Image reconstruction and data analysis methods potentially can be used 1) to aid design of equipment and patient imaging protocols 2) to extract additional task-dependent physiological information from the acquired data

18 Acknowledgements Jefferson Lab Detector and Imaging Group Brian Kross, Stan Majewski, Vladimir Popov, Tim Tran, Drew Weisenberger, Ben Welch, Randy Wojcik Lawrence Berkeley National Laboratory Jicun Hu, Jennifer Huber, Jinyi Qi, William Moses Lawrence Livermore National Laboratory Don Gunter Instituto de Fisica Corpuscular G. Llosá, C. Lacasta Duke University Mecical Center Martin Tornai, Tim Turkington University of Florida David Gilland University of Michigan Neal Clinthorne, Lisha Zhang University of Pennsylvania Ivan Kazantsev Dilon Technologies Lee Fairchild, Ben Welch Support Department of Energy Office of Science Office of Biological and Environmental Research Office of Nuclear Physics U.S. Army Medical Research and Materiel Command