1 / 42

GATE Overview and recent advances

GATE Overview and recent advances. Nicolas Karakatsanis Irène Buvat. National Technical University of Athens, Greece Laboratory of Functional Imaging, U678 INSERM, Paris, France. Outline. Evolution of the use of MC simulations in ET since 1996 OpenGATE motivation and short history

modesta
Download Presentation

GATE Overview and recent advances

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. GATE Overview and recent advances Nicolas Karakatsanis Irène Buvat National Technical University of Athens, Greece Laboratory of Functional Imaging, U678 INSERM, Paris, France

  2. Outline • Evolution of the use of MC simulations in ET since 1996 • OpenGATE motivation and short history • New features in MC simulators in ET • New applications for MC simulations • Upcoming developments in MC simulations • Conclusion

  3. 2001-2005 • 15 different codes: • - 8 « home-made » • - 7 publicly released or available from authors No « standard » code for Monte Carlo simulations in SPECT and PET And recently Most frequently used Penelope SimSET SIMIND GATE Evolution of the codes used for MC simulations in ET since 1996 1996-2000 • 14 different codes: • - 10 « home-made » • - 4 publicly released or available from authors

  4. Motivation for developing GATE in 2001 • Provide a public code • based on a standard code to ensure reliability • enabling SPECT and PET simulations (possibly even more) • accommodating almost any detector design (including prototypes) • modeling time-dependent processes • user-friendly • Developed as a collaborative effort

  5. The OpenGATE collaboration From 4 to 23 labs worldwide • U601 Inserm, Nantes • U650 Inserm, Brest • U678 Inserm, Paris • LPC CNRS, Clermont Ferrand • IReS CNRS, Strasbourg • UMR5515 CNRS, CREATIS, Lyon, • CPPM CNRS, Marseilles • Subatech, CNRS, Nantes • SHFJ CEA, Orsay • DAPNIA CEA, Saclay • Joseph Fourier University, Grenoble • Delft University of Technology, Delft, The Netherlands • Ecole Polytechnique Fédérale de Lausanne, Switzerland • Forschungszentrum Juelich, Germany • Ghent University, Belgium • National Technical University of Athens, Greece • Vrije Universiteit Brussel, Belgium • John Hopkins University, Baltimore, USA • Memorial Sloan-Kettering Cancer Center, New York, USA • University of California, Los Angeles, USA • University of Massachusetts Medical School, Worcester, USA • University of Santiago of Chile, Chile • Sungkyunkwan University School of Medicine, Seoul, Korea

  6. Product of OpenGATE: GATE • Publicly released on May 2004 http://www.opengatecollaboration.org • An official publication: • Jan S, Santin G, Strul D, Staelens S, Assié K, Autret D, Avner D, Barbier R, Bardiès M, Bloomfield PM, Brasse D, Breton V, Bruyndonckx P, Buvat I, Chatziioannou AF, Choi Y, Chung YH, Comtat C, Donnarieix D, Ferrer L, Glick SJ, Groiselle CJ, Guez D, Honore PF, Kerhoas-Cavata S, Kirov AS, Kohli V, Koole M, Krieguer M, van der Laan DJ, Lamare F, Largeron G, Lartizien C, Lazaro D, Maas MC, Maigne L, Mayet F, Melot F, Merheb C, Pennacchio E, Perez J, Pietrzyk U, Rannou FR, Rey M, Schaart D, Schmidtlein CR, Simon L, Song TY, Vieira JM, Visvikis D, Van de Walle R, Wiers E, Morel C. GATE: a simulation toolkit for PET and SPECT. Phys Med Biol 49: 4543-4561, 2004. • More than 800 subscribers to the Gate users mailing list

  7. Tasks of the OpenGATE collaboration • Upgrade GATE for following GEANT4 new releases (1 major release per year) • Incorporate new developments in GATE (1 minor release per year) e.g.: • variance reduction techniques (to be released soon) • speed-up options (e.g., analytical modeling of the collimator response in SPECT) (to be released soon) • tools for running GATE on a cluster or on a grid environment (to be released soon) • extension of GATE for dosimetry applications • tools for interfacing GATE output with other software (STIR) • Organize training

  8. GATE today: technical features • Based on GEANT 4 • Written in C++ • User-friendly: simulations can be designed and controlled using macros, without any knowledge in C++ • Appropriate for SPECT and PET simulations • Flexible enough to model almost any detector design, including prototypes • Explicit modeling of time (hence detector motion, patient motion, radioactive decay, dead time, time of flight, tracer kinetics) • Can handle voxelized and analytical phantoms

  9. GATE today: practical features • Can be freely downloaded, including the source codes • Can be run on many platforms (Linux, Unix, MacOs) • On-line documentation, including FAQ and archives of all questions (and often answers) about GATE that have been asked so far • Help about the use of GATE can be obtained through the gate-user mailing list • Many commercial tomographs and prototypes have already been modeled (including validation of the model)

  10. www.opengatecollaboration.org

  11. PET systems already modeled by the OpenGATE collaboration

  12. GE Advance/Discovery LS PET scanner Schmidtlein et al, Med Phys 2006 GE Advance/Discovery ST PET, 3D mode Schmidtlein et al. MSKCC Some examples

  13. D.Guez et al., HRRT, CEA/DAPNIA and SHJF Some examples HRRT Guez et al, DAPNIA and SHJF

  14. SPECT systems already modeled by the OpenGATE collaboration

  15. Example DST Xli camera Phantom holder Schielding Backcompartment NaI(Tl) crystal Scanning table MEHR collimator Assié et al, Phys Med Biol 2005

  16. 7 6 5 Real data 4 Simulated data 3 2 1 0 50 70 90 110 130 150 170 190 210 230 250 270 15 13 11 FWHM (mm) 9 7 5 3 Energy (keV) 0 5 10 15 20 25 source - collimator distance (cm) Some examples Indium 111 source in air Indium 111 source in water 14 12 10 8 Counts (AU) Counts (AU) 6 4 2 0 230 50 70 90 110 250 270 130 150 170 190 210 Energy (keV) Assié et al, Phys Med Biol 2005

  17. Prototypes already modeled by the OpenGATE collaboration

  18. GATE Experiment Example crystal collimator PSPMT Energy spectrum IASA CsI(Tl) gamma camera … Number of counts Experiment GATE Energy (keV) • Lazaro et al, Phys Med Biol 2004

  19. Monte Carlo simulations today: what is new?

  20. Modeling time dependent processes • SPECT and PET intrinsically involves time: • Change of tracer distribution over time (tracer biokinetic) • Detector motions during acquisition • Patient motion • Radioactive decay • Dead time of the detector • Time-of-flight PET GEANT 4 (hence GATE) is perfect in that regard

  21. Modeling of radioactive decay 15O (2 min) 11C (20 min) • Santin et al, IEEE Trans Nucl Sci 2003

  22. Modeling of time of flight PET • Groiselle et al, IEEE MIC Conf Rec 2004

  23. Modeling realistic phantoms • Realistic phantoms can be easily used as GATE input • NCAT • MOBY • Segars et al, Mol Imaging Biol 2004 • Segars et al, IEEE TNS 2001 • Descourt et al, IEEE MIC Conf Records 2006

  24. Modeling original detector designs GEANT 4 is a very flexible tool • Non-conventional geometries TEP/CT BIOGRAPH Siemens detection block lead end-shielding • Spherical geometry of the Hi-Rez PET scanner • Michel et al, IEEE Conf Records 2006

  25. Modeling original detector designs Small animal imaging TEP/CT BIOGRAPH Siemens • Mouse-size gamma camera • 2 Hamamatsu H8500 PSPMT • NaI pixelized scintillator • Tungsten collimator • Mouse-size PET • 1 Hamamatsu H8500 PSPMT • pixelated LYSO scintillator (30 x 35 crystals per block, 1 head = 1 block) • Sakellios et al, IEEE MIC Conf Records 2006

  26. Modeling original detector designs Small animal imaging • Simulated mouse gamma camera image • (MOBY phantom) • Simulated mouse PET image • (MOBY phantom) • Sakellios et al, IEEE MIC Conf Records 2006

  27. 2000-2004 New applications for Monte Carlo simulations 1995-1999 Design and assessment of correction and reconstruction methods Study of an imaging system response Data production for evaluation purpose Use in the very imaging process Description and validation of a code

  28. Optimizing detector design NEC curves as a function of the crystal in the PET HiRez scanner Michel et al IEEE MIC Conf Records 2006

  29. i j R(i,j): probability that a photon (or positron) emitted in voxel j be detected in pixel i • Calculating R using Monte Carlo simulations: • for non conventional imaging design (small animal) • to account for fully 3D and patient-specific phenomena difficult to model analytically (mostly scatter) e.g., Lazaro et al Phys Med Biol 2005, Rafecas et al IEEE TNS 2004, Rannou et al IEEE MIC Conf Rec 2004 Using Monte Carlo simulations for calculating the system matrix “Object” f GATE is very appropriate but slow Projection p p = R f

  30. Real data 21.2 cm 22 cm Example: SPECT Tc99m phantom Simulated data El Bitar et al IEEE MIC Conf Records 2006

  31. What next?

  32. GATE GATE GATE Bridging the gap between MC modeling in imaging and dosimetry SIMIND DPM DPM The validity of the physics at low energy will have to be checked Problems in G4 have been identified, e.g., multiple scattering and corresponding energy deposit calculation Dewaraja et al, J Nucl Med 2005

  33. Modeling hybrid machines (PET/CT, SPECT/CT, OPET) PET/CT SPECT/CT OPET GATE GATE GATE TOAST • Alexandrakis et al, Phys Med Biol 2005 • Brasse et al, IEEE MIC Conf Rec 2004 • Integrating Monte Carlo modeling tools for: • - common coordinate system • - common object description • - consistent sampling • - convenient assessment of multimodality imaging On-going studies regarding the use of GATE for CT simulations

  34. Conclusion • GATE is a very relevant tool for Monte Carlo simulations in ET • Simulations will be more and more present in (nuclear) medical imaging in the future: • as a invaluable guide for designing scanners, imaging protocols and interpreting SPECT and PET scans • in the very imaging process of a patient

  35. Last but not least: next GATE training • 3 days, March 7-9th, 2007 in Clermont-Ferrand, France • GATE installation, GATE use through lectures and practical sessions given by GATE experts • Registration will open on December, attendance will be limited Registration from mid-december on http://www.opengatecollaboration.org

  36. Acknowledgments • The OpenGATE collaboration

  37. Thank you!!!

  38. Throughput of the simulations • High throughput needed for efficient data production • The major problem with GATE and GEANT4! • Big “World”: • - detectors have a “diameter” greater than 1 m • emitting object (e.g., patient) is large (50 cm up to 1.80 m) • emitting object is finely sampled (typically 1 mm x 1 mm x 1 mm cells) • voxelized objects are most often used • Large number of particles to be simulated • low detection efficiency • in SPECT, typically 1 / 10 000 is detected • in PET, 1 / 200 is detected • At least 4 approaches can be used to increase the throughput of the simulations

  39. Fictitious cross-section (or delta scattering) Using acceleration methods • Variance reduction techniques such as importance sampling (e.g. in SimSET) speed-up factors between 2 and 15

  40. Combining MC with non MC modeling • Full MC • Collimator Angular Response Function • increase in efficiency > 100 • Song et al, Phys Med Biol 2005

  41. Parallel execution of the code on a distributed architecture Speed-up factor ~ number of jobs new merger old merger PET • De Beenhouwer et al, IEEE MIC Conf Records 2006

  42. Smart sampling • Taschereau et al, Med Phys 2006

More Related