UNIVERSIDAD COMPLUTENSE DE MADRID FACULTAD DE CIENCIAS FÍSICAS Departamento de Física Atómica, Molecular y Nuclear TESIS DOCTORAL Caracterización, mejora y diseño de escáneres PET preclínicos MEMORIA PARA OPTAR AL GRADO DE DOCTOR PRESENTADA POR Esther Vicente Torrico Directores José Manuel Udías Moinelo Joaquín López Herraiz Juan José Vaquero López Madrid, 2013 © Esther Vicente Torrico, 2012 Universidad Complutense de Madrid Facultad de Ciencias Físicas Dpto. de Física Atómica, Molecular y Nuclear CARACTERIZACIÓN, MEJORA Y DISEÑO DE ESCÁNERES PET PRECLÍNICOS ESTHER VICENTE TORRICO Tesis dirigida por: Dr. José Manuel Udías Moinelo Dr. Joaquín López Herraiz Dr. Juan José Vaquero López Madrid 2012 Contents MOTIVATION AND OBJECTIVES .................................................................................................................. 1! THESIS OUTLINE ............................................................................................................................................... 3! 1.! INTRODUCTION ........................................................................................................................................ 5! 1.1.! PRINCIPLES OF PET I - PHYSICS BACKGROUND ...................................................................................... 6! 1.1.1.!Beta decay ................................................................................................................................. 6! 1.1.2.!PET Radionuclides ................................................................................................................... 7! 1.1.3.!Interactions of gamma radiation with matter ........................................................................... 8! 1.2.! PRINCIPLES OF PET II - DETECTORS ..................................................................................................... 11! 1.2.1.!Scintillators ............................................................................................................................. 11! 1.2.2.!Photosensors ........................................................................................................................... 13! 1.2.3.!Electronics .............................................................................................................................. 14! 1.3.! PRINCIPLES OF PET III - CORRECTIONS ................................................................................................ 17! 1.3.1.!Decay ...................................................................................................................................... 17! 1.3.2.!Attenuation .............................................................................................................................. 17! 1.3.3.!Scatter ..................................................................................................................................... 18! 1.3.4.!Random coincidences ............................................................................................................. 18! 1.3.5.!Normalization ......................................................................................................................... 19! 1.3.6.!Dead-time ............................................................................................................................... 20! 1.3.7.!Pile-up ..................................................................................................................................... 20! 1.4.! MONTE CARLO SIMULATIONS .............................................................................................................. 21! 1.4.1.!Random numbers and probability distribution function ......................................................... 22! 1.4.2.!Monte Carlo Packages for Nuclear Medicine ........................................................................ 22! 1.5.! BASICS OF IMAGE RECONSTRUCTION ................................................................................................... 24! 1.5.1.!Data organization ................................................................................................................... 24! 1.5.2.!Analytical methods .................................................................................................................. 26! 1.5.3.!Iterative methods .................................................................................................................... 28! 1.6.! REFERENCES ......................................................................................................................................... 31! 2.! MATERIALS .............................................................................................................................................. 35! 2.1.! THE RPET SCANNER ............................................................................................................................. 35! 2.1.1.!System description .................................................................................................................. 35! 2.1.2.!Data acquisition and processing ............................................................................................ 36! 2.2.! THE ARGUS PET/CT SCANNER ............................................................................................................. 38! 2.2.1.!System description .................................................................................................................. 38! 2.2.2.!Data acquisition ...................................................................................................................... 39! 2.3.! MONTE CARLO SIMULATIONS: PENELOPET ......................................................................................... 40! 2.3.1.!Main features of PeneloPET ................................................................................................... 40! 2.3.2.!PENELOPE ............................................................................................................................ 43! 2.4.! IMAGE RECONSTRUCTION: FIRST ........................................................................................................ 45! 2.4.1.!Main features of the FIRST algorithm .................................................................................... 45! 2.4.2.!GFIRST: GPU-Based Fast Iterative Reconstruction of Fully 3-D PET Sinograms ............... 46! 2.5.! REFERENCES ......................................................................................................................................... 49! 3.! PERFORMANCE EVALUATION OF PRECLINICAL PET SCANNERS ........................................ 51! 3.1.! CHARACTERIZATION OF RPET & ARGUS SCANNERS ............................................................................ 52! 3.1.1.!Materials & Methods .............................................................................................................. 52! 3.1.2.!Results ..................................................................................................................................... 59! 3.1.3.!Conclusions ............................................................................................................................. 65! 3.2.! SCATTER FRACTION ESTIMATION USING 18F AND 68GA SOURCES ....................................................... 66! 3.2.1.!Materials & Methods .............................................................................................................. 66! 3.2.2.!Results ..................................................................................................................................... 68! 3.2.3.!Conclusions ............................................................................................................................. 72! 3.3.! REFERENCES ......................................................................................................................................... 74! 4.! DATA-CORRECTIONS IN PRECLINICAL PET ................................................................................. 75! 4.1.! MODELING OF PILE-UP AND DEAD-TIME FOR SMALL ANIMAL PET SCANNERS ...................................... 76! 4.1.1.!Methods ................................................................................................................................... 79! 4.1.2.!Results ..................................................................................................................................... 82! 4.1.3.!Conclusions ............................................................................................................................. 88! 4.1.4.!Appendix 4.1A. Linear relationship between ! and SCR ........................................................ 88! 4.1.5.!Appendix 4.1B. Relative error in the corrected count rates as a function of the error in the effective dead-time .................................................................................................................. 89! 4.2.! MEASUREMENT OF MISALIGNMENTS IN SMALL-ANIMAL PET SCANNERS BASED ON ROTATING PLANAR DETECTORS AND PARALLEL-BEAM GEOMETRY ....................................................................... 90! 4.2.1.!Monte Carlo simulations using PeneloPET ........................................................................... 91! 4.2.2.!Study of the effect of misalignments ........................................................................................ 92! 4.2.3.!Calibration algorithm ........................................................................................................... 104! 4.2.4.!Evaluation ............................................................................................................................. 107! 4.2.5.!Conclusions ........................................................................................................................... 110! 4.3.! ATTENUATION CORRECTION OF PET IMAGES USING CT DATA IN THE SMALL ANIMAL PET SCANNER ARGUS PET/CT .................................................................................................................. 111! 4.3.1.!Materials & Methods ............................................................................................................ 111! 4.3.2.!Results ................................................................................................................................... 114! 4.3.3.!Conclusions ........................................................................................................................... 116! 4.4.! REFERENCES ....................................................................................................................................... 117! 5.! DESIGN OF SMALL ANIMAL PET PROTOTYPES ......................................................................... 121! 5.1.! ZOOM-IN PET SCANNER ..................................................................................................................... 122! 5.1.1.!Setup description .................................................................................................................. 123! 5.1.2.!Main modifications to PeneloPET to consider the Zoom-in PET system ............................. 124! 5.1.3.!Simulated study of the performance of the scanner .............................................................. 127! 5.1.4.!Results ................................................................................................................................... 129! 5.1.5.!Conclusions ........................................................................................................................... 134! 5.2.! NIH PPI SCANNER .............................................................................................................................. 135! 5.2.1.!Setup description .................................................................................................................. 135! 5.2.2.!Image Reconstruction for the PPI ........................................................................................ 137! 5.2.3.!Simulated study of the performance of the scanner .............................................................. 141! 5.2.4.!Results ................................................................................................................................... 144! 5.2.5.!Conclusions ........................................................................................................................... 153! 5.3.! REFERENCES ....................................................................................................................................... 154! CONCLUSIONS OF THIS THESIS ............................................................................................................... 157! PUBLICATIONS DERIVED FROM THIS THESIS .................................................................................... 159! LIST OF FIGURES ........................................................................................................................................... 163! LIST OF TABLES ............................................................................................................................................. 169! APPENDIX A. -DESCRIPTION OF THE PHANTOMS ............................................................................. 171! BIBLIOGRAPHY .............................................................................................................................................. 173! RESUMEN EN CASTELLANO ....................................................................................................................... R1! Motivation and Objectives &Thesis Outline Motivation and Objectives In 1953, the young daughter of a Rhode Island farmer traveled to Boston to find a doctor to diagnose a neurological problem that left her unable to read. When her neurosurgeon at Massachusetts General Hospital could not help her, he enlisted the help of a colleague, Dr. Gordon L. Brownell. As Time magazine reported the following year, Dr. Brownell along with William H. Sweet developed a scanning machine [Sweet, 1951, Brownell et al., 1969, Burnham and Brownell, 1972] that isolated, within a third of an inch (8.5 mm), the location of a tumor that the neurosurgeon successfully removed from the girl’s brain. The technology Dr. Brownell invented was the basis of positron emission tomography (PET). A few years later, in 1973, Michael E. Phelps and collaborators built the first PET tomograph, known as PETT I [Ter-Pogossian et al., 1975, Phelps et al., 1975]. Phelps was one of the first to show how different parts of the brain are activated when performing mental tasks. Since this first PET scanner, positron emission tomography has been established in oncology, cardiology and neurology. The extension of this technique to preclinical research has represented a great challenge ever since the development of the first dedicated small-animal PET system in the mid 1990s ([Watanabe et al., 1992, Pavlopoulos and Tzanakos, 1993, 1996, Tzanakos and Pavlopoulos, 1993, Bloomfield et al., 1995]), with the required improvement in performance in terms of spatial resolution and sensitivity. The interest of this improvement lies in the fact that images with higher resolution can improve our capability of studying human diseases using animal models. Besides the higher resolution requirements, many small-animal PET system designs deal with new geometries which may also hinder direct application of algorithms initially developed for clinical scanners. This poses the necessity of developing protocols adapted to the specific small animal systems in use and, at the same time, leads to questions about how the typical sources of error in clinical scanners scale to small animal systems. In order to improve the quantification properties of PET images in clinical and preclinical practice, data- and image-processing methods are subject of intense interest and development. The evaluation of such methods often relies on the use of simulated data and images since these offer control of the ground truth. Monte Carlo simulations are widely used for PET since they can take into account all the processes involved in PET imaging, from the emission of the positron to the detection of the photons by the detectors. Simulation techniques have become an indispensable complement to a wide range of problems that could not be addressed by experimental or analytical approaches [Rogers, 2006]. PET scanners simulation with Monte Carlo methods also allows the optimization of system design for new scanners, the study of singled-out factors affecting image quality and the validation of correction methodologies for effects such as pile-up and dead-time, scatter, attenuation, detector misalignments, partial volume, etc; everything with the aim of improving image quantification, as well as to develop and test new image reconstruction algorithms. Another major advantage of simulations in PET imaging is that they allow studying parameters that are not measurable in practice. This thesis is embedded in one of the research lines carried out at the Nuclear Physics Group (Grupo de Física Nuclear, GFN) of the Universidad Complutense de Madrid in close collaboration with the Medical Imaging Laboratory (Laboratorio de Imagen Médica, LIM) of Hospital General Universitario Gregorio Marañón, whose objectives are to design, develop and evaluate new systems of data acquisition, processing and reconstruction of images for applications in biomedical research. In this context, the present thesis deals with the study and performance evaluation of the specific small- animal PET systems available at the Medical Imaging Laboratory, the study of the sources of error that limit the quality of the images with the investigation of algorithms to compensate them, and the search of new system designs in collaboration with two more research centers (Department of Biomedical Engineering, University of California, (Davis, CA) and the National Institutes of Health (NIH), Bethesda, MD [Molecular Imaging Program, National Cancer Institute]) where the author of this thesis 1 Motivation and Objectives &Thesis Outline was working as a part of an internship of the JAEPredoctoral (2008) program (Ph.D. fellowship from Instituto de Estructura de la Materia, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain). The main goal of this thesis is to contribute to the improvement of the quality of PET images for preclinical research with small animals by intensive use of Monte Carlo simulations, either for studying limiting problems in existing scanners providing methods to compensate them, either for guiding in the design of new prototypes, analyzing advantages and drawbacks before taking the final decision. Specific objectives are as follows: 1. To evaluate the performance of two of the small-animal PET systems available at the Medical Imaging Laboratory, following, as far as possible, a standard methodology in order to compare systems between them and with other commercial preclinical systems under similar conditions [Vicente et al., 2006 , Goertzen et al., 2012, Vicente et al., 2010a]. 2. To study the sources of error that limit the quality of reconstructed PET images using Monte Carlo simulations and to investigate new methods and algorithms to compensate for these errors [Vicente et al., 2011, Vicente et al., 2012a, Abella et al., 2012, Vicente et al., 2010b]. 3. To use Monte Carlo simulations for the design of new prototypes, performing the necessary modifications in the Monte Carlo package employed (peneloPET, [España et al., 2009]) and in the available reconstruction methods (as GFIRST [Herraiz et al., 2011]) in order to make them suitable to the non-conventional geometries of the new designs [Vicente et al., 2012b]. The algorithms developed in this thesis are not exclusive of any scanner in particular; they have been designed to be flexible and suitable for different architectures with only a few common constrains. However, since this work takes advantage of the access to real data collected by the specific systems available at the Medical Imaging Laboratory, the development and testing of the different methods were adapted to the particular geometry of these systems ([Wang et al., 2006b, Vaquero et al., 2005a]). As a final consideration, it is worth mentioning that significant part of the results presented in this thesis, besides giving rise to scientific publications, are intended to be incorporated into the preclinical high-resolution systems manufactured by SEDECAL and distributed worldwide under technology transfer agreements with the Medical Imaging Laboratory and the Nuclear Physics Group. 2 Motivation and Objectives &Thesis Outline Thesis Outline After a brief general theoretical introduction in Chapter 1, Chapter 2 presents the description of the general materials used in this work. Specifically, we describe the two scanners employed for the characterization (Chapter 3) and the study of several data corrections (Chapter 4). Moreover, we present the main features of the Monte Carlo simulation tool, PeneloPET [España et al., 2009] and the 3D-OSEM reconstruction method, FIRST [Herraiz et al., 2006a], used in this thesis. Chapter 3 presents the characterization of the rPET system [Vaquero et al., 2005a] and the Argus scanner [Wang et al., 2006b] and a more detailed evaluation of the accuracy of the method proposed in NEMA NU 4-2008 standard [NEMA-NU4, 2008] to estimate the scatter fraction with 18F and with a radionuclide with a lager positron range as 68Ga. In Chapter 4 we study in more detail some of the most important corrections that should be applied to PET data. The correction algorithms described have been developed for the two scanners whose performance evaluation is presented in Chapter 3, but they can be applied to other systems. The main contributions resulting from this part of the thesis are a new method to correct pile-up and dead- time effects, a study of the effect of mechanical misalignments of PET scanners and a protocol to detect and measure them, and an attenuation correction method based on CT images. Chapter 5 presents the work regarding the design of new preclinical PET scanner prototypes using Monte Carlo simulations (PeneloPET) to study and characterize their performance. This chapter shows examples of the modifications on simulation codes and reconstruction methods needed to adapt the existing codes to the non-conventional geometry of some designs. At the end of this manuscript we present the general conclusions of the thesis, the publications derived from this thesis and the lists of figures and tables shown in the document. 3 Motivation and Objectives &Thesis Outline References Abella, M., Vicente, E., Rodríguez-Ruano, A., España, S., Lage, E., Desco, M., Udias, J. M. & Vaquero, J. J. 2012. Misalignments calibration in small-animal PET scanners based on rotating planar detectors and parallel-beam geometry. Phys Med Biol (Submitted). Bloomfield, P. M., Rajeswaran, S., Spinks, T. J., Hume, S. P., Myers, R., Ashworth, S., Clifford, K. M., Jones, W. F., Byars, L. G., Young, J. & et al. 1995. The design and physical characteristics of a small animal positron emission tomograph. Phys Med Biol, 40, 1105-26. Brownell, G. L., Burnham, C. A., Wilensky, S., Aronow, S., Kazemi, H. & Streider , D. 1969. New developments in positron scintigraphy and the application of cyclotron produced positron emitters. In: Medical Radioisotope Scintigraphy, 1969 Vienna, Austria. International Atomic Energy Agency, 163–176. Burnham, C. A. & Brownell, G. L. 1972. A Multi-Crystal Positron Camera. Nuclear Science, IEEE Transactions on, 19, 201- 205. España, S., Herraiz, J. L., Vicente, E., Vaquero, J. J., Desco, M. & Udias, J. M. 2009. PeneloPET, a Monte Carlo PET simulation tool based on PENELOPE: features and validation. Phys Med Biol, 54, 1723-42. Goertzen, A. L., Bao, Q., Bergeron, M., Blankemeyer, E., Blinder, S., Cañadas, M., Chatziioannou, A. F., Dinelle, K., Elhami, E., Jans, H.-S., Lage, E., Lecomte, R., Sossi, V., Surti, S., Tai, Y.-C., Vaquero, J. J., Vicente, E., Williams, D. A. & Laforest, R. 2012. NEMA NU 4-2008 Comparison of Preclinical PET Imaging Systems. The Journal of Nuclear Medicine (Accepted). Herraiz, J. L., Espana, S., Vaquero, J. J., Desco, M. & Udias, J. M. 2006a. FIRST: Fast Iterative Reconstruction Software for (PET) tomography. Phys Med Biol, 51, 4547-65. Herraiz, J. L., España, S., Cabido, R., Montemayor, A. S., Desco, M., Vaquero, J. J. & Udias, J. M. 2011. GPU-Based Fast Iterative Reconstruction of Fully 3-D PET Sinograms. Nuclear Science, IEEE Transactions on, 58, 2257-2263. National Electrical Manufacturers Association (NEMA). 2008. Performance Measurements of Small Animal Positron Emission Tomographs. NEMA Standards Publication NU4-2008. Rosslyn, VA. National Electrical Manufacturers Association Pavlopoulos, S. & Tzanakos, G. 1993. Design and performance evaluation of a high resolution small animal positron tomograph. In: Nuclear Science Symposium and Medical Imaging Conference, 1993., 1993 IEEE Conference Record., 31 Oct-6 Nov 1993 1993. 1697-1701 vol.3. Pavlopoulos, S. & Tzanakos, G. 1996. Design and performance evaluation of a high-resolution small animal positron tomograph. Nuclear Science, IEEE Transactions on, 43, 3249-3255. Phelps, M. E., Hoffman, E. J., Mullani, N. A. & Ter-Pogossian, M. M. 1975. Application of annihilation coincidence detection to transaxial reconstruction tomography. J Nucl Med, 16, 210-24. Rogers, D. W. 2006. Fifty years of Monte Carlo simulations for medical physics. Phys Med Biol, 51, R287-301. Sweet, W. H. 1951. The uses of nuclear disintegration in the diagnosis and treatment of brain tumor. N Engl J Med, 245, 875- 8. Ter-Pogossian, M. M., Phelps, M. E., Hoffman, E. J. & Mullani, N. A. 1975. A positron-emission transaxial tomograph for nuclear imaging (PETT). Radiology, 114, 89-98. Tzanakos, G. & Pavlopoulos, S. 1993. Design and performance evaluation of a new high resolution detector array module for PET. In: Nuclear Science Symposium and Medical Imaging Conference, 1993., 1993 IEEE Conference Record., 31 Oct-6 Nov 1993 1993. 1842-1846 vol.3. Vaquero, J. J., Lage, E., Ricon, L., Abella, M., Vicente, E. & Desco, M. 2005a. rPET detectors design and data processing. In: Nuclear Science Symposium Conference Record, 2005 IEEE, 23-29 Oct. 2005 2005a. 2885-2889. Vicente, E., Herraiz, J. L., Canadas, M., Cal-Gonzalez, J., Espana, S., Desco, M., Vaquero, J. J. & Udias, J. M. 2010a. Validation of NEMA NU4-2008 Scatter Fraction estimation with 18F and 68Ga for the ARGUS small-animal PET scanner. In: Nuclear Science Symposium Conference Record (NSS/MIC), 2010 IEEE, Oct. 30 2010-Nov. 6 2010 2010a. 3553-3557. Vicente, E., Herraiz, J. L., Espana, S., Herranz, E., Desco, M., Vaquero, J. J. & Udias, J. M. 2011. Deadtime and pile-up correction method based on the singles to coincidences ratio for PET. In: Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2011 IEEE, 23-29 Oct. 2011 2011. 2933-2935. Vicente, E., Herraiz, J. L., España, S., Herranz, E., Desco, M., Vaquero, J. J. & Udías, J. M. 2012a. Improved effective dead- time correction for PET scanners: Application to small-animal PET. Phys Med Biol (Submitted). Vicente, E., Herraiz, J. L., Seidel, J., Green, M. V., Desco, M., Vaquero, J. J. & Udias, J. M. 2012b. Regularization of 3D Iterative Reconstruction for a Limited-Angle PET Tomograph. In: Nuclear Science Symposium Conference Record (NSS/MIC), 2012 IEEE (Submitted), 2012b. Vicente, E., Udías, A. L., Herraiz, J. L., Desco, M., Vaquero, J. J. & Udías, J. M. 2010b. Corrección de atenuación de imágenes PET usando datos de TAC en el escáner para animales pequeños Argus PET/CT. Libro de Actas, CASEIB 2010. Vicente, E., Vaquero, J. J., Lage, E., Tapias, G., Abella, M., Herraiz, J. L., España, S., Udías, J. M. & Desco, M. 2006 Caracterización del Tomógrafo de Animales rPET. Libro de Actas, CASEIB 2006. Wang, Y., Seidel, J., Tsui, B. M., Vaquero, J. J. & Pomper, M. G. 2006b. Performance evaluation of the GE healthcare eXplore VISTA dual-ring small-animal PET scanner. J Nucl Med, 47, 1891-900. Watanabe, M., Uchida, H., Okada, H., Shimizu, K., Satoh, N., Yoshikawa, E., Ohmura, T., Yamashita, T. & Tanaka, E. 1992. A high resolution PET for animal studies. Medical Imaging, IEEE Transactions on, 11, 577-580. 4 CHAPTER 1 - Introduction 1. Introduction Positron Emission Tomography (PET) [Cherry et al., 2003] is a nuclear medicine technique that uses radioactive substances for the diagnosis and staging of different diseases. These radioactive substances consist of a radionuclide (tracer), chemically bound to a biologically active molecule. Once administered to the patient, the molecule concentrates at specific organs or cellular receptors with a certain biological function. This allows nuclear medicine to image the location and extent of a disease process in the body, based on the cellular and physiologic function. PET is considered essential in the management of many human cancers [Papathanassiou et al., 2009]. The ability to visualize physiological function separates nuclear medicine imaging techniques from traditional anatomic imaging techniques, such as Computed Tomography (CT). When combined with anatomic imaging, such as CT or Magnetic Resonance Imaging (MRI), PET provides the best available information on tumor extent for many common cancers [Macmanus et al., 2009]. PET is based on the decay mechanism of positron emitting nuclides. The emitted positron interacts with an electron of the surrounding matter, resulting in an annihilation of the positron and the electron. In this annihilation process energy and momentum are conserved. Therefore, two gamma rays are emitted, each having an energy equal to the rest mass energy of the electron or the positron (mc2 = 511keV), which propagate in the opposite direction of each other. The two gamma rays are coincidentally registered by the ring detectors of the tomograph (Figure 1) [Ter-Pogossian, 1982] defining a line of response (LOR) along which the positron annihilation took place. The information recorded in every possible LOR is assembled and, with the aid of image processing tools, it is employed to produce an image of the activity and thereby of the functionality of the organism. Figure 1. Schematic representation of a PET scanner and data processing principles. This chapter describes a brief theoretical introduction required to follow the contents of this thesis. The explanation includes some notions of the physics background, detection system, main corrections as well as the tools used to simulate and reconstruct PET data. 5