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Toussaint M, Loignon-Houle F, Auger É, Lapointe G, Dussault JP, Lecomte R. On the implementation of acollinearity in PET Monte Carlo simulations. Phys Med Biol 2024; 69:18NT01. [PMID: 39159667 DOI: 10.1088/1361-6560/ad70f1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Accepted: 08/19/2024] [Indexed: 08/21/2024]
Abstract
Objective.Acollinearity of annihilation photons (APA) introduces spatial blur in positron emission tomography (PET) imaging. This phenomenon increases proportionally with the scanner diameter and it has been shown to follow a Gaussian distribution. This last statement can be interpreted in two ways: the magnitude of the acollinearity angle, or the angular deviation of annihilation photons from perfect collinearity. As the former constitutes the partial integral of the latter, a misinterpretation could have significant consequences on the resulting spatial blurring. Previous research investigating the impact of APA in PET imaging has assumed the Gaussian nature of its angular deviation, which is consistent with experimental results. However, a comprehensive analysis of several simulation software packages for PET data acquisition revealed that the magnitude of APA was implemented as a Gaussian distribution.Approach.We quantified the impact of this misinterpretation of APA by comparing simulations obtained with GATE, which is one of these simulation programs, to an in-house modification of GATE that models APA deviation as following a Gaussian distribution.Main results.We show that the APA misinterpretation not only alters the spatial blurring profile in image space, but also considerably underestimates the impact of APA on spatial resolution. For an ideal PET scanner with a diameter of 81 cm, the APA point source response simulated under the first interpretation has a cusp shape with 0.4 mm FWHM. This is significantly different from the expected Gaussian point source response of 2.1 mm FWHM reproduced under the second interpretation.Significance.Although this misinterpretation has been found in several PET simulation tools, it has had a limited impact on the simulated spatial resolution of current PET scanners due to its small magnitude relative to the other factors. However, the inaccuracy it introduces in estimating the overall spatial resolution of PET scanners will increase as the performance of newer devices improves.
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Affiliation(s)
- Maxime Toussaint
- Sherbrooke Molecular Imaging Center of CRCHUS and Department of Nuclear Medicine and Radiobiology, Sherbrooke, Québec, Canada
| | - Francis Loignon-Houle
- Instituto de Instrumentación para Imagen Molecular (I3M), Centro Mixto CSIC-Universitat Politécnica de Valéncia, Valencia, Spain
| | | | | | - Jean-Pierre Dussault
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Roger Lecomte
- Sherbrooke Molecular Imaging Center of CRCHUS and Department of Nuclear Medicine and Radiobiology, Sherbrooke, Québec, Canada
- IR&T Inc., Sherbrooke, Québec, Canada
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Li S, Hamdi M, Dutta K, Fraum TJ, Luo J, Laforest R, Shoghi KI. FAST (fast analytical simulator of tracer)-PET: an accurate and efficient PET analytical simulation tool. Phys Med Biol 2024; 69:165020. [PMID: 39047765 DOI: 10.1088/1361-6560/ad6743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 07/23/2024] [Indexed: 07/27/2024]
Abstract
Objective.Simulation of positron emission tomography (PET) images is an essential tool in the development and validation of quantitative imaging workflows and advanced image processing pipelines. Existing Monte Carlo or analytical PET simulators often compromise on either efficiency or accuracy. We aim to develop and validate fast analytical simulator of tracer (FAST)-PET, a novel analytical framework, to simulate PET images accurately and efficiently.Approach. FAST-PET simulates PET images by performing precise forward projection, scatter, and random estimation that match the scanner geometry and statistics. Although the same process should be applicable to other scanner models, we focus on the Siemens Biograph Vision-600 in this work. Calibration and validation of FAST-PET were performed through comparison with an experimental scan of a National Electrical Manufacturers Association (NEMA) Image Quality (IQ) phantom. Further validation was conducted between FAST-PET and Geant4 Application for Tomographic Emission (GATE) quantitatively in clinical image simulations in terms of intensity-based and texture-based features and task-based tumor segmentation.Main results.According to the NEMA IQ phantom simulation, FAST-PET's simulated images exhibited partial volume effects and noise levels comparable to experimental images, with a relative bias of the recovery coefficient RC within 10% for all spheres and a coefficient of variation for the background region within 6% across various acquisition times. FAST-PET generated clinical PET images exhibit high quantitative accuracy and texture comparable to GATE (correlation coefficients of all features over 0.95) but with ∼100-fold lower computation time. The tumor segmentation masks comparison between both methods exhibited significant overlap and shape similarity with high concordance CCC > 0.97 across measures.Significance.FAST-PET generated PET images with high quantitative accuracy comparable to GATE, making it ideal for applications requiring extensive PET image simulations such as virtual imaging trials, and the development and validation of image processing pipelines.
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Affiliation(s)
- Suya Li
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United States of America
- Imaging Science Program, McKelvey School of Engineering, Washington University in St Louis, St Louis, MO, United States of America
| | - Mahdjoub Hamdi
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United States of America
| | - Kaushik Dutta
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United States of America
- Imaging Science Program, McKelvey School of Engineering, Washington University in St Louis, St Louis, MO, United States of America
| | - Tyler J Fraum
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United States of America
| | - Jingqin Luo
- Department of Surgery, Washington University School of Medicine, St Louis, MO, United States of America
| | - Richard Laforest
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United States of America
- Imaging Science Program, McKelvey School of Engineering, Washington University in St Louis, St Louis, MO, United States of America
| | - Kooresh I Shoghi
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United States of America
- Imaging Science Program, McKelvey School of Engineering, Washington University in St Louis, St Louis, MO, United States of America
- Department of Biomedical Engineering, Washington University in St Louis, St Louis, MO, United States of America
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Herraiz JL, Lopez-Montes A, Badal A. MCGPU-PET: An Open-Source Real-Time Monte Carlo PET Simulator. COMPUTER PHYSICS COMMUNICATIONS 2024; 296:109008. [PMID: 38145286 PMCID: PMC10735232 DOI: 10.1016/j.cpc.2023.109008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2023]
Abstract
Monte Carlo (MC) simulations are commonly used to model the emission, transmission, and/or detection of radiation in Positron Emission Tomography (PET). In this work, we introduce a new open-source MC software for PET simulation, MCGPU-PET, which has been designed to fully exploit the computing capabilities of modern GPUs to simulate the acquisition of more than 100 million coincidences per second from voxelized sources and material distributions. The new simulator is an extension of the PENELOPE-based MCGPU code previously used in cone-beam CT and mammography applications. We validated the accuracy of the accelerated code by comparing it to GATE and PeneloPET simulations achieving an agreement within 10 percent approximately. As an example application of the code for fast estimation of PET coincidences, a scan of the NEMA IQ phantom was simulated. A fully 3D sinogram with 6382 million true coincidences and 731 million scatter coincidences was generated in 54 seconds in one GPU. MCGPU-PET provides an estimation of true and scatter coincidences and spurious background (for positron-gamma emitters such as 124I) at a rate 3 orders of magnitude faster than CPU-based MC simulators. This significant speed-up enables the use of the code for accurate scatter and prompt-gamma background estimations within an iterative image reconstruction process.
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Affiliation(s)
- Joaquin L. Herraiz
- Complutense University of Madrid, EMFTEL, Grupo de Física Nuclear and IPARCOS, Madrid, 28040, Spain
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdiSSC), Madrid,28040, Spain
| | - Alejandro Lopez-Montes
- Complutense University of Madrid, EMFTEL, Grupo de Física Nuclear and IPARCOS, Madrid, 28040, Spain
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, United States of America
| | - Andreu Badal
- DIDSR, OSEL, CDRH, US Food and Drug Administration, Silver Spring, MD, 20993, USA
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de Scals S, Fraile LM, Udías JM, Martínez Cortés L, Oteo M, Morcillo MÁ, Carreras-Delgado JL, Cabrera-Martín MN, España S. Feasibility study of a SiPM-fiber detector for non-invasive measurement of arterial input function for preclinical and clinical positron emission tomography. EJNMMI Phys 2024; 11:12. [PMID: 38291187 PMCID: PMC10828322 DOI: 10.1186/s40658-024-00618-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 01/19/2024] [Indexed: 02/01/2024] Open
Abstract
Pharmacokinetic positron emission tomography (PET) studies rely on the measurement of the arterial input function (AIF), which represents the time-activity curve of the radiotracer concentration in the blood plasma. Traditionally, obtaining the AIF requires invasive procedures, such as arterial catheterization, which can be challenging, time-consuming, and associated with potential risks. Therefore, the development of non-invasive techniques for AIF measurement is highly desirable. This study presents a detector for the non-invasive measurement of the AIF in PET studies. The detector is based on the combination of scintillation fibers and silicon photomultipliers (SiPMs) which leads to a very compact and rugged device. The feasibility of the detector was assessed through Monte Carlo simulations conducted on mouse tail and human wrist anatomies studying relevant parameters such as energy spectrum, detector efficiency and minimum detectable activity (MDA). The simulations involved the use of 18F and 68Ga isotopes, which exhibit significantly different positron ranges. In addition, several prototypes were built in order to study the different components of the detector including the scintillation fiber, the coating of the fiber, the SiPMs, and the operating configuration. Finally, the simulations were compared with experimental measurements conducted using a tube filled with both 18F and 68Ga to validate the obtained results. The MDA achieved for both anatomies (approximately 1000 kBq/mL for mice and 1 kBq/mL for humans) falls below the peak radiotracer concentrations typically found in PET studies, affirming the feasibility of conducting non-invasive AIF measurements with the fiber detector. The sensitivity for measurements with a tube filled with 18F (68Ga) was 1.2 (2.07) cps/(kBq/mL), while for simulations, it was 2.81 (6.23) cps/(kBq/mL). Further studies are needed to validate these results in pharmacokinetic PET studies.
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Affiliation(s)
- Sara de Scals
- Grupo de Física Nuclear, EMFTEL and IPARCOS, Universidad Complutense de Madrid, Madrid, Spain
- Instituto de Investigación del Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Luis Mario Fraile
- Grupo de Física Nuclear, EMFTEL and IPARCOS, Universidad Complutense de Madrid, Madrid, Spain
- Instituto de Investigación del Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - José Manuel Udías
- Grupo de Física Nuclear, EMFTEL and IPARCOS, Universidad Complutense de Madrid, Madrid, Spain
- Instituto de Investigación del Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Laura Martínez Cortés
- Unidad de Aplicaciones Médicas de las Radiaciones Ionizantes, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain
| | - Marta Oteo
- Unidad de Aplicaciones Médicas de las Radiaciones Ionizantes, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain
| | - Miguel Ángel Morcillo
- Unidad de Aplicaciones Médicas de las Radiaciones Ionizantes, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain
| | | | | | - Samuel España
- Grupo de Física Nuclear, EMFTEL and IPARCOS, Universidad Complutense de Madrid, Madrid, Spain.
- Instituto de Investigación del Hospital Clínico San Carlos (IdISSC), Madrid, Spain.
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.
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Galve P, Arias-Valcayo F, Villa-Abaunza A, Ibáñez P, Udías JM. UMC-PET: a fast and flexible Monte Carlo PET simulator. Phys Med Biol 2024; 69:035018. [PMID: 38198727 DOI: 10.1088/1361-6560/ad1cf9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 01/10/2024] [Indexed: 01/12/2024]
Abstract
Objective.The GPU-based Ultra-fast Monte Carlo positron emission tomography simulator (UMC-PET) incorporates the physics of the emission, transport and detection of radiation in PET scanners. It includes positron range, non-colinearity, scatter and attenuation, as well as detector response. The objective of this work is to present and validate UMC-PET as a a multi-purpose, accurate, fast and flexible PET simulator.Approach.We compared UMC-PET against PeneloPET, a well-validated MC PET simulator, both in preclinical and clinical scenarios. Different phantoms for scatter fraction (SF) assessment following NEMA protocols were simulated in a 6R-SuperArgus and a Biograph mMR scanner, comparing energy histograms, NEMA SF, and sensitivity for different energy windows. A comparison with real data reported in the literature on the Biograph scanner is also shown.Main results.NEMA SF and sensitivity estimated by UMC-PET where within few percent of PeneloPET predictions. The discrepancies can be attributed to small differences in the physics modeling. Running in a 11 GB GeForce RTX 2080 Ti GPU, UMC-PET is ∼1500 to ∼2000 times faster than PeneloPET executing in a single core Intel(R) Xeon(R) CPU W-2155 @ 3.30 GHz.Significance.UMC-PET employs a voxelized scheme for the scanner, patient adjacent objects (such as shieldings or the patient bed), and the activity distribution. This makes UMC-PET extremely flexible. Its high simulation speed allows applications such as MC scatter correction, faster SRM estimation for complex scanners, or even MC iterative image reconstruction.
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Affiliation(s)
- Pablo Galve
- Grupo de Física Nuclear, EMFTEL & IPARCOS, Universidad Complutense de Madrid, CEI Moncloa, 28040 Madrid, Spain
- Université Paris Cité, Inserm, PARCC, F-75015 Paris, France
- Health Research Institute of the Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Fernando Arias-Valcayo
- Grupo de Física Nuclear, EMFTEL & IPARCOS, Universidad Complutense de Madrid, CEI Moncloa, 28040 Madrid, Spain
- Health Research Institute of the Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Amaia Villa-Abaunza
- Grupo de Física Nuclear, EMFTEL & IPARCOS, Universidad Complutense de Madrid, CEI Moncloa, 28040 Madrid, Spain
| | - Paula Ibáñez
- Grupo de Física Nuclear, EMFTEL & IPARCOS, Universidad Complutense de Madrid, CEI Moncloa, 28040 Madrid, Spain
- Health Research Institute of the Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - José Manuel Udías
- Grupo de Física Nuclear, EMFTEL & IPARCOS, Universidad Complutense de Madrid, CEI Moncloa, 28040 Madrid, Spain
- Health Research Institute of the Hospital Clínico San Carlos (IdISSC), Madrid, Spain
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Rajagopal A, Natsuaki Y, Wangerin K, Hamdi M, An H, Sunderland JJ, Laforest R, Kinahan PE, Larson PEZ, Hope TA. Synthetic PET via Domain Translation of 3-D MRI. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2023; 7:333-343. [PMID: 37396797 PMCID: PMC10311993 DOI: 10.1109/trpms.2022.3223275] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Historically, patient datasets have been used to develop and validate various reconstruction algorithms for PET/MRI and PET/CT. To enable such algorithm development, without the need for acquiring hundreds of patient exams, in this article we demonstrate a deep learning technique to generate synthetic but realistic whole-body PET sinograms from abundantly available whole-body MRI. Specifically, we use a dataset of 56 18F-FDG-PET/MRI exams to train a 3-D residual UNet to predict physiologic PET uptake from whole-body T1-weighted MRI. In training, we implemented a balanced loss function to generate realistic uptake across a large dynamic range and computed losses along tomographic lines of response to mimic the PET acquisition. The predicted PET images are forward projected to produce synthetic PET (sPET) time-of-flight (ToF) sinograms that can be used with vendor-provided PET reconstruction algorithms, including using CT-based attenuation correction (CTAC) and MR-based attenuation correction (MRAC). The resulting synthetic data recapitulates physiologic 18F-FDG uptake, e.g., high uptake localized to the brain and bladder, as well as uptake in liver, kidneys, heart, and muscle. To simulate abnormalities with high uptake, we also insert synthetic lesions. We demonstrate that this sPET data can be used interchangeably with real PET data for the PET quantification task of comparing CTAC and MRAC methods, achieving ≤ 7.6% error in mean-SUV compared to using real data. These results together show that the proposed sPET data pipeline can be reasonably used for development, evaluation, and validation of PET/MRI reconstruction methods.
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Affiliation(s)
- Abhejit Rajagopal
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA 94158 USA
| | - Yutaka Natsuaki
- Department of Radiation Oncology, University of New Mexico, Albuquerque, NM 87131 USA
| | | | - Mahdjoub Hamdi
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63130 USA
| | - Hongyu An
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63130 USA
| | - John J Sunderland
- Department of Radiology, The University of Iowa, Iowa City, IA 52242 USA
| | - Richard Laforest
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63130 USA
| | - Paul E Kinahan
- Department of Radiology, University of Washington, Seattle, WA 98195 USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA 94158 USA
| | - Thomas A Hope
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA 94158 USA
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Jha AK, Bradshaw TJ, Buvat I, Hatt M, Kc P, Liu C, Obuchowski NF, Saboury B, Slomka PJ, Sunderland JJ, Wahl RL, Yu Z, Zuehlsdorff S, Rahmim A, Boellaard R. Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE Guidelines). J Nucl Med 2022; 63:1288-1299. [PMID: 35618476 PMCID: PMC9454473 DOI: 10.2967/jnumed.121.263239] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 05/11/2022] [Indexed: 01/26/2023] Open
Abstract
An important need exists for strategies to perform rigorous objective clinical-task-based evaluation of artificial intelligence (AI) algorithms for nuclear medicine. To address this need, we propose a 4-class framework to evaluate AI algorithms for promise, technical task-specific efficacy, clinical decision making, and postdeployment efficacy. We provide best practices to evaluate AI algorithms for each of these classes. Each class of evaluation yields a claim that provides a descriptive performance of the AI algorithm. Key best practices are tabulated as the RELAINCE (Recommendations for EvaLuation of AI for NuClear medicinE) guidelines. The report was prepared by the Society of Nuclear Medicine and Molecular Imaging AI Task Force Evaluation team, which consisted of nuclear-medicine physicians, physicists, computational imaging scientists, and representatives from industry and regulatory agencies.
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Affiliation(s)
- Abhinav K Jha
- Department of Biomedical Engineering and Mallinckrodt Institute of Radiology, Washington University in St. Louis, Missouri;
| | - Tyler J Bradshaw
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Irène Buvat
- LITO, Institut Curie, Université PSL, U1288 Inserm, Orsay, France
| | - Mathieu Hatt
- LaTiM, INSERM, UMR 1101, Univ Brest, Brest, France
| | - Prabhat Kc
- Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland
| | - Chi Liu
- Department of Radiology and Biomedical Imaging, Yale University, Connecticut
| | | | - Babak Saboury
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Maryland
| | - Piotr J Slomka
- Department of Imaging, Medicine, and Cardiology, Cedars-Sinai Medical Center, California
| | | | - Richard L Wahl
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, Missouri
| | - Zitong Yu
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri
| | | | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Canada; and
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centers, Netherlands
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Auditore L, Pistone D, Amato E, Italiano A. Monte Carlo methods in nuclear medicine. Nucl Med Mol Imaging 2022. [DOI: 10.1016/b978-0-12-822960-6.00136-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
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Barati S, Enferadi M, Sarkar S, Geramifar P. The effect of magnetic field strength on the positron range and projected annihilation artifact in integrated PET/MR systems: A GATE Monte Carlo study. Med Phys 2021; 48:7712-7724. [PMID: 34706098 DOI: 10.1002/mp.15313] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 09/19/2021] [Accepted: 10/12/2021] [Indexed: 12/11/2022] Open
Abstract
PURPOSE With improvements in positron emission tomography/magnetic resonance imaging (PET/MRI) over the last decade, there is a need to investigate the projected annihilation (shine-through) artifact and resolution impact for different PET radiopharmaceuticals, magnetic field (MF) strengths, and tissues. METHODS The GATE Monte Carlo (MC) simulation was used to simulate the annihilation distribution of positrons in different tissues and MFs. The positron distribution was studied in magnetic field (MF) intensities up to 15 T for 11 C, 13 N, 15 O, 18 F, 68 Ga, and 82 Rb. Moreover, the image quality in terms of the occurrence of projected annihilation artifacts was investigated using the 4D anthropomorphic digital extended cardiac-torso (XCAT) phantom. RESULTS Positron ranges were restricted across the directions perpendicular to the MF, but no change along the direction of the MF was detected. The projected annihilation artifacts were observed with the presence of MF in the sagittal and coronal view of PET images prepared from the XCAT phantom. The intensity of artifact was constant in MFs higher than 3 T. The significant effect of the MF on resolution improvement was observed in soft tissue for 68 Ga in 7 T and 82 Rb in 3 and 7 T, while higher MFs have no impact on resolution. The improvement of resolution in the lung tissue was observed for the medium- and high-energy radionuclides in 7 T MF. CONCLUSION The MF can create the projected annihilation artifact in the boundary of air cavities and other tissues for medium- and high-energy radionuclides especially for 68 Ga in clinical studies. In addition, the strength of the MFs more than 3 T was ineffective on the intensity of the projected annihilation artifact. In a clinical PET/MR scanner, MF has remarkable spatial resolution improvement in lung tissue, especially for medium- and high-energy radionuclides, and negligible effect in bone and soft tissue for most radionuclides.
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Affiliation(s)
- Sepideh Barati
- Department of Nuclear Medicine, Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Milad Enferadi
- Division of Molecular Imaging and Theranostics, Department of Nuclear Medicine, University Hospital Salzburg, Paracelsus Medical University, Salzburg, Austria
| | - Saeed Sarkar
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
| | - Parham Geramifar
- Research Center for Nuclear Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
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Jha AK, Myers KJ, Obuchowski NA, Liu Z, Rahman MA, Saboury B, Rahmim A, Siegel BA. Objective Task-Based Evaluation of Artificial Intelligence-Based Medical Imaging Methods:: Framework, Strategies, and Role of the Physician. PET Clin 2021; 16:493-511. [PMID: 34537127 DOI: 10.1016/j.cpet.2021.06.013] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Artificial intelligence-based methods are showing promise in medical imaging applications. There is substantial interest in clinical translation of these methods, requiring that they be evaluated rigorously. We lay out a framework for objective task-based evaluation of artificial intelligence methods. We provide a list of available tools to conduct this evaluation. We outline the important role of physicians in conducting these evaluation studies. The examples in this article are proposed in the context of PET scans with a focus on evaluating neural network-based methods. However, the framework is also applicable to evaluate other medical imaging modalities and other types of artificial intelligence methods.
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Affiliation(s)
- Abhinav K Jha
- Department of Biomedical Engineering, Mallinckrodt Institute of Radioly, Alvin J. Siteman Cancer Center, Washington University in St. Louis, 510 S Kingshighway Boulevard, St Louis, MO 63110, USA.
| | - Kyle J Myers
- Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration (FDA), Silver Spring, MD, USA
| | | | - Ziping Liu
- Department of Biomedical Engineering, Washington University in St. Louis, 1 Brookings Drive, St Louis, MO 63130, USA
| | - Md Ashequr Rahman
- Department of Biomedical Engineering, Washington University in St. Louis, 1 Brookings Drive, St Louis, MO 63130, USA
| | - Babak Saboury
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA
| | - Arman Rahmim
- Department of Radiology, Department of Physics, University of British Columbia, BC Cancer, BC Cancer Research Institute, 675 West 10th Avenue, Office 6-112, Vancouver, British Columbia V5Z 1L3, Canada
| | - Barry A Siegel
- Division of Nuclear Medicine, Mallinckrodt Institute of Radiology, Alvin J. Siteman Cancer Center, Washington University School of Medicine, 510 S Kingshighway Boulevard #956, St Louis, MO 63110, USA
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11
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Park H, Paganetti H, Schuemann J, Jia X, Min CH. Monte Carlo methods for device simulations in radiation therapy. Phys Med Biol 2021; 66:10.1088/1361-6560/ac1d1f. [PMID: 34384063 PMCID: PMC8996747 DOI: 10.1088/1361-6560/ac1d1f] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 08/12/2021] [Indexed: 11/12/2022]
Abstract
Monte Carlo (MC) simulations play an important role in radiotherapy, especially as a method to evaluate physical properties that are either impossible or difficult to measure. For example, MC simulations (MCSs) are used to aid in the design of radiotherapy devices or to understand their properties. The aim of this article is to review the MC method for device simulations in radiation therapy. After a brief history of the MC method and popular codes in medical physics, we review applications of the MC method to model treatment heads for neutral and charged particle radiation therapy as well as specific in-room devices for imaging and therapy purposes. We conclude by discussing the impact that MCSs had in this field and the role of MC in future device design.
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Affiliation(s)
- Hyojun Park
- Department of Radiation Convergence Engineering, Yonsei University, Wonju, Republic of Korea
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States of America
| | - Jan Schuemann
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States of America
| | - Xun Jia
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX 75235, United States of America
| | - Chul Hee Min
- Department of Radiation Convergence Engineering, Yonsei University, Wonju, Republic of Korea
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Meng F, Shi Y, Li C, Li L, Qin W, Zhu S. Hybrid model of photon propagation based on the analytical and Monte Carlo methods for a dual-head PET system. Phys Med Biol 2021; 66. [PMID: 34330106 DOI: 10.1088/1361-6560/ac195b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Accepted: 07/30/2021] [Indexed: 11/12/2022]
Abstract
The construction of photon propagation has a close relationship with the quality of reconstructed images. The classical Monte Carlo (MC) based method can model the photon propagation precisely, but it is time-consuming. The analytical method can often quickly construct a model, but its precision is a problem. How to fully exploit the advantages of the MC simulation and analytical model is an open problem. Inspired by the characteristics of the depth of interaction (DOI) detectors, which can help confirm the deposited position of a photon with DOI-encoding technology, we virtually discretize each crystal into several subcrystals to obtain the statistical distribution by MC-based simulation. Then, the statistical distribution is combined with a spatially variant solid-angle model. This combination strategy provides a hybrid model to describe photon propagation with relatively high accuracy and low computational cost. Three discretization schemes are compared to optimize the constructed photon propagation model. Several experiments are carried out to evaluate the performance of the proposed hybrid method. The metrics of full width at half maximum (FWHM), contrast recovery (CR), and coefficient of variation (COV) are adopted to quantitate the imaging results. The classical MC-based method is compared as a gold-standard reference. When a crystal is divided into two discretized positions, the convergent tendencies of CRs and COVs are consistent with that based on MC simulation method, respectively. In terms of FWHMs, the resolutions of using the MC-based model and the proposed hybrid model are 0.71 mm and 0.68 mm in the direction parallel to the detector head, respectively. This indicates the potential of the proposed method in positron emission tomography imaging.
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Affiliation(s)
- Fanzhen Meng
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
| | - Yu Shi
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
| | - Chenfeng Li
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
| | - Lei Li
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
| | - Wei Qin
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
| | - Shouping Zhu
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
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Paredes-Pacheco J, López-González FJ, Silva-Rodríguez J, Efthimiou N, Niñerola-Baizán A, Ruibal Á, Roé-Vellvé N, Aguiar P. SimPET-An open online platform for the Monte Carlo simulation of realistic brain PET data. Validation for 18 F-FDG scans. Med Phys 2021; 48:2482-2493. [PMID: 33713354 PMCID: PMC8252452 DOI: 10.1002/mp.14838] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 03/03/2021] [Accepted: 03/04/2021] [Indexed: 12/11/2022] Open
Abstract
Purpose SimPET (www.sim‐pet.org) is a free cloud‐based platform for the generation of realistic brain positron emission tomography (PET) data. In this work, we introduce the key features of the platform. In addition, we validate the platform by performing a comparison between simulated healthy brain FDG‐PET images and real healthy subject data for three commercial scanners (GE Advance NXi, GE Discovery ST, and Siemens Biograph mCT). Methods The platform provides a graphical user interface to a set of automatic scripts taking care of the code execution for the phantom generation, simulation (SimSET), and tomographic image reconstruction (STIR). We characterize the performance using activity and attenuation maps derived from PET/CT and MRI data of 25 healthy subjects acquired with a GE Discovery ST. We then use the created maps to generate synthetic data for the GE Discovery ST, the GE Advance NXi, and the Siemens Biograph mCT. The validation was carried out by evaluating Bland‐Altman differences between real and simulated images for each scanner. In addition, SPM voxel‐wise comparison was performed to highlight regional differences. Examples for amyloid PET and for the generation of ground‐truth pathological patients are included. Results The platform can be efficiently used for generating realistic simulated FDG‐PET images in a reasonable amount of time. The validation showed small differences between SimPET and acquired FDG‐PET images, with errors below 10% for 98.09% (GE Discovery ST), 95.09% (GE Advance NXi), and 91.35% (Siemens Biograph mCT) of the voxels. Nevertheless, our SPM analysis showed significant regional differences between the simulated images and real healthy patients, and thus, the use of the platform for converting control subject databases between different scanners requires further investigation. Conclusions The presented platform can potentially allow scientists in clinical and research settings to perform MC simulation experiments without the need for high‐end hardware or advanced computing knowledge and in a reasonable amount of time.
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Affiliation(s)
- José Paredes-Pacheco
- Radiology and Psychiatry Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain.,Molecular Imaging Unit, Centro de Investigaciones Médico-Sanitarias, General Foundation of the University of Málaga, Málaga, Spain
| | - Francisco Javier López-González
- Radiology and Psychiatry Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain.,Molecular Imaging Unit, Centro de Investigaciones Médico-Sanitarias, General Foundation of the University of Málaga, Málaga, Spain
| | - Jesús Silva-Rodríguez
- Nuclear Medicine Department & Molecular Imaging Research Group, University Hospital (SERGAS) & Health Research Institute of Santiago de Compostela (IDIS), Galicia, Spain.,R&D Department, Qubiotech Health Intelligence SL, A Coruña, Galicia, Spain
| | - Nikos Efthimiou
- Positron Emission Tomography Research Centre, University of Hull, Hull, HU6 7RX, UK
| | - Aida Niñerola-Baizán
- Nuclear Medicine Department, Hospital Clinic Barcelona, Universitat de Barcelona, Barcelona, Spain.,Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Álvaro Ruibal
- Radiology and Psychiatry Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain.,Nuclear Medicine Department & Molecular Imaging Research Group, University Hospital (SERGAS) & Health Research Institute of Santiago de Compostela (IDIS), Galicia, Spain
| | - Núria Roé-Vellvé
- Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Pablo Aguiar
- Radiology and Psychiatry Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain.,Nuclear Medicine Department & Molecular Imaging Research Group, University Hospital (SERGAS) & Health Research Institute of Santiago de Compostela (IDIS), Galicia, Spain
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Ahmed AM, Chacon A, Rutherford H, Akamatsu G, Mohammadi A, Nishikido F, Tashima H, Yoshida E, Yamaya T, Franklin DR, Rosenfeld A, Guatelli S, Safavi-Naeini M. A validated Geant4 model of a whole-body PET scanner with four-layer DOI detectors. ACTA ACUST UNITED AC 2020; 65:235051. [DOI: 10.1088/1361-6560/abaa24] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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15
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López-Montes A, Galve P, Udias JM, Cal-González J, Vaquero JJ, Desco M, Herraiz JL. Real-Time 3D PET Image with Pseudoinverse Reconstruction. APPLIED SCIENCES-BASEL 2020. [DOI: https://doi.org/10.3390/app10082829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Real-time positron emission tomography (PET) may provide information from first-shot images, enable PET-guided biopsies, and allow awake animal studies. Fully-3D iterative reconstructions yield the best images in PET, but they are too slow for real-time imaging. Analytical methods such as Fourier back projection (FBP) are very fast, but yield images of poor quality with artifacts due to noise or data incompleteness. In this work, an image reconstruction based on the pseudoinverse of the system response matrix (SRM) is presented. w. To implement the pseudoinverse method, the reconstruction problem is separated into two stages. First, the axial part of the SRM is pseudo-inverted (PINV) to rebin the 3D data into 2D datasets. Then, the resulting 2D slices can be reconstructed with analytical methods or by applying the pseudoinverse algorithm again. The proposed two-step PINV reconstruction yielded good-quality images at a rate of several frames per second, compatible with real time applications. Furthermore, extremely fast direct PINV reconstruction of projections of the 3D image collapsed along specific directions can be implemented.
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Abstract
Real-time positron emission tomography (PET) may provide information from first-shot images, enable PET-guided biopsies, and allow awake animal studies. Fully-3D iterative reconstructions yield the best images in PET, but they are too slow for real-time imaging. Analytical methods such as Fourier back projection (FBP) are very fast, but yield images of poor quality with artifacts due to noise or data incompleteness. In this work, an image reconstruction based on the pseudoinverse of the system response matrix (SRM) is presented. w. To implement the pseudoinverse method, the reconstruction problem is separated into two stages. First, the axial part of the SRM is pseudo-inverted (PINV) to rebin the 3D data into 2D datasets. Then, the resulting 2D slices can be reconstructed with analytical methods or by applying the pseudoinverse algorithm again. The proposed two-step PINV reconstruction yielded good-quality images at a rate of several frames per second, compatible with real time applications. Furthermore, extremely fast direct PINV reconstruction of projections of the 3D image collapsed along specific directions can be implemented.
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Lai Y, Zhong Y, Chalise A, Shao Y, Jin M, Jia X, Chi Y. gPET: a GPU-based, accurate and efficient Monte Carlo simulation tool for PET. Phys Med Biol 2019; 64:245002. [PMID: 31711051 PMCID: PMC10593186 DOI: 10.1088/1361-6560/ab5610] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Monte Carlo (MC) simulation method plays an essential role in the refinement and development of positron emission tomography (PET) systems. However, most existing MC simulation packages suffer from long execution time for practical PET simulations. To fully address this issue, we developed and validated gPET, a graphics processing unit (GPU)-based MC simulation tool for PET. gPET was built on the NVidia CUDA platform. The simulation process was modularized into three functional parts and carried out by the GPU parallel threads: (1) source management, including positron decay, transport and annihilation; (2) gamma transport inside the phantom; and (3) signal detection and processing inside the detector. A hybrid of voxelized (for patient phantoms) and parametrized (for detectors) geometries were employed to sufficiently support particle navigations. Multiple inputs and outputs were available. Hence, a user can flexibly examine different aspects of a PET simulation. We evaluated the performance of gPET in three test cases with benchmark work from GATE8.0, in terms of the testing of the functional modules, the physics models used for gamma transport inside the detector, and the geometric configuration of an irregularly shaped PET detector. Both accuracy and efficiency were quantified. In all test cases, the differences between gPET and GATE for the coincidences with respect to the energy and crystal index distributions are below 3.18% and 2.54%, respectively. The speedup factor is 500 for gPET on a single Titan Xp GPU (1.58 GHz) over GATE8.0 on a single core of Intel i7-6850K CPU (3.6 GHz) for all test cases. In summary, gPET is an accurate and efficient MC simulation tool for PET.
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Affiliation(s)
- Youfang Lai
- Department of Physics, University of Texas at Arlington, Arlington, TX 76019, United States of America
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18
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Pfaehler E, De Jong JR, Dierckx RAJO, van Velden FHP, Boellaard R. SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool. EJNMMI Phys 2018; 5:16. [PMID: 30225675 PMCID: PMC6141406 DOI: 10.1186/s40658-018-0215-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Accepted: 04/25/2018] [Indexed: 01/28/2023] Open
Abstract
Background Positron-emission tomography (PET) simulators are frequently used for development and performance evaluation of segmentation methods or quantitative uptake metrics. To date, most PET simulation tools are based on Monte Carlo simulations, which are computationally demanding. Other analytical simulation tools lack the implementation of time of flight (TOF) or resolution modelling (RM). In this study, a fast and easy-to-use PET simulation-reconstruction package, SiMulAtion and ReconsTruction (SMART)-PET, is developed and validated, which includes both TOF and RM. SMART-PET, its documentation and instructions to calibrate the tool to a specific PET/CT system are available on Zenodo. SMART-PET allows the fast generation of 3D PET images. As input, it requires one image representing the activity distribution and one representing the corresponding CT image/attenuation map. It allows the user to adjust different parameters, such as reconstruction settings (TOF/RM), noise level or scan duration. Furthermore, a random spatial shift can be included, representing patient repositioning. To evaluate the tool, simulated images were compared with real scan data of the NEMA NU 2 image quality phantom. The scan was acquired as a 60-min list-mode scan and reconstructed with and without TOF and/or RM. For every reconstruction setting, ten statistically equivalent images, representing 30, 60, 120 and 300 s scan duration, were generated. Simulated and real-scan data were compared regarding coefficient of variation in the phantom background and activity recovery coefficients (RCs) of the spheres. Furthermore, standard deviation images of each of the ten statistically equivalent images were compared. Results SMART-PET produces images comparable to actual phantom data. The image characteristics of simulated and real PET images varied in similar ways as function of reconstruction protocols and noise levels. The change in image noise with variation of simulated TOF settings followed the theoretically expected behaviour. RC as function of sphere size agreed within 0.3–11% between simulated and actual phantom data. Conclusions SMART-PET allows for rapid and easy simulation of PET data. The user can change various acquisition and reconstruction settings (including RM and TOF) and noise levels. The images obtained show similar image characteristics as those seen in actual phantom data. Electronic supplementary material The online version of this article (10.1186/s40658-018-0215-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Elisabeth Pfaehler
- Departments of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Johan R De Jong
- Departments of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Rudi A J O Dierckx
- Departments of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Floris H P van Velden
- Department of Radiology, Section of Nuclear Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Ronald Boellaard
- Departments of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. .,Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands.
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Abushab KM, Herraiz JL, Vicente E, Cal-Gonzalez J, Espana S, Vaquero JJ, Jakoby BW, Udias JM. Evaluation of PeneloPET Simulations of Biograph PET/CT Scanners. IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2016. [DOI: 10.1109/tns.2016.2527789] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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20
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Fraile L, Herraiz J, Udías J, Cal-González J, Corzo P, España S, Herranz E, Pérez-Liva M, Picado E, Vicente E, Muñoz-Martín A, Vaquero J. Experimental validation of gallium production and isotope-dependent positron range correction in PET. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2016. [DOI: 10.1016/j.nima.2016.01.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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21
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System models for PET statistical iterative reconstruction: A review. Comput Med Imaging Graph 2016; 48:30-48. [DOI: 10.1016/j.compmedimag.2015.12.003] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Revised: 10/09/2015] [Accepted: 12/09/2015] [Indexed: 02/03/2023]
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22
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Kamińska D, Gajos A, Czerwiński E, Alfs D, Bednarski T, Białas P, Curceanu C, Dulski K, Głowacz B, Gupta-Sharma N, Gorgol M, Hiesmayr BC, Jasińska B, Korcyl G, Kowalski P, Krzemień W, Krawczyk N, Kubicz E, Mohammed M, Niedźwiecki S, Pawlik-Niedźwiecka M, Raczyński L, Rudy Z, Silarski M, Wieczorek A, Wiślicki W, Zgardzińska B, Zieliński M, Moskal P. A feasibility study of ortho-positronium decays measurement with the J-PET scanner based on plastic scintillators. THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS 2016; 76:445. [PMID: 27547122 PMCID: PMC4978780 DOI: 10.1140/epjc/s10052-016-4294-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2016] [Accepted: 08/01/2016] [Indexed: 05/13/2023]
Abstract
We present a study of the application of the Jagiellonian positron emission tomograph (J-PET) for the registration of gamma quanta from decays of ortho-positronium (o-Ps). The J-PET is the first positron emission tomography scanner based on organic scintillators in contrast to all current PET scanners based on inorganic crystals. Monte Carlo simulations show that the J-PET as an axially symmetric and high acceptance scanner can be used as a multi-purpose detector well suited to pursue research including e.g. tests of discrete symmetries in decays of ortho-positronium in addition to the medical imaging. The gamma quanta originating from o-Ps decay interact in the plastic scintillators predominantly via the Compton effect, making the direct measurement of their energy impossible. Nevertheless, it is shown in this paper that the J-PET scanner will enable studies of the [Formula: see text] decays with angular and energy resolution equal to [Formula: see text] and [Formula: see text], respectively. An order of magnitude shorter decay time of signals from plastic scintillators with respect to the inorganic crystals results not only in better timing properties crucial for the reduction of physical and instrumental background, but also suppresses significantly the pile-ups, thus enabling compensation of the lower efficiency of the plastic scintillators by performing measurements with higher positron source activities.
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Affiliation(s)
- D. Kamińska
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - A. Gajos
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - E. Czerwiński
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - D. Alfs
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - T. Bednarski
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - P. Białas
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - C. Curceanu
- INFN, Laboratori Nazionali di Frascati, CP 13, Via E. Fermi 40, 00044 Frascati, Italy
| | - K. Dulski
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - B. Głowacz
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - N. Gupta-Sharma
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - M. Gorgol
- Department of Nuclear Methods, Institute of Physics, Maria Curie-Sklodowska University, Pl. M. Curie-Sklodowskiej 1, 20-031 Lublin, Poland
| | - B. C. Hiesmayr
- Faculty of Physics, University of Vienna, Boltzmanngasse 5, 1090 Vienna, Austria
| | - B. Jasińska
- Department of Nuclear Methods, Institute of Physics, Maria Curie-Sklodowska University, Pl. M. Curie-Sklodowskiej 1, 20-031 Lublin, Poland
| | - G. Korcyl
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - P. Kowalski
- Świerk Computing Centre, National Centre for Nuclear Research, 05-400 Otwock-Świerk, Poland
| | - W. Krzemień
- High Energy Department, National Centre for Nuclear Research, 05-400 Otwock-Świerk, Poland
| | - N. Krawczyk
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - E. Kubicz
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - M. Mohammed
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - Sz. Niedźwiecki
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - M. Pawlik-Niedźwiecka
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - L. Raczyński
- Świerk Computing Centre, National Centre for Nuclear Research, 05-400 Otwock-Świerk, Poland
| | - Z. Rudy
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - M. Silarski
- INFN, Laboratori Nazionali di Frascati, CP 13, Via E. Fermi 40, 00044 Frascati, Italy
| | - A. Wieczorek
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - W. Wiślicki
- Świerk Computing Centre, National Centre for Nuclear Research, 05-400 Otwock-Świerk, Poland
| | - B. Zgardzińska
- Department of Nuclear Methods, Institute of Physics, Maria Curie-Sklodowska University, Pl. M. Curie-Sklodowskiej 1, 20-031 Lublin, Poland
| | - M. Zieliński
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
| | - P. Moskal
- Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, S. Łojasiewicza 11, 30-348 Kraków, Poland
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Cal-González J, Pérez-Liva M, Herraiz JL, Vaquero JJ, Desco M, Udías JM. Tissue-Dependent and Spatially-Variant Positron Range Correction in 3D PET. IEEE TRANSACTIONS ON MEDICAL IMAGING 2015; 34:2394-403. [PMID: 26011878 DOI: 10.1109/tmi.2015.2436711] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Positron range (PR) is a significant factor that limits PET image resolution, especially with some radionuclides currently used in clinical and preclinical studies such as (82)Rb, (124)I and (68)Ga. The use of an accurate model of the PR in the image reconstruction may minimize its impact on the image quality. Nevertheless, PR distributions are difficult to model, as they may be different at each voxel and direction, depending on the materials that the positron flies through. Several approximated methods have been proposed, considering only one or several propagating media without taking into account boundaries effects. In some regions, like lungs or trachea, these methods may not be accurate enough and yield artifacts. In this work, we present an efficient method to accurately incorporate spatially-variant PR corrections. The method is based on pre-computing voxel-dependent PR kernels using a CT or a manually segmented image, and a model of the dependence of the PR on each material derived from Monte Carlo simulations. The images are convoluted with these kernels in the forward-projection step of the iterative reconstruction algorithm. This implementation of the algorithm adds a modest overhead to the overall reconstruction time and it obtains artifact-free PR-corrected images, even when the activity is concentrated at tissue boundaries with extreme changes of density. We verified the method with the preclinical Argus PET/CT scanner, but it can be also applied to other scanners and improve the image quality in clinical PET studies using isotopes with large PR.
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Cal-González J, Moore SC, Park MA, Herraiz JL, Vaquero JJ, Desco M, Udias JM. Improved quantification for local regions of interest in preclinical PET imaging. Phys Med Biol 2015; 60:7127-49. [PMID: 26334312 PMCID: PMC4593622 DOI: 10.1088/0031-9155/60/18/7127] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
In Positron Emission Tomography, there are several causes of quantitative inaccuracy, such as partial volume or spillover effects. The impact of these effects is greater when using radionuclides that have a large positron range, e.g. (68)Ga and (124)I, which have been increasingly used in the clinic. We have implemented and evaluated a local projection algorithm (LPA), originally evaluated for SPECT, to compensate for both partial-volume and spillover effects in PET. This method is based on the use of a high-resolution CT or MR image, co-registered with a PET image, which permits a high-resolution segmentation of a few tissues within a volume of interest (VOI) centered on a region within which tissue-activity values need to be estimated. The additional boundary information is used to obtain improved activity estimates for each tissue within the VOI, by solving a simple inversion problem. We implemented this algorithm for the preclinical Argus PET/CT scanner and assessed its performance using the radionuclides (18)F, (68)Ga and (124)I. We also evaluated and compared the results obtained when it was applied during the iterative reconstruction, as well as after the reconstruction as a postprocessing procedure. In addition, we studied how LPA can help to reduce the 'spillover contamination', which causes inaccurate quantification of lesions in the immediate neighborhood of large, 'hot' sources. Quantification was significantly improved by using LPA, which provided more accurate ratios of lesion-to-background activity concentration for hot and cold regions. For (18)F, the contrast was improved from 3.0 to 4.0 in hot lesions (when the true ratio was 4.0) and from 0.16 to 0.06 in cold lesions (true ratio = 0.0), when using the LPA postprocessing. Furthermore, activity values estimated within the VOI using LPA during reconstruction were slightly more accurate than those obtained by post-processing, while also visually improving the image contrast and uniformity within the VOI.
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Affiliation(s)
- J. Cal-González
- Grupo de Física Nuclear, Dpto. de Física Atómica, Molecular y Nuclear, Universidad Complutense de Madrid, CEI Moncloa, Spain
| | - S. C. Moore
- Division of Nuclear Medicine, Department of Radiology, Harvard Medical School and Brigham and Women’s Hospital. Boston, USA
| | - M.-A. Park
- Division of Nuclear Medicine, Department of Radiology, Harvard Medical School and Brigham and Women’s Hospital. Boston, USA
| | - J. L. Herraiz
- Grupo de Física Nuclear, Dpto. de Física Atómica, Molecular y Nuclear, Universidad Complutense de Madrid, CEI Moncloa, Spain
- Madrid-MIT M+Visión Consortium, Research Lab. of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - J. J. Vaquero
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Spain
| | - M. Desco
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Spain
- Unidad de Medicina y Cirugía Experimental, Hospital General Universitario Gregorio Marañón, CIBERSAM, Madrid, Spain
| | - J. M. Udias
- Grupo de Física Nuclear, Dpto. de Física Atómica, Molecular y Nuclear, Universidad Complutense de Madrid, CEI Moncloa, Spain
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Cal-González J, Moore SC, Park MA, Herraiz JL, Vaquero JJ, Desco M, Udias JM. Improved quantification for local regions of interest in preclinical PET imaging. Phys Med Biol 2015. [DOI: https://doi.org/10.1088/0031-9155/60/18/7127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Berthon B, Häggström I, Apte A, Beattie BJ, Kirov AS, Humm JL, Marshall C, Spezi E, Larsson A, Schmidtlein CR. PETSTEP: Generation of synthetic PET lesions for fast evaluation of segmentation methods. Phys Med 2015; 31:969-980. [PMID: 26321409 PMCID: PMC4888783 DOI: 10.1016/j.ejmp.2015.07.139] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2015] [Revised: 07/07/2015] [Accepted: 07/08/2015] [Indexed: 11/25/2022] Open
Abstract
Purpose This work describes PETSTEP (PET Simulator of Tracers via Emission Projection): a faster and more accessible alternative to Monte Carlo (MC) simulation generating realistic PET images, for studies assessing image features and segmentation techniques. Methods PETSTEP was implemented within Matlab as open source software. It allows generating three-dimensional PET images from PET/CT data or synthetic CT and PET maps, with user-drawn lesions and user-set acquisition and reconstruction parameters. PETSTEP was used to reproduce images of the NEMA body phantom acquired on a GE Discovery 690 PET/CT scanner, and simulated with MC for the GE Discovery LS scanner, and to generate realistic Head and Neck scans. Finally the sensitivity (S) and Positive Predictive Value (PPV) of three automatic segmentation methods were compared when applied to the scanner-acquired and PETSTEP-simulated NEMA images. Results PETSTEP produced 3D phantom and clinical images within 4 and 6 min respectively on a single core 2.7 GHz computer. PETSTEP images of the NEMA phantom had mean intensities within 2% of the scanner-acquired image for both background and largest insert, and 16% larger background Full Width at Half Maximum. Similar results were obtained when comparing PETSTEP images to MC simulated data. The S and PPV obtained with simulated phantom images were statistically significantly lower than for the original images, but led to the same conclusions with respect to the evaluated segmentation methods. Conclusions PETSTEP allows fast simulation of synthetic images reproducing scanner-acquired PET data and shows great promise for the evaluation of PET segmentation methods.
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Affiliation(s)
- Beatrice Berthon
- Wales Research & Diagnostic PET Imaging Centre, Cardiff University, Cardiff, Wales, UK.
| | - Ida Häggström
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Aditya Apte
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA
| | - Bradley J Beattie
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA
| | - Assen S Kirov
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA
| | - John L Humm
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA
| | - Christopher Marshall
- Wales Research & Diagnostic PET Imaging Centre, Cardiff University, Cardiff, Wales, UK
| | - Emiliano Spezi
- School of Engineering, Cardiff University, Cardiff, Wales, UK
| | - Anne Larsson
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - C Ross Schmidtlein
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA
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Cal-González J, Lage E, Herranz E, Vicente E, Udias JM, Moore SC, Park MA, Dave SR, Parot V, Herraiz JL. Simulation of triple coincidences in PET. Phys Med Biol 2015; 60:117-36. [PMID: 25479147 DOI: 10.1088/0031-9155/60/1/117] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Although current PET scanners are designed and optimized to detect double coincidence events, there is a significant amount of triple coincidences in any PET acquisition. Triple coincidences may arise from causes such as: inter-detector scatter (IDS), random triple interactions (RT), or the detection of prompt gamma rays in coincidence with annihilation photons when non-pure positron-emitting radionuclides are used (β(+)γ events). Depending on the data acquisition settings of the PET scanner, these triple events are discarded or processed as a set of double coincidences if the energy of the three detected events is within the scanner's energy window. This latter option introduces noise in the data, as at most, only one of the possible lines-of-response defined by triple interactions corresponds to the line along which the decay occurred. Several novel works have pointed out the possibility of using triple events to increase the sensitivity of PET scanners or to expand PET imaging capabilities by allowing differentiation between radiotracers labeled with non-pure and pure positron-emitting radionuclides. In this work, we extended the Monte Carlo simulator PeneloPET to assess the proportion of triple coincidences in PET acquisitions and to evaluate their possible applications. We validated the results of the simulator against experimental data acquired with a modified version of a commercial preclinical PET/CT scanner, which was enabled to acquire and process triple-coincidence events. We used as figures of merit the energy spectra for double and triple coincidences and the triples-to-doubles ratio for different energy windows and radionuclides. After validation, the simulator was used to predict the relative quantity of triple-coincidence events in two clinical scanners assuming different acquisition settings. Good agreement between simulations and preclinical experiments was found, with differences below 10% for most of the observables considered. For clinical scanners and pure positron emitters, we found that around 10% of the processed double events come from triple coincidences, increasing this ratio substantially for non-pure emitters (around 25% for (124)I and > 50% for (86)Y). For radiotracers labeled with (18)F we found that the relative quantity of IDS events in standard acquisitions is around 18% for the preclinical scanner and between 14 and 22% for the clinical scanners. For non-pure positron emitters like (124)I, we found a β(+)γ triples-to-doubles ratio of 2.5% in the preclinical scanner and of up to 4% in the clinical scanners.
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Affiliation(s)
- J Cal-González
- Grupo de Física Nuclear, Dpto. de Física Atómica, Molecular y Nuclear, Universidad Complutense de Madrid, CEI Moncloa, Spain
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Popota FD, Aguiar P, España S, Lois C, Udias JM, Ros D, Pavia J, Gispert JD. Monte Carlo simulations versus experimental measurements in a small animal PET system. A comparison in the NEMA NU 4-2008 framework. Phys Med Biol 2015; 60:151-62. [PMID: 25479341 DOI: 10.1088/0031-9155/60/1/151] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
In this work a comparison between experimental and simulated data using GATE and PeneloPET Monte Carlo simulation packages is presented. All simulated setups, as well as the experimental measurements, followed exactly the guidelines of the NEMA NU 4-2008 standards using the microPET R4 scanner. The comparison was focused on spatial resolution, sensitivity, scatter fraction and counting rates performance. Both GATE and PeneloPET showed reasonable agreement for the spatial resolution when compared to experimental measurements, although they lead to slight underestimations for the points close to the edge. High accuracy was obtained between experiments and simulations of the system's sensitivity and scatter fraction for an energy window of 350-650 keV, as well as for the counting rate simulations. The latter was the most complicated test to perform since each code demands different specifications for the characterization of the system's dead time. Although simulated and experimental results were in excellent agreement for both simulation codes, PeneloPET demanded more information about the behavior of the real data acquisition system. To our knowledge, this constitutes the first validation of these Monte Carlo codes for the full NEMA NU 4-2008 standards for small animal PET imaging systems.
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Affiliation(s)
- F D Popota
- Unitat de Biofisica i Bioenginyeria, Universitat de Barcelona, Barcelona, Spain. Universidad de Pompeu Fabra, Barcelona, Spain
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Cal-González J, Lage E, Herranz E, Vicente E, Udias JM, Moore SC, Park MA, Dave SR, Parot V, Herraiz JL. Simulation of triple coincidences in PET. Phys Med Biol 2014. [DOI: https://doi.org/10.1088/0031-9155/60/1/117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Gianoli C, Riboldi M, Kurz C, De Bernardi E, Bauer J, Fontana G, Ciocca M, Parodi K, Baroni G. PET-CT scanner characterization for PET raw data use in biomedical research. Comput Med Imaging Graph 2014; 38:358-68. [DOI: 10.1016/j.compmedimag.2014.03.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2013] [Revised: 03/11/2014] [Accepted: 03/24/2014] [Indexed: 11/27/2022]
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España S, Marcinkowski R, Keereman V, Vandenberghe S, Van Holen R. DigiPET: sub-millimeter spatial resolution small-animal PET imaging using thin monolithic scintillators. Phys Med Biol 2014; 59:3405-20. [PMID: 24888974 DOI: 10.1088/0031-9155/59/13/3405] [Citation(s) in RCA: 85] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
A new preclinical PET system based on dSiPMs, called DigiPET, is presented. The system is based on thin monolithic scintillation crystals and exhibits superior spatial resolution at low-cost compared to systems based on pixelated crystals. Current dedicated small-rodent PET scanners have a spatial resolution in the order of 1 mm. Most of them have a large footprint, requiring considerable laboratory space. For rodent brain imaging, a PET scanner with sub-millimeter resolution is desired. To achieve this, crystals with a pixel pitch down to 0.5 mm have been used. However, fine pixels are difficult to produce and will render systems expensive. In this work, we present the first results with a high-resolution preclinical PET scanner based on thin monolithic scintillators and a large solid angle. The design is dedicated to rat-brain imaging and therefore has a very compact geometry. Four detectors were placed in a square arrangement with a distance of 34.5 mm between two opposing detector modules, defining a field of view (FOV) of 32 × 32 × 32 mm(3). Each detector consists of a thin monolithic LYSO crystal of 32 × 32 × 2 mm(3) optically coupled to a digital silicon photomultiplier (dSiPM). Event positioning within each detector was obtained using the maximum likelihood estimation (MLE) method. To evaluate the system performance, we measured the energy resolution, coincidence resolving time (CRT), sensitivity and spatial resolution. The image quality was evaluated by acquiring a hot-rod phantom filled with (18)F-FDG and a rat head one hour after an (18)F-FDG injection. The MLE yielded an average intrinsic spatial resolution on the detector of 0.54 mm FWHM. We obtained a CRT of 680 ps and an energy resolution of 18% FWHM at 511 keV. The sensitivity and spatial resolution obtained at the center of the FOV were 6.0 cps kBq(-1) and 0.7 mm, respectively. In the reconstructed images of the hot-rod phantom, hot rods down to 0.7 mm can be discriminated. In conclusion, a compact PET scanner was built using dSiPM technology and thin monolithic LYSO crystals. Excellent spatial resolution and acceptable sensitivity were demonstrated. Promising results were also obtained in a hot-rod phantom and in rat-brain imaging.
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Affiliation(s)
- Samuel España
- Department of Electronics and Information Systems, MEDISIP, Ghent University-iMinds-IBiTech, De Pintelaan 185 block B, B-9000 Ghent, Belgium
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Boisson F, Wimberley CJ, Lehnert W, Zahra D, Pham T, Perkins G, Hamze H, Gregoire MC, Reilhac A. NEMA NU 4-2008 validation and applications of the PET-SORTEO Monte Carlo simulations platform for the geometry of the Inveon PET preclinical scanner. Phys Med Biol 2013; 58:6749-63. [DOI: 10.1088/0031-9155/58/19/6749] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Cal-González J, Herraiz JL, España S, Corzo PMG, Vaquero JJ, Desco M, Udias JM. Positron range estimations with PeneloPET. Phys Med Biol 2013; 58:5127-52. [PMID: 23835700 DOI: 10.1088/0031-9155/58/15/5127] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Technical advances towards high resolution PET imaging try to overcome the inherent physical limitations to spatial resolution. Positrons travel in tissue until they annihilate into the two gamma photons detected. This range is the main detector-independent contribution to PET imaging blurring. To a large extent, it can be remedied during image reconstruction if accurate estimates of positron range are available. However, the existing estimates differ, and the comparison with the scarce experimental data available is not conclusive. In this work we present positron annihilation distributions obtained from Monte Carlo simulations with the PeneloPET simulation toolkit, for several common PET isotopes ((18)F, (11)C, (13)N, (15)O, (68)Ga and (82)Rb) in different biological media (cortical bone, soft bone, skin, muscle striated, brain, water, adipose tissue and lung). We compare PeneloPET simulations against experimental data and other simulation results available in the literature. To this end the different positron range representations employed in the literature are related to each other by means of a new parameterization for positron range profiles. Our results are generally consistent with experiments and with most simulations previously reported with differences of less than 20% in the mean and maximum range values. From these results, we conclude that better experimental measurements are needed, especially to disentangle the effect of positronium formation in positron range. Finally, with the aid of PeneloPET, we confirm that scaling approaches can be used to obtain universal, material and isotope independent, positron range profiles, which would considerably simplify range correction.
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Affiliation(s)
- J Cal-González
- Grupo de Física Nuclear, Departamento de Física Atómica, Molecular y Nuclear, Universidad Complutense de Madrid, CEI Moncloa, Spain
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Cal-González J, Herraiz JL, España S, Corzo PMG, Vaquero JJ, Desco M, Udias JM. Positron range estimations with PeneloPET. Phys Med Biol 2013. [DOI: https://doi.org/10.1088/0031-9155/58/15/5127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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España S, Deprez K, Van Holen R, Vandenberghe S. Fast calibration of SPECT monolithic scintillation detectors using un-collimated sources. Phys Med Biol 2013; 58:4807-25. [DOI: 10.1088/0031-9155/58/14/4807] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Vicente E, Herraiz JL, España S, Herranz E, Desco M, Vaquero JJ, Udías JM. Improved dead-time correction for PET scanners: application to small-animal PET. Phys Med Biol 2013; 58:2059-72. [PMID: 23459028 DOI: 10.1088/0031-9155/58/7/2059] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Pile-up and dead-time are two main causes of nonlinearity in the response of a PET scanner as a function of activity in the field of view (FOV). For a given scanner and acquisition system, pile-up effects depend on the material and size of the object being imaged and on the distribution of activity inside and outside the FOV, because these factors change the singles-to-coincidences ratio (SCR). Thus, it is difficult to devise an accurate correction that would be valid for any acquisition. In this work, we demonstrate a linear relationship between SCR and effective dead-time, which measures the effects of both dead-time (losses) and pile-up (gains and losses). This relationship allows us to propose a simple method to accurately estimate dead-time and pile-up corrections using only two calibration acquisitions with, respectively, a high and low SCR. The method has been tested with simulations and experimental data for two different scanner geometries: a scanner with large area detectors and no pile-up rejection, and a scanner composed of two full rings of smaller detectors. Our results show that the SCR correction method is accurate within 7%, even for high activities in the FOV, and avoids the bias of the standard single-parameter method.
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Affiliation(s)
- E Vicente
- Grupo de Física Nuclear, Departamento de Física Atómica, Molecular y Nuclear, Universidad Complutense de Madrid, CEI Moncloa, Spain
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Vicente E, Herraiz JL, España S, Herranz E, Desco M, Vaquero JJ, Udías JM. Improved dead-time correction for PET scanners: application to small-animal PET. Phys Med Biol 2013. [DOI: https://doi.org/10.1088/0031-9155/58/7/2059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Abstract
The driving force in the research and development of new hybrid PET-CT/MR imaging scanners is the production of images with optimum quality, accuracy, and resolution. However, the acquisition process is limited by several factors. Key issues are the respiratory and cardiac motion artifacts that occur during an imaging session. In this article the necessary tools for modeling and simulation of realistic high-resolution four-dimensional PET-CT and PET-MR imaging data are described. Beyond the need for four-dimensional simulations, accurate modeling of the acquisition process can be included within the reconstruction algorithms assisting in the improvement of image quality and accuracy of estimation of physiologic parameters from four-dimensional hybrid PET imaging.
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Abella M, Vicente E, Rodríguez-Ruano A, España S, Lage E, Desco M, Udias JM, Vaquero JJ. Misalignments calibration in small-animal PET scanners based on rotating planar detectors and parallel-beam geometry. Phys Med Biol 2012; 57:7493-518. [DOI: 10.1088/0031-9155/57/22/7493] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Mitev K, Gerganov G, Kirov AS, Schmidtlein CR, Madzhunkov Y, Kawrakow I. Influence of photon energy cuts on PET Monte Carlo simulation results. Med Phys 2012; 39:4175-86. [DOI: 10.1118/1.4725168] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Herraiz JL, España S, Cabido R, Montemayor AS, Desco M, Vaquero JJ, Udias JM. GPU-Based Fast Iterative Reconstruction of Fully 3-D PET Sinograms. IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2011. [DOI: 10.1109/tns.2011.2158113] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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Tsoumpas C, Buerger C, King AP, Mollet P, Keereman V, Vandenberghe S, Schulz V, Schleyer P, Schaeffter T, Marsden PK. Fast generation of 4D PET-MR data from real dynamic MR acquisitions. Phys Med Biol 2011; 56:6597-613. [DOI: 10.1088/0031-9155/56/20/005] [Citation(s) in RCA: 79] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Herraiz J, España S, Cal-González J, Vaquero J, Desco M, Udías J. Fully 3D GPU PET reconstruction. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2011. [DOI: 10.1016/j.nima.2010.12.043] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Cal-González J, Herraiz J, España S, Vicente E, Herranz E, Desco M, Vaquero J, Udías J. Study of CT-based positron range correction in high resolution 3D PET imaging. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2011. [DOI: 10.1016/j.nima.2010.12.041] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Cañadas M, Arce P, Rato Mendes P. Validation of a small-animal PET simulation using GAMOS: a GEANT4-based framework. Phys Med Biol 2010; 56:273-88. [DOI: 10.1088/0031-9155/56/1/016] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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McLennan A, Reilhac A, Brady M. SORTEO: Monte Carlo-based simulator with list-mode capabilities. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2010; 2009:3751-4. [PMID: 19964808 DOI: 10.1109/iembs.2009.5334536] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Monte Carlo-based PET simulators are powerful tools in the evaluation and validation of new PET algorithms. Accurate generation of projection data from spatiotemporal tracer distributions enable, for a given scanner specification and attenuating media distribution, quantitative analysis based on known ground truth. High activity-related phenomena, such as the contribution of randoms, as well as block and system deadtimes, corrupt actual PET scan data and therefore must be integrated within the simulation model, along with photon interactions within tissue and scanner materials. The PET-SORTEO Monte Carlo simulator, dedicated to full ring tomographs, is able to generate scattered, unscattered, and randoms event distributions from voxelized phantoms, accounting for data losses due to system deadtime. We show the results of extending the simulator to include accurate generation of list-mode data. Our implementation avoids incorrect event distribution and event timing inaccuracies cause by local and propagating temporal rounding errors. List-mode events produced by the PET-SORTEO simulator, when rebinned, are now consistent with sinograms produced by the simulator.
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Affiliation(s)
- Andrew McLennan
- Department of Engineering Science, University of Oxford, UK.
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Ortuño JE, Kontaxakis G, Rubio JL, Guerra P, Santos A. Efficient methodologies for system matrix modelling in iterative image reconstruction for rotating high-resolution PET. Phys Med Biol 2010; 55:1833-61. [DOI: 10.1088/0031-9155/55/7/004] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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