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Li S, Zhu Y, Spencer BA, Wang G. Single-Subject Deep-Learning Image Reconstruction With a Neural Optimization Transfer Algorithm for PET-Enabled Dual-Energy CT Imaging. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2024; 33:4075-4089. [PMID: 38941203 DOI: 10.1109/tip.2024.3418347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
Combining dual-energy computed tomography (DECT) with positron emission tomography (PET) offers many potential clinical applications but typically requires expensive hardware upgrades or increases radiation doses on PET/CT scanners due to an extra X-ray CT scan. The recent PET-enabled DECT method allows DECT imaging on PET/CT without requiring a second X-ray CT scan. It combines the already existing X-ray CT image with a 511 keV γ -ray CT (gCT) image reconstructed from time-of-flight PET emission data. A kernelized framework has been developed for reconstructing gCT image but this method has not fully exploited the potential of prior knowledge. Use of deep neural networks may explore the power of deep learning in this application. However, common approaches require a large database for training, which is impractical for a new imaging method like PET-enabled DECT. Here, we propose a single-subject method by using neural-network representation as a deep coefficient prior to improving gCT image reconstruction without population-based pre-training. The resulting optimization problem becomes the tomographic estimation of nonlinear neural-network parameters from gCT projection data. This complicated problem can be efficiently solved by utilizing the optimization transfer strategy with quadratic surrogates. Each iteration of the proposed neural optimization transfer algorithm includes: PET activity image update; gCT image update; and least-square neural-network learning in the gCT image domain. This algorithm is guaranteed to monotonically increase the data likelihood. Results from computer simulation, real phantom data and real patient data have demonstrated that the proposed method can significantly improve gCT image quality and consequent multi-material decomposition as compared to other methods.
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Hybrid System: PET/CT. Nucl Med Mol Imaging 2022. [DOI: 10.1016/b978-0-12-822960-6.00103-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Goh KL, Liew SC. Dual-energy x-ray approach for object/energy-specific attenuation coefficient correction in single-photon emission computed tomography: effects of contrast agent. J Med Imaging (Bellingham) 2021; 8:052106. [PMID: 34084871 DOI: 10.1117/1.jmi.8.5.052106] [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: 10/29/2020] [Accepted: 05/11/2021] [Indexed: 11/14/2022] Open
Abstract
Purpose: To investigate the influence of radiographic contrast agent on the accuracy of the photon counts arising from the emission of gamma rays of radionuclides in single-photon emission computed tomography (SPECT), when dual-energy x-ray CT (DXCT) is employed for providing object/energy-specific attenuation coefficient correction in SPECT. Approach: Computer simulation was performed for three transmission CT approaches, namely, the conventional (single kVp, unimodal spectrum) x-ray CT, DXCT (single kVp, bimodal spectrum) with basis material decomposition (BMD), and DXCT with BMD followed by basis material coefficients transformation (BMT), to study the effects of these approaches on the accuracy of the photon counts from the SPECT image of a thorax-like phantom. Results: All three CT approaches revealed that the error in the counts was both photon energy and iodine concentration-dependent. Differences in the trending increase/decrease in the errors with the respective increase in iodine concentration and photon energy were observed among the three CT approaches. Of the three, the BMT/SPECT approach resulted in the smallest error in the concentration of radionuclides measured, especially in the contrast agent-filled region, and the optimal level depended on the iodine concentration and photon energy. Conclusion: With a judicious choice of the basis materials and photon energy, it may be possible to take advantage of the benefits of the BMT method to mitigate the accuracy problem in DXCT for quantitative SPECT imaging.
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Affiliation(s)
| | - Soo Chin Liew
- National University of Singapore, Center for Remote Imaging, Sensing and Processing and Department of Physics, Singapore
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4
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Wang G. PET-enabled dual-energy CT: image reconstruction and a proof-of-concept computer simulation study. Phys Med Biol 2020; 65:245028. [PMID: 33120376 DOI: 10.1088/1361-6560/abc5ca] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Standard dual-energy computed tomography (CT) uses two different x-ray energies to obtain energy-dependent tissue attenuation information to allow quantitative material decomposition. The combined use of dual-energy CT and positron emission tomography (PET) may provide a more comprehensive characterization of disease states in cancer and other diseases. However, the integration of dual-energy CT with PET is not trivial, either requiring costly hardware upgrades or increasing radiation exposure. This paper proposes a different dual-energy CT imaging method that is enabled by PET. Instead of using a second x-ray CT scan with a different energy, this method exploits time-of-flight PET image reconstruction via the maximum likelihood attenuation and activity (MLAA) algorithm to obtain a 511 keV gamma-ray attenuation image from PET emission data. The high-energy gamma-ray attenuation image is then combined with the low-energy x-ray CT of PET/CT to provide a pair of dual-energy CT images. A major challenge with the standard MLAA reconstruction is the high noise present in the reconstructed 511 keV attenuation map, which would not compromise the PET activity reconstruction too much but may significantly affect the performance of the gamma-ray attenuation image for material decomposition. To overcome the problem, we further propose a kernel MLAA algorithm to exploit the prior information from the available x-ray CT image. We conducted a computer simulation to test the concept and algorithm for the task of material decomposition. The simulation results demonstrate that this PET-enabled dual-energy CT method is promising for quantitative material decomposition. The proposed method can be readily implemented on time-of-flight PET/CT scanners to enable simultaneous PET and dual-energy CT imaging.
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Affiliation(s)
- Guobao Wang
- Department of Radiology, University of California, Davis, CA, United States of America
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5
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Shapira N, Scheuermann J, Perkins AE, Kim J, Liu LP, Karp JS, Noël PB. Quantitative positron emission tomography imaging in the presence of iodinated contrast media using electron density quantifications from dual-energy computed tomography. Med Phys 2020; 48:273-286. [PMID: 33170953 DOI: 10.1002/mp.14589] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 07/31/2020] [Accepted: 11/02/2020] [Indexed: 11/10/2022] Open
Abstract
PURPOSE As preparation for future positron emission tomography (PET)/dual-energy computed tomography (DECT)T imaging modality and new possible clinical applications, the study aimed to evaluate the utility of clinically available spectral results from a DECT system for improving attenuation corrections of PET acquisitions in the presence of iodinated contrast media. The dependence of the accuracy of PET quantification values, reconstructed with conventional and spectral-based attenuation corrections, was examined as a function of the amount of iodine content and x-ray radiation exposure. METHODS Measurements were performed on commercial PET/CT and DECT systems, using a semi-anthropomorphic phantom with seven centrifuge tubes in its bore. Five different configurations of tube contents were scanned by both PET/CT and DECT. With the aim of mimicking clinically observed concentrations, in all phantom configurations the center tube contained a high concentration of radionuclide while the peripheral tubes contained a lower concentration of radionuclide. Iodine content was incrementally increased between phantom configurations by replacing iodine-free tubes with tubes that contained the original radionuclide concentration within a 10 mg/ml iodine dilution. DECT-based attenuation correction maps were generated by scaling electron density spectral results into corresponding 511 keV photon linear attenuation coefficients. RESULTS Mean SUV values obtained from the nominal PET reconstruction, using conventional CT images as input for the attenuation correction, demonstrate a monotonic increase of 8.6% when the water and radionuclide mixtures were replaced by iodine, water, and radionuclide (same level of activity) mixture. Mean SUV values obtained from the DECT-based reconstruction, in which the attenuation correction utilizes electron density values as input, demonstrate different, more stable behavior across all iodine insert configurations, with a standard deviation to mean ratio of less than 1%. This observed behavior was independent of the area size used for measurement. A minor radiation dose dependency of the electron density values (below 0.5%) was observed. This resulted in consistent (iodine independent) PET quantification behavior, which persisted even at the lowest radiation dose levels tested in our experiment, that is, 25% of the radiation dose utilized for CT acquisition in the clinical PET/CT protocol. CONCLUSIONS Utilization of DECT-generated electron density estimations for attenuation correction benefit PET quantification consistency in the presence of iodine and at nominal and low DECT radiation exposure levels. The ability to correctly account for iodinated contrast media in PET acquisitions will allow the development of new clinical applications that rely on the quantitative capabilities of spectral CT technologies and modern PET systems.
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Affiliation(s)
- Nadav Shapira
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Joshua Scheuermann
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Johoon Kim
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Leening P Liu
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Joel S Karp
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Peter B Noël
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.,Department of Diagnostic and Interventional Radiology, School of Medicine & klinikum rechts der Isar, Technical University of Munich, München, Germany
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Shiyam Sundar LK, Muzik O, Buvat I, Bidaut L, Beyer T. Potentials and caveats of AI in hybrid imaging. Methods 2020; 188:4-19. [PMID: 33068741 DOI: 10.1016/j.ymeth.2020.10.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/05/2020] [Accepted: 10/07/2020] [Indexed: 12/18/2022] Open
Abstract
State-of-the-art patient management frequently mandates the investigation of both anatomy and physiology of the patients. Hybrid imaging modalities such as the PET/MRI, PET/CT and SPECT/CT have the ability to provide both structural and functional information of the investigated tissues in a single examination. With the introduction of such advanced hardware fusion, new problems arise such as the exceedingly large amount of multi-modality data that requires novel approaches of how to extract a maximum of clinical information from large sets of multi-dimensional imaging data. Artificial intelligence (AI) has emerged as one of the leading technologies that has shown promise in facilitating highly integrative analysis of multi-parametric data. Specifically, the usefulness of AI algorithms in the medical imaging field has been heavily investigated in the realms of (1) image acquisition and reconstruction, (2) post-processing and (3) data mining and modelling. Here, we aim to provide an overview of the challenges encountered in hybrid imaging and discuss how AI algorithms can facilitate potential solutions. In addition, we highlight the pitfalls and challenges in using advanced AI algorithms in the context of hybrid imaging and provide suggestions for building robust AI solutions that enable reproducible and transparent research.
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Affiliation(s)
- Lalith Kumar Shiyam Sundar
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | | | - Irène Buvat
- Laboratoire d'Imagerie Translationnelle en Oncologie, Inserm, Institut Curie, Orsay, France
| | - Luc Bidaut
- College of Science, University of Lincoln, Lincoln, UK
| | - Thomas Beyer
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
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7
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Yang Q, Fullagar WK, Myers GR, Latham SJ, Varslot T, Sheppard AP, Kingston AM. X-ray attenuation models to account for beam hardening in computed tomography. APPLIED OPTICS 2020; 59:9126-9136. [PMID: 33104623 DOI: 10.1364/ao.402304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 09/10/2020] [Indexed: 06/11/2023]
Abstract
We introduce a beam-hardening correction method for lab-based X-ray computed tomography (CT) by modifying existing iterative tomographic reconstruction algorithms. Our method simplifies the standard Alvarez-Macovski X-ray attenuation model [Phys. Med. Biol.21, 733 (1976)] and is compatible with conventional (i.e., single-spectrum) CT scans. The sole modification involves a polychromatic projection operation, which is equivalent to applying a weighting that more closely matches the attenuation of polychromatic X-rays. Practicality is a priority, so we only require information about the X-ray spectrum and some constants relating to material properties. No other changes to the experimental setup or the iterative algorithms are necessary. Using reconstructions of simulations and several large experimental datasets, we show that this method is able to remove or reduce cupping, streaking, and other artefacts from X-ray beam hardening and improve the self-consistency of projected attenuation in CT. When the assumptions made in the simplifications are valid, the reconstructed tomogram can even be quantitative.
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Hopkins SR. Ventilation/Perfusion Relationships and Gas Exchange: Measurement Approaches. Compr Physiol 2020; 10:1155-1205. [PMID: 32941684 DOI: 10.1002/cphy.c180042] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Ventilation-perfusion ( V ˙ A / Q ˙ ) matching, the regional matching of the flow of fresh gas to flow of deoxygenated capillary blood, is the most important mechanism affecting the efficiency of pulmonary gas exchange. This article discusses the measurement of V ˙ A / Q ˙ matching with three broad classes of techniques: (i) those based in gas exchange, such as the multiple inert gas elimination technique (MIGET); (ii) those derived from imaging techniques such as single-photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRI), computed tomography (CT), and electrical impedance tomography (EIT); and (iii) fluorescent and radiolabeled microspheres. The focus is on the physiological basis of these techniques that provide quantitative information for research purposes rather than qualitative measurements that are used clinically. The fundamental equations of pulmonary gas exchange are first reviewed to lay the foundation for the gas exchange techniques and some of the imaging applications. The physiological considerations for each of the techniques along with advantages and disadvantages are briefly discussed. © 2020 American Physiological Society. Compr Physiol 10:1155-1205, 2020.
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Affiliation(s)
- Susan R Hopkins
- Departments of Medicine and Radiology, University of California, San Diego, California, USA
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Oehmigen M, Lindemann ME, Tellmann L, Lanz T, Quick HH. Improving the CT (140 kVp) to PET (511 keV) conversion in PET/MR hardware component attenuation correction. Med Phys 2020; 47:2116-2127. [DOI: 10.1002/mp.14091] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 02/10/2020] [Accepted: 02/10/2020] [Indexed: 01/21/2023] Open
Affiliation(s)
- Mark Oehmigen
- High‐Field and Hybrid MR Imaging University Hospital Essen Essen Germany
| | - Maike E. Lindemann
- High‐Field and Hybrid MR Imaging University Hospital Essen Essen Germany
| | - Lutz Tellmann
- Institute for Neuroscience and Medicine (INM‐4) Forschungszentrum Jülich GmbH Jülich Germany
| | | | - Harald H. Quick
- High‐Field and Hybrid MR Imaging University Hospital Essen Essen Germany
- Erwin L. Hahn Institute for MR Imaging University Duisburg‐Essen Essen Germany
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10
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Lillington J, Brusaferri L, Kläser K, Shmueli K, Neji R, Hutton BF, Fraioli F, Arridge S, Cardoso MJ, Ourselin S, Thielemans K, Atkinson D. PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques. Med Phys 2020; 47:790-811. [PMID: 31794071 PMCID: PMC7027532 DOI: 10.1002/mp.13943] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2019] [Revised: 07/23/2019] [Accepted: 11/20/2019] [Indexed: 12/16/2022] Open
Abstract
Positron emission tomography/magnetic resonance imaging (PET/MRI) potentially offers several advantages over positron emission tomography/computed tomography (PET/CT), for example, no CT radiation dose and soft tissue images from MR acquired at the same time as the PET. However, obtaining accurate linear attenuation correction (LAC) factors for the lung remains difficult in PET/MRI. LACs depend on electron density and in the lung, these vary significantly both within an individual and from person to person. Current commercial practice is to use a single‐valued population‐based lung LAC, and better estimation is needed to improve quantification. Given the under‐appreciation of lung attenuation estimation as an issue, the inaccuracy of PET quantification due to the use of single‐valued lung LACs, the unique challenges of lung estimation, and the emerging status of PET/MRI scanners in lung disease, a review is timely. This paper highlights past and present methods, categorizing them into segmentation, atlas/mapping, and emission‐based schemes. Potential strategies for future developments are also presented.
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Affiliation(s)
- Joseph Lillington
- Centre for Medical Imaging, University College London, London, W1W 7TS, UK
| | - Ludovica Brusaferri
- Institute of Nuclear Medicine, University College London, London, NW1 2BU, UK
| | - Kerstin Kläser
- Centre for Medical Image Computing, University College London, London, WC1E 7JE, UK
| | - Karin Shmueli
- Magnetic Resonance Imaging Group, Department of Medical Physics & Biomedical Engineering, University College London, London, WC1E 6BT, UK
| | - Radhouene Neji
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, GU16 8QD, UK
| | - Brian F Hutton
- Institute of Nuclear Medicine, University College London, London, NW1 2BU, UK
| | - Francesco Fraioli
- Institute of Nuclear Medicine, University College London, London, NW1 2BU, UK
| | - Simon Arridge
- Centre for Medical Image Computing, University College London, London, WC1E 7JE, UK
| | - Manuel Jorge Cardoso
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Kris Thielemans
- Institute of Nuclear Medicine, University College London, London, NW1 2BU, UK
| | - David Atkinson
- Centre for Medical Imaging, University College London, London, W1W 7TS, UK
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Zhao W, Lv T, Lee R, Chen Y, Xing L. Obtaining dual-energy computed tomography (CT) information from a single-energy CT image for quantitative imaging analysis of living subjects by using deep learning. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2020; 25:139-148. [PMID: 31797593 PMCID: PMC6938283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
Abstract
Computed tomographic (CT) is a fundamental imaging modality to generate cross-sectional views of internal anatomy in a living subject or interrogate material composition of an object, and it has been routinely used in clinical applications and nondestructive testing. In a standard CT image, pixels having the same Hounsfield Units (HU) can correspond to different materials, and it is therefore challenging to differentiate and quantify materials. Dual-energy CT (DECT) is desirable to differentiate multiple materials, but the costly DECT scanners are not widely available as single-energy CT (SECT) scanners. Recent advancement in deep learning provides an enabling tool to map images between different modalities with incorporated prior knowledge. Here we develop a deep learning approach to perform DECT imaging by using the standard SECT data. The end point of the approach is a model capable of providing the high-energy CT image for a given input low-energy CT image. The feasibility of the deep learning-based DECT imaging method using a SECT data is demonstrated using contrast-enhanced DECT images and evaluated using clinical relevant indexes. This work opens new opportunities for numerous DECT clinical applications with a standard SECT data and may enable significantly simplified hardware design, scanning dose and image cost reduction for future DECT systems.
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Affiliation(s)
| | | | - Rena Lee
- Department of Bioengineering, Ehwa Womens University, Seoul, Korea
| | | | - Lei Xing
- Department of Radiation Oncology, Stanford University, Palo Alto, CA 94306, USA
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12
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Wright CL, Maly JJ, Zhang J, Knopp MV. Advancing Precision Nuclear Medicine and Molecular Imaging for Lymphoma. PET Clin 2016; 12:63-82. [PMID: 27863567 DOI: 10.1016/j.cpet.2016.08.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
PET with fluorodeoxyglucose F 18 (18F FDG-PET) is a meaningful biomarker for the detection, targeted biopsy, and treatment of lymphoma. This article reviews the evolution of 18F FDG-PET as a putative biomarker for lymphoma and addresses the current capabilities, challenges, and opportunities to enable precision medicine practices for lymphoma. Precision nuclear medicine is driven by new imaging technologies and methodologies to more accurately detect malignant disease. Although quantitative assessment of response is limited, such technologies will enable a more precise metabolic mapping with much higher definition image detail and thus may make it a robust and valid quantitative response assessment methodology.
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Affiliation(s)
- Chadwick L Wright
- Wright Center of Innovation in Biomedical Imaging, Division of Imaging Science, Department of Radiology, The Ohio State University Wexner Medical Center, 395 West 12th Avenue, Room 430, Columbus, OH 43210, USA
| | - Joseph J Maly
- Division of Hematology, Department of Internal Medicine, The Ohio State University Wexner Medical Center, Starling Loving Hall 406C, 320 West 10th Avenue, Columbus, OH 43210, USA
| | - Jun Zhang
- Wright Center of Innovation in Biomedical Imaging, Division of Imaging Science, Department of Radiology, The Ohio State University Wexner Medical Center, 395 West 12th Avenue, Room 430, Columbus, OH 43210, USA
| | - Michael V Knopp
- Wright Center of Innovation in Biomedical Imaging, Division of Imaging Science, Department of Radiology, The Ohio State University Wexner Medical Center, 395 West 12th Avenue, Room 430, Columbus, OH 43210, USA.
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Vaquero JJ, Kinahan P. Positron Emission Tomography: Current Challenges and Opportunities for Technological Advances in Clinical and Preclinical Imaging Systems. Annu Rev Biomed Eng 2016; 17:385-414. [PMID: 26643024 DOI: 10.1146/annurev-bioeng-071114-040723] [Citation(s) in RCA: 171] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Positron emission tomography (PET) imaging is based on detecting two time-coincident high-energy photons from the emission of a positron-emitting radioisotope. The physics of the emission, and the detection of the coincident photons, give PET imaging unique capabilities for both very high sensitivity and accurate estimation of the in vivo concentration of the radiotracer. PET imaging has been widely adopted as an important clinical modality for oncological, cardiovascular, and neurological applications. PET imaging has also become an important tool in preclinical studies, particularly for investigating murine models of disease and other small-animal models. However, there are several challenges to using PET imaging systems. These include the fundamental trade-offs between resolution and noise, the quantitative accuracy of the measurements, and integration with X-ray computed tomography and magnetic resonance imaging. In this article, we review how researchers and industry are addressing these challenges.
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Affiliation(s)
- Juan José Vaquero
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, 28911 Madrid, Spain, and Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain;
| | - Paul Kinahan
- Departments of Radiology, Bioengineering, and Physics, University of Washington, Seattle, Washington 98195;
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14
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de Galiza Barbosa F, Delso G, Ter Voert EEGW, Huellner MW, Herrmann K, Veit-Haibach P. Multi-technique hybrid imaging in PET/CT and PET/MR: what does the future hold? Clin Radiol 2016; 71:660-72. [PMID: 27108800 DOI: 10.1016/j.crad.2016.03.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Revised: 03/11/2016] [Accepted: 03/22/2016] [Indexed: 12/19/2022]
Abstract
Integrated positron-emission tomography and computed tomography (PET/CT) is one of the most important imaging techniques to have emerged in oncological practice in the last decade. Hybrid imaging, in general, remains a rapidly growing field, not only in developing countries, but also in western industrialised healthcare systems. A great deal of technological development and research is focused on improving hybrid imaging technology further and introducing new techniques, e.g., integrated PET and magnetic resonance imaging (PET/MRI). Additionally, there are several new PET tracers on the horizon, which have the potential to broaden clinical applications in hybrid imaging for diagnosis as well as therapy. This article aims to highlight some of the major technical and clinical advances that are currently taking place in PET/CT and PET/MRI that will potentially maintain the position of hybrid techniques at the forefront of medical imaging technologies.
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Affiliation(s)
- F de Galiza Barbosa
- Department of Nuclear Medicine, University Hospital Zurich, Switzerland; University of Zurich, Switzerland
| | - G Delso
- Department of Nuclear Medicine, University Hospital Zurich, Switzerland; GE Healthcare, Waukesha, WI, USA
| | - E E G W Ter Voert
- Department of Nuclear Medicine, University Hospital Zurich, Switzerland; University of Zurich, Switzerland
| | - M W Huellner
- Department of Nuclear Medicine, University Hospital Zurich, Switzerland; University of Zurich, Switzerland; Department of Neuroradiology, University Hospital Zurich, Switzerland
| | - K Herrmann
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, United States; Department of Nuclear Medicine, Universitätsklinikum Würzburg, Oberdürrbacher, Str. 6, Würzburg, Germany
| | - P Veit-Haibach
- Department of Nuclear Medicine, University Hospital Zurich, Switzerland; University of Zurich, Switzerland; Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland.
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15
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Lee TC, Alessio AM, Miyaoka RM, Kinahan PE. Morphology supporting function: attenuation correction for SPECT/CT, PET/CT, and PET/MR imaging. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF... 2016; 60:25-39. [PMID: 26576737 PMCID: PMC5262384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Both SPECT, and in particular PET, are unique in medical imaging for their high sensitivity and direct link to a physical quantity, i.e. radiotracer concentration. This gives PET and SPECT imaging unique capabilities for accurately monitoring disease activity for the purposes of clinical management or therapy development. However, to achieve a direct quantitative connection between the underlying radiotracer concentration and the reconstructed image values several confounding physical effects have to be estimated, notably photon attenuation and scatter. With the advent of dual-modality SPECT/CT, PET/CT, and PET/MR scanners, the complementary CT or MR image data can enable these corrections, although there are unique challenges for each combination. This review covers the basic physics underlying photon attenuation and scatter and summarizes technical considerations for multimodal imaging with regard to PET and SPECT quantification and methods to address the challenges for each multimodal combination.
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Affiliation(s)
- Tzu C Lee
- Department of Bioengineering, University of Washington, Seattle, WA, USA -
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16
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Yang Q, Lu Y, Xi Y, Cong W, Kalra M, Wang G. Sinogram-based attenuation correction in PET/CT. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2016; 24:9-22. [PMID: 26890905 DOI: 10.3233/xst-160536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
In a typical positron emission tomography/computed tomography (PET/CT) system, the attenuation correction is necessary for PET image reconstruction, which involves a transformation from the CT Hounsfield units (HU) to its linear attenuation coefficient (LAC) at 511 keV. This transformation is usually aided by an empirical bilinear function, followed by the forward projection of the transformed attenuation image. In this paper, we propose a direct method that calculates attenuation factors from CT projections, without using a reconstructed CT image. In this method, the human body is considered as a mixture of three distinct components: air, water and bone. Then, we estimate the proportions of these three components along each x-ray path and restore the attenuation factor at 511 keV with the known water and bone LACs. Our numerical results show that the proposed method produces as accurate estimation as the conventional HU mapping method.
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Affiliation(s)
- Qingsong Yang
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Yang Lu
- Department of Physics and Reconstruction, Molecular Imaging Business Unit, United Imaging Healthcare Co., Ltd, Shanghai, China
| | - Yan Xi
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Wenxiang Cong
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Mannudeep Kalra
- Divisions of Thoracic and Cardiac Imaging at Massachusetts General Hospital
| | - Ge Wang
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
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Parodi K. Vision 20/20: Positron emission tomography in radiation therapy planning, delivery, and monitoring. Med Phys 2015; 42:7153-68. [DOI: 10.1118/1.4935869] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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