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Sperry BW, Bateman TM, Akin EA, Bravo PE, Chen W, Dilsizian V, Hyafil F, Khor YM, Miller RJH, Slart RHJA, Slomka P, Verberne H, Miller EJ, Liu C. Hot spot imaging in cardiovascular diseases: an information statement from SNMMI, ASNC, and EANM. J Nucl Cardiol 2023; 30:626-652. [PMID: 35864433 DOI: 10.1007/s12350-022-02985-8] [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: 02/07/2022] [Accepted: 04/19/2022] [Indexed: 11/30/2022]
Abstract
This information statement from the Society of Nuclear Medicine and Molecular Imaging, American Society of Nuclear Cardiology, and European Association of Nuclear Medicine describes the performance, interpretation, and reporting of hot spot imaging in nuclear cardiology. The field of nuclear cardiology has historically focused on cold spot imaging for the interpretation of myocardial ischemia and infarction. Hot spot imaging has been an important part of nuclear medicine, particularly for oncology or infection indications, and the use of hot spot imaging in nuclear cardiology continues to expand. This document focuses on image acquisition and processing, methods of quantification, indications, protocols, and reporting of hot spot imaging. Indications discussed include myocardial viability, myocardial inflammation, device or valve infection, large vessel vasculitis, valve calcification and vulnerable plaques, and cardiac amyloidosis. This document contextualizes the foundations of image quantification and highlights reporting in each indication for the cardiac nuclear imager.
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Affiliation(s)
- Brett W Sperry
- Saint Luke's Mid America Heart Institute, 4401 Wornall Rd, Suite 2000, Kansas City, MO, 64111, USA.
| | - Timothy M Bateman
- Saint Luke's Mid America Heart Institute, 4401 Wornall Rd, Suite 2000, Kansas City, MO, 64111, USA
| | - Esma A Akin
- George Washington University Hospital, Washington, DC, USA
| | - Paco E Bravo
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Wengen Chen
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Vasken Dilsizian
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Fabien Hyafil
- Department of Nuclear Medicine, Hôpital Européen Georges-Pompidou, DMU IMAGINA, Assistance Publique -Hôpitaux de Paris, University of Paris, Paris, France
| | - Yiu Ming Khor
- Department of Nuclear Medicine and Molecular Imaging, Singapore General Hospital, Singapore, Singapore
| | - Robert J H Miller
- Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada
| | - Riemer H J A Slart
- Department of Nuclear Medicine and Molecular Imaging, Medical Imaging Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Biomedical Photonic Imaging, University of Twente, Enschede, The Netherlands
| | - Piotr Slomka
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Hein Verberne
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Edward J Miller
- Department of Radiology and Biomedical Imaging, Yale University, 801 Howard Ave, New Haven, CT, 06519, USA
| | - Chi Liu
- Department of Radiology and Biomedical Imaging, Yale University, 801 Howard Ave, New Haven, CT, 06519, USA.
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Wang X, Yang X, Wang J, Dong C, Ding J, Wu M, Wang Y, Ding H, Zhang H, Sang X, Zhao H, Huo L. Metabolic Tumor Volume Measured by 18F-FDG PET/CT is Associated with the Survival of Unresectable Hepatocellular Carcinoma Treated with PD-1/PD-L1 Inhibitors Plus Molecular Targeted Agents. J Hepatocell Carcinoma 2023; 10:587-598. [PMID: 37063093 PMCID: PMC10094465 DOI: 10.2147/jhc.s401647] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 03/21/2023] [Indexed: 04/18/2023] Open
Abstract
Purpose The combination of PD-1/PD-L1 inhibitors and molecular targeted agents showed promising efficacy for unresectable hepatocellular carcinoma (uHCC). This study aimed to investigate the prognostic value of metabolic parameters from 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) in patients with uHCC underwent the combined therapies. Patients and Methods Patients with uHCC treated with a combination of immunotherapy and targeted therapy who underwent baseline 18F-FDG PET/CT between July 2018 and December 2021 were recruited retrospectively. The metabolic tumor volume (MTV), total lesion glycolysis (TLG), maximum standardized uptake values (SUVmax), and clinical and biological parameters were recorded. A multivariate prediction model was developed for overall survival (OS) using these parameters together with clinical prognostic factors. Results Seventy-seven patients were finally included. The median OS was 16.8 months. We found that a high MTV (≥39.65 cm3 as the median value) was significantly associated with OS (P<0.05). In multivariate analyses for OS, a high MTV, high Eastern Cooperative Oncology Group performance status (ECOG-PS, ≥1), Child-Pugh (B-C) grade, and the presence of bone metastasis were significantly associated with poor OS (HR 1.371, HR 3.73, HR 15.384, and HR 2.994, all P<0.05, respectively). A multivariate prognostic model including MTV and prognostic factors, such as ECOG-PS, Child-Pugh grade, and bone metastasis, further improved the identification of different OS subgroups. Conclusion High MTV is an adverse prognostic factor in patients with uHCC treated with a combination of immunotherapy and molecular targeted agents. Integrating PET/CT parameters with clinical prognostic factors could help to personalize immunotherapy.
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Affiliation(s)
- Xuezhu Wang
- Department of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Xu Yang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Jingnan Wang
- Department of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Chengyan Dong
- GE Healthcare China, Beijing, People’s Republic of China
| | - Jie Ding
- Department of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Meiqi Wu
- Department of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Yanyu Wang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Haiyan Ding
- Department of Biomedical Engineering, Tsinghua University, Beijing, People’s Republic of China
| | - Hui Zhang
- Department of Biomedical Engineering, Tsinghua University, Beijing, People’s Republic of China
| | - Xinting Sang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Haitao Zhao
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
- Correspondence: Li Huo; Haitao Zhao, #1 Shuaifuyuan, Dongcheng District, Beijing, People’s Republic of China, Tel +86 13910801986; +86 13901246374, Email ;
| | - Li Huo
- Department of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
- Correspondence: Li Huo; Haitao Zhao, #1 Shuaifuyuan, Dongcheng District, Beijing, People’s Republic of China, Tel +86 13910801986; +86 13901246374, Email ;
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Enhancement of 18F-Fluorodeoxyglucose PET Image Quality by Deep-Learning-Based Image Reconstruction Using Advanced Intelligent Clear-IQ Engine in Semiconductor-Based PET/CT Scanners. Diagnostics (Basel) 2022; 12:diagnostics12102500. [PMID: 36292189 PMCID: PMC9599974 DOI: 10.3390/diagnostics12102500] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/03/2022] [Accepted: 10/14/2022] [Indexed: 11/22/2022] Open
Abstract
Deep learning (DL) image quality improvement has been studied for application to 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). It is unclear, however, whether DL can increase the quality of images obtained with semiconductor-based PET/CT scanners. This study aimed to compare the quality of semiconductor-based PET/CT scanner images obtained by DL-based technology and conventional OSEM image with Gaussian postfilter. For DL-based data processing implementation, we used Advanced Intelligent Clear-IQ Engine (AiCE, Canon Medical Systems, Tochigi, Japan) and for OSEM images, Gaussian postfilter of 3 mm FWHM is used. Thirty patients who underwent semiconductor-based PET/CT scanner imaging between May 6, 2021, and May 19, 2021, were enrolled. We compared AiCE images and OSEM images and scored them for delineation, image noise, and overall image quality. We also measured standardized uptake values (SUVs) in tumors and healthy tissues and compared them between AiCE and OSEM. AiCE images scored significantly higher than OSEM images for delineation, image noise, and overall image quality. The Fleiss kappa value for the interobserver agreement was 0.57. Among the 21 SUV measurements in healthy organs, 11 (52.4%) measurements were significantly different between AiCE and OSEM images. More pathological lesions were detected in AiCE images as compared with OSEM images, with AiCE images showing higher SUVs for pathological lesions than OSEM images. AiCE can improve the quality of images acquired with semiconductor-based PET/CT scanners, including the noise level, contrast, and tumor detection capability.
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Wang J, Shao Y, Liu B, Wang X, Geist BK, Li X, Li F, Zhao H, Hacker M, Ding H, Zhang H, Huo L. Dynamic 18F-FDG PET imaging of liver lesions: evaluation of a two-tissue compartment model with dual blood input function. BMC Med Imaging 2021; 21:90. [PMID: 34034664 PMCID: PMC8152049 DOI: 10.1186/s12880-021-00623-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 05/17/2021] [Indexed: 11/10/2022] Open
Abstract
Background Dynamic PET with kinetic modeling was reported to be potentially helpful in the assessment of hepatic malignancy. In this study, a kinetic modeling analysis was performed on hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) from dynamic FDG positron emission tomography/computer tomography (PET/CT) scans. Methods A reversible two-tissue compartment model with dual blood input function, which takes into consideration the blood supply from both hepatic artery and portal vein, was used for accurate kinetic modeling of liver dynamic 18F-FDG PET imaging. The blood input functions were directly measured as the mean values over the VOIs on descending aorta and portal vein respectively. And the contribution of hepatic artery to the blood input function was optimization-derived in the process of model fitting. The kinetic model was evaluated using dynamic PET data acquired on 24 patients with identified hepatobiliary malignancy. 38 HCC or ICC identified lesions and 24 healthy liver regions were analyzed. Results Results showed significant differences in kinetic parameters \documentclass[12pt]{minimal}
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\begin{document}$${K}_{i}$$\end{document}Ki between HCC and ICC lesions. Further investigations of the effect of SUV measurements on the derived kinetic parameters were conducted. And results showed comparable effectiveness of the kinetic modeling using either SUVmean or SUVmax measurements. Conclusions Dynamic 18F-FDG PET imaging with optimization-derived hepatic artery blood supply fraction dual-blood input function kinetic modeling can effectively distinguish malignant lesions from healthy liver tissue, as well as HCC and ICC lesions.
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Affiliation(s)
- Jingnan Wang
- Department of Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, People's Republic of China.,Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, People's Republic of China
| | - Yunwen Shao
- Department of Biomedical Engineering, Tsinghua University, Beijing, People's Republic of China
| | - Bowei Liu
- Department of Biomedical Engineering, Tsinghua University, Beijing, People's Republic of China
| | - Xuezhu Wang
- Department of Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, People's Republic of China.,Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, People's Republic of China
| | - Barbara Katharina Geist
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Xiang Li
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Fang Li
- Department of Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, People's Republic of China.,Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, People's Republic of China
| | - Haitao Zhao
- Department of Liver Surgery, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, People's Republic of China
| | - Marcus Hacker
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Haiyan Ding
- Department of Biomedical Engineering, Tsinghua University, Beijing, People's Republic of China
| | - Hui Zhang
- Department of Biomedical Engineering, Tsinghua University, Beijing, People's Republic of China.
| | - Li Huo
- Department of Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, People's Republic of China.,Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, People's Republic of China
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Schaart DR. Physics and technology of time-of-flight PET detectors. Phys Med Biol 2021; 66. [PMID: 33711831 DOI: 10.1088/1361-6560/abee56] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 03/12/2021] [Indexed: 01/04/2023]
Abstract
The imaging performance of clinical positron emission tomography (PET) systems has evolved impressively during the last ∼15 years. A main driver of these improvements has been the introduction of time-of-flight (TOF) detectors with high spatial resolution and detection efficiency, initially based on photomultiplier tubes, later silicon photomultipliers. This review aims to offer insight into the challenges encountered, solutions developed, and lessons learned during this period. Detectors based on fast, bright, inorganic scintillators form the scope of this work, as these are used in essentially all clinical TOF-PET systems today. The improvement of the coincidence resolving time (CRT) requires the optimization of the entire detection chain and a sound understanding of the physics involved facilitates this effort greatly. Therefore, the theory of scintillation detector timing is reviewed first. Once the fundamentals have been set forth, the principal detector components are discussed: the scintillator and the photosensor. The parameters that influence the CRT are examined and the history, state-of-the-art, and ongoing developments are reviewed. Finally, the interplay between these components and the optimization of the overall detector design are considered. Based on the knowledge gained to date, it appears feasible to improve the CRT from the values of 200-400 ps achieved by current state-of-the-art TOF-PET systems to about 100 ps or less, even though this may require the implementation of advanced methods such as time resolution recovery. At the same time, it appears unlikely that a system-level CRT in the order of ∼10 ps can be reached with conventional scintillation detectors. Such a CRT could eliminate the need for conventional tomographic image reconstruction and a search for new approaches to timestamp annihilation photons with ultra-high precision is therefore warranted. While the focus of this review is on timing performance, it attempts to approach the topic from a clinically driven perspective, i.e. bearing in mind that the ultimate goal is to optimize the value of PET in research and (personalized) medicine.
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Affiliation(s)
- Dennis R Schaart
- Delft University of Technology, Radiation Science & Technology dept., section Medical Physics & Technology, Mekelweg 15, 2629 JB Delft, The Netherlands
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Geist BK, Xing H, Wang J, Shi X, Zhao H, Hacker M, Sang X, Huo L, Li X. A methodological investigation of healthy tissue, hepatocellular carcinoma, and other lesions with dynamic 68Ga-FAPI-04 PET/CT imaging. EJNMMI Phys 2021; 8:8. [PMID: 33483880 PMCID: PMC7822999 DOI: 10.1186/s40658-021-00353-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 01/05/2021] [Indexed: 12/18/2022] Open
Abstract
Background The study aimed to establish a 68Ga-FAPI-04 kinetic model in hepatic lesions, to determine the potential role of kinetic parameters in the differentiation of hepatocellular carcinoma (HCC) from non-HCC lesions. Material and methods Time activity curves (TACs) were extracted from seven HCC lesions and five non-HCC lesions obtained from 68Ga-FAPI-04 dynamic positron emission tomography (PET) scans of eight patients. Three kinetic models were applied to the TACs, using image-derived hepatic artery and/or portal vein as input functions. The maximum standardized uptake value (SUVmax) was taken for the lesions, the hepatic artery, and for the portal veins—the mean SUV for all healthy regions. The optimum model was chosen after applying the Schwartz information criteria to the TACs, differences in model parameters between HCC, non-HCC lesions, and healthy tissue were evaluated with the ANOVA test. Results A reversible two-tissue compartment model using both the arterial as well as venous input function was most preferred and showed significant differences in the kinetic parameters VND, VT, and BPND between HCC, non-HCC lesions, and healthy regions (p < 0.01). Conclusion Several model parameters derived from a two-tissue compartment kinetic model with two image-derived input function from vein and aorta and using SUVmax allow a differentiation between HCC and non-HCC lesions, obtained from dynamically performed PET scans using FAPI.
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Affiliation(s)
- Barbara Katharina Geist
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Haiqun Xing
- Department of Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, 100730, China.,Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, 100730, China
| | - Jingnan Wang
- Department of Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, 100730, China.,Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, 100730, China
| | - Ximin Shi
- Department of Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, 100730, China.,Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, 100730, China
| | - Haitao Zhao
- Department of Liver Surgery, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, 100730, China
| | - Marcus Hacker
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Xinting Sang
- Department of Liver Surgery, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, 100730, China
| | - Li Huo
- Department of Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, 100730, China. .,Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, 100730, China.
| | - Xiang Li
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
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Salvadori J, Odille F, Karcher G, Marie PY, Imbert L. Fully digital PET is unaffected by any deterioration in TOF resolution and TOF image quality in the wide range of routine PET count rates. EJNMMI Phys 2021; 8:1. [PMID: 33409746 PMCID: PMC7788141 DOI: 10.1186/s40658-020-00344-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 11/30/2020] [Indexed: 12/11/2022] Open
Abstract
PURPOSE Digital PET involving silicon photomultipliers (SiPM) provides an enhanced time-of-flight (TOF) resolution as compared with photomultiplier (PMT)-based PET, but also a better prevention of the count-related rises in dead time and pile-up effects mainly due to smaller trigger domains (i.e., the detection surfaces associated with each trigger circuit). This study aimed to determine whether this latter property could help prevent against deteriorations in TOF resolution and TOF image quality in the wide range of PET count rates documented in clinical routine. METHODS Variations, according to count rates, in timing resolution and in TOF-related enhancement of the quality of phantom images were compared between the first fully digital PET (Vereos) and a PMT-based PET (Ingenuity). Single-count rate values were additionally extracted from the list-mode data of routine analog- and digital-PET exams at each 500-ms interval, in order to determine the ranges of routine PET count rates. RESULTS Routine PET count rates were lower for the Vereos than for the Ingenuity. For Ingenuity, the upper limits were estimated at approximately 21.7 and 33.2 Mcps after injection of respectively 3 and 5 MBq.kg-1 of current 18F-labeled tracers. At 5.8 Mcps, corresponding to the lower limit of the routine count rates documented with the Ingenuity, timing resolutions provided by the scatter phantom were 326 and 621 ps for Vereos and Ingenuity, respectively. At higher count rates, timing resolution was remarkably stable for Vereos but exhibited a progressive deterioration for Ingenuity, respectively reaching 732 and 847 ps at the upper limits of 21.7 and 33.2 Mcps. The averaged TOF-related gain in signal/noise ratio was stable at approximately 2 for Vereos but decreased from 1.36 at 5.8 Mcps to 1.14 and 1.00 at respectively 21.7 and 33.2 Mcps for Ingenuity. CONCLUSION Contrary to the Ingenuity PMT-based PET, the Vereos fully digital PET is unaffected by any deterioration in TOF resolution and consequently, in the quality of TOF images, in the wide range of routine PET count rates. This advantage is even more striking with higher count-rates for which the preferential use of digital PET should be further recommended (i.e., dynamic PET recording, higher injected activities).
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Affiliation(s)
- Julien Salvadori
- Department of Nuclear Medicine and Nancyclotep Molecular Imaging Platform, CHRU-Nancy, Université de Lorraine, F54000, Nancy, France. .,Université de Lorraine, INSERM, UMR 1254, F54000, Nancy, France.
| | - Freddy Odille
- Department of Nuclear Medicine and Nancyclotep Molecular Imaging Platform, CHRU-Nancy, Université de Lorraine, F54000, Nancy, France.,Université de Lorraine, INSERM, UMR 1254, F54000, Nancy, France
| | - Gilles Karcher
- Department of Nuclear Medicine and Nancyclotep Molecular Imaging Platform, CHRU-Nancy, Université de Lorraine, F54000, Nancy, France.,Université de Lorraine, INSERM, UMR 1254, F54000, Nancy, France
| | - Pierre-Yves Marie
- Department of Nuclear Medicine and Nancyclotep Molecular Imaging Platform, CHRU-Nancy, Université de Lorraine, F54000, Nancy, France.,Université de Lorraine, INSERM, UMR 1116, F54000, Nancy, France
| | - Laetitia Imbert
- Department of Nuclear Medicine and Nancyclotep Molecular Imaging Platform, CHRU-Nancy, Université de Lorraine, F54000, Nancy, France.,Université de Lorraine, INSERM, UMR 1254, F54000, Nancy, France
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8
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Geist BK, Wang J, Wang X, Lin J, Yang X, Zhang H, Li F, Zhao H, Hacker M, Huo L, Li X. Comparison of different kinetic models for dynamic 18F-FDG PET/CT imaging of hepatocellular carcinoma with various, also dual-blood input function. ACTA ACUST UNITED AC 2020; 65:045001. [DOI: 10.1088/1361-6560/ab66e3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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