Citation: | GONG Tan, SHANG Fei, TANG Xiaoying, HUO Li, LIU Shuai. Relationship Between Pharmacokinetic Parameters and Imaging Duration in Dynamic 11C-Acetate Cardiac PET/CT[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(4): 758-765. DOI: 10.12290/xhyxzz.2023-0121 |
[1] |
Lindner O, Sorensen J, Vogt J, et al. Cardiac efficiency and oxygen consumption measured with 11C-acetate PET after long-term cardiac resynchronization therapy[J]. J Nucl Med, 2006, 47: 378-383.
|
[2] |
Sorensen J, Valind S, Andersson LG. Simultaneous quantification of myocardial perfusion, oxidative metabolism, cardiac efficiency and pump function at rest and during supine bicycle exercise using 11C-acetate PET - a pilot study[J]. Clin Physiol Funct Imaging, 2010, 30: 279-284. DOI: 10.1111/j.1475-097X.2010.00938.x
|
[3] |
Liu S, Lin X, Shi X, et al. Myocardial tissue and metabolism characterization in men with alcohol consumption by cardiovascular magnetic resonance and 11C-acetate PET/CT[J]. J Cardiovasc Magn R, 2020, 22: 23. DOI: 10.1186/s12968-020-00614-2
|
[4] |
Ukkonen H, Knuuti J, Katoh C, et al. Use of [11 C] acetate and [15 O] O2 PET for the assessment of myocardial oxygen utilization in patients with chronic myocardial infarction[J]. Eur J Nucl Med, 2001, 28: 334-339. DOI: 10.1007/s002590000444
|
[5] |
Nesterov SV, Turta O, Han C, et al. 11C acetate has excellent reproducibility for quantification of myocardial oxidative metabolism[J]. Eur Heart J Cardiovasc Imaging, 2015, 16: 500-506. DOI: 10.1093/ehjci/jeu289
|
[6] |
Torizuka T, Nobezawa S, Momiki S, et al. Short dynamic FDG-PET imaging protocol for patients with lung cancer[J]. Eur J Nucl Med, 2000, 27: 1538-1542. DOI: 10.1007/s002590000312
|
[7] |
Visser EP, Kienhorst L, Geus-Oei L, et al. Shortened dynamic FDG-PET protocol to determine the glucose metabolic rate in non-small cell lung carcinoma[C]. 2008 IEEE Nuclear Science Symposium Conference Record. IEEE, 2008: 4455-4458.
|
[8] |
Monden T, Kudomi N, Sasakawa Y, et al. Shortening the duration of [18 F] FDG PET brain examination for diagnosis of brain glioma[J]. Mol Imaging Biol, 2011, 13: 754-758. DOI: 10.1007/s11307-010-0384-z
|
[9] |
Liu G, Yu H, Shi D, et al. Short-time total-body dynamic PET imaging performance in quantifying the kinetic metrics of 18F-FDG in healthy volunteers[J]. Eur J Nucl Med Mol Imaging, 2022, 49: 2493-2503. DOI: 10.1007/s00259-021-05500-2
|
[10] |
Samimi R, Kamali-Asl A, Geramifar P, et al. Short-duration dynamic FDG PET imaging: optimization and clinical application[J]. Phys Med, 2020, 80: 193-200. DOI: 10.1016/j.ejmp.2020.11.004
|
[11] |
Cerqueira MD, Weissman NJ, Dilsizian V, et al. Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart: a statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association[J]. Circulation, 2002, 105: 539-542. DOI: 10.1161/hc0402.102975
|
[12] |
何升级, 刘帅, 张辉, 等. 基于交替方向乘子法(ADMM)直接重建心脏11C-acetate PET动力学参数图[J]. 中国医学影像技术, 2022, 38: 758-763. https://www.cnki.com.cn/Article/CJFDTOTAL-ZYXX202205029.htm
|
[13] |
Dimitrakopoulou-Strauss A, Strauss LG, Heichel T, et al. The role of quantitative (18)F-FDG PET studies for the differentiation of malignant and benign bone lesions[J]. J Nucl Med, 2002, 43: 510-518.
|
[14] |
Dimitrakopoulou-Strauss A, Strauss LG, Schwarzbach M, et al. Dynamic PET 18F-FDG studies in patients with primary and recurrent soft-tissue sarcomas: impact on diagnosis and correlation with grading[J]. J Nucl Med, 2001, 42: 713-720.
|
[15] |
Rusten E, Rodal J, Revheim ME, et al. Quantitative dynamic (18)FDG-PET and tracer kinetic analysis of soft tissue sarcomas[J]. Acta Oncol, 2013, 52: 1160-1167. DOI: 10.3109/0284186X.2012.728713
|
[16] |
Strauss LG, Dimitrakopoulou-Strauss A, Koczan D, et al. 18F-FDG kinetics and gene expression in giant cell tumors[J]. J Nucl Med, 2004, 45: 1528-1535.
|
[17] |
Dimitrakopoulou-Strauss A, Hohenberger P, Pan L, et al. Dynamic PET with FDG in patients with unresectable aggressive fibromatosis: regression-based parametric images and correlation to the FDG kinetics based on a 2-tissue compartment model[J]. Clin Nucl Med, 2012, 37: 943-948. DOI: 10.1097/RLU.0b013e31825b1da4
|
[18] |
Humbert O, Lasserre M, Bertaut A, et al. Breast cancer blood flow and metabolism on dual-acquisition (18)F-FDG PET: correlation with tumor phenotype and neoadjuvant chemotherapy response[J]. J Nucl Med, 2018, 59: 1035-1041. DOI: 10.2967/jnumed.117.203075
|
[19] |
Ye Q, Wu J, Lu Y, et al. Improved discrimination between benign and malignant LDCT screening-detected lung nodules with dynamic over static 18F-FDG PET as a function of injected dose[J]. Phys Med Biol, 2018, 63: 175015. DOI: 10.1088/1361-6560/aad97f
|
[20] |
Nishiyama Y, Yamamoto Y, Monden T, et al. Diagnostic value of kinetic analysis using dynamic FDG PET in immunocompetent patients with primary CNS lymphoma[J]. Eur J Nucl Med Mol Imaging, 2007, 34: 78-86. DOI: 10.1007/s00259-006-0153-z
|
[1] | ZHANG Ning, RUAN Gechong, JIAO Yang, LIU Xiaoqing, Jonathan Lio, KANG Lin. Research Hotspots and Trends of Growth Mindset in Medical Education: A Bibliometric Analysis[J]. Medical Journal of Peking Union Medical College Hospital. DOI: 10.12290/xhyxzz.2024-0796 |
[2] | JIANG Wenli, HUANG Tian, WANG Furui, ZHOU Guangbo, ZHENG Ya, WANG Yuping, HU Zenan. A Bibliometric Analysis of the Relationship Between Oral Microbiome and Digestive System Diseases[J]. Medical Journal of Peking Union Medical College Hospital. DOI: 10.12290/xhyxzz.2024-0877 |
[3] | ZHANG Ning, HE Mu, ZHANG Xiangyu, KANG Lin, SUN Xiaohong, LIU Xiaohong, QU Xuan, ZHU Minglei. A Bibliometric Analysis of the Development of Global Research on Geriatric Interdisciplinary Team From 2000 to 2023[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(5): 1107-1116. DOI: 10.12290/xhyxzz.2024-0180 |
[4] | SUN Jianhua, LUO Hongbo, LI Zunzhu, LU Meishan, LIAN Hui, WANG Xiaoting, Critical Care Ultrasound Study Group. Cognition and Practice of Doctor-Nurse Integration Construction in the Department of Critical Care Medicine[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(3): 518-521. DOI: 10.12290/xhyxzz.2024-0116 |
[5] | SHI Xiuqing, YAN Siyu, HUANG Qiao, LI Xuhui, WANG Yongbo, MA Wenhao, SHANG Hongcai, JIN Yinghui. Real World Research: Bridging the Gap Between Clinical Practice Guidelines and Clinical Decision Making[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(4): 859-867. DOI: 10.12290/xhyxzz.2022-0217 |
[6] | LIU Yuan, ZHAO Lin. Update and Interpretation of 2022 National Comprehensive Cancer Network Clinical Practice Guidelines for Gastric Cancer[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(6): 999-1004. DOI: 10.12290/xhyxzz.2022-0271 |
[7] | SHI Jiyuan, TIAN Jinhui, GAO Ya, XU Jian'guo, LI Zheng. A Bibliometric Analysis of the Global Research Output on Artificial Intelligence Clinical Research[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(5): 871-879. DOI: 10.12290/xhyxzz.2021-0746 |
[8] | XU Haojie, WANG Lu, LIU Mingjuan, ZHAO Lidan. Analysis of Integrating Training in Scientific Research and Clinical Practice among Current Medical Postgraduates of Three Academic Systems[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(1): 66-73. DOI: 10.12290/xhyxzz.2021-0623 |
[9] | Li-fan ZHANG, Xiao-qing LIU. Study Design and Clinical Practice of Diagnostic Accucary Test[J]. Medical Journal of Peking Union Medical College Hospital, 2020, 11(1): 96-101. DOI: 10.3969/j.issn.1674-9081.20190276 |
[10] | Yao-long CHEN, Hong-cai SHANG, Ke-hu YANG, Chen WANG. International Experience and China's Route in Clinical Practice Guidelines[J]. Medical Journal of Peking Union Medical College Hospital, 2019, 10(3): 289-292. DOI: 10.3969/j.issn.1674-9081.2019.03.018 |