Rahib L, Smith BD, Aizenberg R, Rosenzweig AB, Fleshman JM, Matrisian LM. Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the united States. Cancer Res. 2014;74:2913–21. https://doi.org/10.1158/0008-5472.CAN-14-0155.
Article CAS PubMed Google Scholar
Lee ES, Lee JM. Imaging diagnosis of pancreatic cancer: a state-of-the-art review. World J Gastroenterol. 2014;20:7864–77. https://doi.org/10.3748/wjg.v20.i24.7864.
Article PubMed PubMed Central Google Scholar
Schwenck J, Sonanini D, Cotton JM, Rammensee HG, la Fougere C, Zender L, et al. Advances in PET imaging of cancer. Nat Rev Cancer. 2023;23:474–90. https://doi.org/10.1038/s41568-023-00576-4.
Article CAS PubMed Google Scholar
Dias AH, Hansen AK, Munk OL, Gormsen LC. Normal values for (18)F-FDG uptake in organs and tissues measured by dynamic whole body multiparametric FDG PET in 126 patients. EJNMMI Res. 2022;12:15. https://doi.org/10.1186/s13550-022-00884-0.
Article CAS PubMed PubMed Central Google Scholar
Zhang X, Cherry SR, Xie Z, Shi H, Badawi RD, Qi J. Subsecond total-body imaging using ultrasensitive positron emission tomography. Proc Natl Acad Sci U S A. 2020;117:2265–7. https://doi.org/10.1073/pnas.1917379117.
Article CAS PubMed PubMed Central Google Scholar
Viswanath V, Chitalia R, Pantel AR, Karp JS, Mankoff DA. Analysis of Four-Dimensional data for total body PET imaging. PET Clin. 2021;16:55–64. https://doi.org/10.1016/j.cpet.2020.09.009.
Article PubMed PubMed Central Google Scholar
Sperti C, Pasquali C, Decet G, Chierichetti F, Liessi G, Pedrazzoli S. F-18-fluorodeoxyglucose positron emission tomography in differentiating malignant from benign pancreatic cysts: a prospective study. J Gastrointest Surg. 2005;9. https://doi.org/10.1016/j.gassur.2004.10.002. 22– 8; discussion 8–9.
Saif MW, Cornfeld D, Modarresifar H, Ojha B. 18F-FDG positron emission tomography CT (FDG PET-CT) in the management of pancreatic cancer: initial experience in 12 patients. J Gastrointestin Liver Dis. 2008;17:173–8.
Daamen LA, Groot VP, Goense L, Wessels FJ, Borel Rinkes IH, Intven MPW, et al. The diagnostic performance of CT versus FDG PET-CT for the detection of recurrent pancreatic cancer: a systematic review and meta-analysis. Eur J Radiol. 2018;106:128–36. https://doi.org/10.1016/j.ejrad.2018.07.010.
Zhang J, Jia G, Zuo C, Jia N, Wang H. (18)F- FDG PET/CT helps differentiate autoimmune pancreatitis from pancreatic cancer. BMC Cancer. 2017;17:695. https://doi.org/10.1186/s12885-017-3665-y.
Article CAS PubMed PubMed Central Google Scholar
Pakzad F, Groves AM, Ell PJ. The role of positron emission tomography in the management of pancreatic cancer. Semin Nucl Med. 2006;36:248–56. https://doi.org/10.1053/j.semnuclmed.2006.03.005.
Jha P, Bijan B. PET/CT for pancreatic malignancy: potential and pitfalls. J Nucl Med Technol. 2015;43:92–7. https://doi.org/10.2967/jnmt.114.145458.
Patlak CS, Blasberg RG, Fenstermacher JD. Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J Cereb Blood Flow Metab. 1983;3:1–7. https://doi.org/10.1038/jcbfm.1983.1.
Article CAS PubMed Google Scholar
Patlak CS, Blasberg RG. Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. Generalizations J Cereb Blood Flow Metab. 1985;5:584–90. https://doi.org/10.1038/jcbfm.1985.87.
Article CAS PubMed Google Scholar
Logan J, Fowler JS, Volkow ND, Wolf AP, Dewey SL, Schlyer DJ, et al. Graphical analysis of reversible radioligand binding from time-activity measurements applied to [N-11 C-methyl]-(-)-cocaine PET studies in human subjects. J Cereb Blood Flow Metab. 1990;10:740–7. https://doi.org/10.1038/jcbfm.1990.127.
Article CAS PubMed Google Scholar
Lammertsma AA, Bench CJ, Hume SP, Osman S, Gunn K, Brooks DJ, et al. Comparison of methods for analysis of clinical [11 C]raclopride studies. J Cereb Blood Flow Metab. 1996;16:42–52. https://doi.org/10.1097/00004647-199601000-00005.
Article CAS PubMed Google Scholar
Gambhir SS, Schwaiger M, Huang SC, Krivokapich J, Schelbert HR, Nienaber CA, et al. Simple noninvasive quantification method for measuring myocardial glucose utilization in humans employing positron emission tomography and fluorine-18 Deoxyglucose. J Nucl Med. 1989;30:359–66.
Ohtake T, Kosaka N, Watanabe T, Yokoyama I, Moritan T, Masuo M, et al. Noninvasive method to obtain input function for measuring tissue glucose utilization of thoracic and abdominal organs. J Nucl Med. 1991;32:1432–8.
Palard-Novello X, Visser D, Tolboom N, Smith CLC, Zwezerijnen G, van de Giessen E, et al. Validation of image-derived input function using a long axial field of view PET/CT scanner for two different tracers. EJNMMI Phys. 2024;11:25. https://doi.org/10.1186/s40658-024-00628-0.
Article PubMed PubMed Central Google Scholar
de Geus-Oei LF, Visser EP, Krabbe PF, van Hoorn BA, Koenders EB, Willemsen AT, et al. Comparison of image-derived and arterial input functions for estimating the rate of glucose metabolism in therapy-monitoring 18F-FDG PET studies. J Nucl Med. 2006;47:945–9.
Zanotti-Fregonara P, Fadaili el M, Maroy R, Comtat C, Souloumiac A, Jan S, et al. Comparison of eight methods for the Estimation of the image-derived input function in dynamic [(18)F]-FDG PET human brain studies. J Cereb Blood Flow Metab. 2009;29:1825–35. https://doi.org/10.1038/jcbfm.2009.93.
Zanotti-Fregonara P, Chen K, Liow JS, Fujita M, Innis RB. Image-derived input function for brain PET studies: many challenges and few opportunities. J Cereb Blood Flow Metab. 2011;31:1986–98. https://doi.org/10.1038/jcbfm.2011.107.
Article PubMed PubMed Central Google Scholar
Rissanen E, Tuisku J, Luoto P, Arponen E, Johansson J, Oikonen V, et al. Automated reference region extraction and population-based input function for brain [(11)C]TMSX PET image analyses. J Cereb Blood Flow Metab. 2015;35:157–65. https://doi.org/10.1038/jcbfm.2014.194.
Article CAS PubMed Google Scholar
Contractor KB, Kenny LM, Coombes CR, Turkheimer FE, Aboagye EO, Rosso L. Evaluation of limited blood sampling population input approaches for kinetic quantification of [18F]fluorothymidine PET data. EJNMMI Res. 2012;2:11. https://doi.org/10.1186/2191-219X-2-11.
Article CAS PubMed PubMed Central Google Scholar
Zanotti-Fregonara P, Hirvonen J, Lyoo CH, Zoghbi SS, Rallis-Frutos D, Huestis MA, et al. Population-based input function modeling for [(18)F]FMPEP-d 2, an inverse agonist radioligand for cannabinoid CB1 receptors: validation in clinical studies. PLoS ONE. 2013;8:e60231. https://doi.org/10.1371/journal.pone.0060231.
Article CAS PubMed PubMed Central Google Scholar
Sari H, Eriksson L, Mingels C, Alberts I, Casey ME, Afshar-Oromieh A, et al. Feasibility of using abbreviated scan protocols with population-based input functions for accurate kinetic modeling of [(18)F]-FDG datasets from a long axial FOV PET scanner. Eur J Nucl Med Mol Imaging. 2023;50:257–65. https://doi.org/10.1007/s00259-022-05983-7.
Article CAS PubMed Google Scholar
van Sluis J, Yaqub M, Brouwers AH, Dierckx R, Noordzij W, Boellaard R. Use of population input functions for reduced scan duration whole-body Patlak (18)F-FDG PET imaging. EJNMMI Phys. 2021;8:11. https://doi.org/10.1186/s40658-021-00357-8.
Article PubMed PubMed Central Google Scholar
Fahrni G, Karakatsanis NA, Di Domenicantonio G, Garibotto V, Zaidi H. Does whole-body Patlak (18)F-FDG PET imaging improve lesion detectability in clinical oncology? Eur Radiol. 2019;29:4812–21. https://doi.org/10.1007/s00330-018-5966-1.
Zaker N, Kotasidis F, Garibotto V, Zaidi H. Assessment of lesion detectability in dynamic Whole-Body PET imaging using compartmental and Patlak parametric mapping. Clin Nucl Med. 2020;45:e221–31. https://doi.org/10.1097/RLU.0000000000002954.
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