{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T14:25:54Z","timestamp":1781706354405,"version":"3.54.5"},"reference-count":32,"publisher":"IOP Publishing","issue":"6","license":[{"start":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T00:00:00Z","timestamp":1615507200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T00:00:00Z","timestamp":1615507200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012401","name":"Beijing Science and Technology Plan Project","doi-asserted-by":"crossref","award":["Z181100001618017"],"award-info":[{"award-number":["Z181100001618017"]}],"id":[{"id":"10.13039\/501100012401","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Peking University Medical Information Cross Project","award":["BMU2018MI009"],"award-info":[{"award-number":["BMU2018MI009"]}]},{"name":"Scientific Research Seed Fund of Peking University First Hospital","award":["2018SF052"],"award-info":[{"award-number":["2018SF052"]}]},{"name":"National Special Fund for the Development of Major Research Equipment and Instrument","award":["2011YQ03011409"],"award-info":[{"award-number":["2011YQ03011409"]}]},{"name":"National Science and Technology Infrastructure Program during the 12th Five-Year Plan Period","award":["2014BAA03B03"],"award-info":[{"award-number":["2014BAA03B03"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2021,3,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:sup>18<\/jats:sup>\n                    F-FDG uptake rate constant\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    is the main physiology parameter measured in dynamic PET studies. A model-independent graphical analysis using Patlak plot with plasma input function (PIF) is a standard approach used to estimate\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    <jats:italic>.<\/jats:italic>\n                    The PIF is the\n                    <jats:sup>18<\/jats:sup>\n                    F-FDG time activity curve (TAC) in plasma that is obtained by serial arterial blood sampling. The purpose of the study is to evaluate a Patlak plot-based optimization approach with reduced blood samples for noninvasive quantification of dynamic\n                    <jats:sup>18<\/jats:sup>\n                    F-FDG PET imaging. Eight 60 min rhesus monkey brain dynamic\n                    <jats:sup>18<\/jats:sup>\n                    F-FDG PET scans with arterial blood samples were collected. The measured PIF (mPIF) was determined by arterial blood samples. TACs of seven cerebral regions of interest were generated from each study. With a given number of blood samples, the population-based PIF (pPIF) was determined by either interpolation or extrapolation method using scale calibrated population mean of normalized PIF. The optimal sampling scheme with given blood sample size was determined by maximizing the correlations between the\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    estimated from pPIF and those obtained by mPIF. A leave-two-out cross-validation method was used for evaluation. The linear correlations between the\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    estimates from pPIF with optimal sampling schemes and those from mPIF were:\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    (pPIF 1 sample at 40 min)\u00a0=\u00a01.015\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    (mPIF) \u2212 0.000,\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    \u00a0=\u00a00.974;\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    (pPIF 2 samples at 35 and 50 min)\u00a0=\u00a01.052\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    (mPIF) \u2212 0.001,\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    \u00a0=\u00a00.976;\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    (pPIF 3 samples at 12, 40, and 50 min)\u00a0=\u00a01.030\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    (mPIF) \u2212 0.000,\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    \u00a0=\u00a00.985; and\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    (pPIF 4 samples at 10, 20, 40, and 50 min)\u00a0=\u00a01.016\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    (mPIF)- 0.000,\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    \u00a0=\u00a00.993. As the sample size became greater or equal to 4, the\n                    <jats:italic>\n                      K\n                      <jats:sub>i<\/jats:sub>\n                    <\/jats:italic>\n                    estimates from pPIF with the optimal protocol were almost identical to those from mPIF. The Patlak plot-based optimization approach is a reliable method to estimate PIF for noninvasive quantification of non-human primate dynamic\n                    <jats:sup>18<\/jats:sup>\n                    F-FDG PET imaging and is potentially extendable to further translational human studies.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/abe83b","type":"journal-article","created":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T05:49:45Z","timestamp":1615528185000},"page":"064005","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Noninvasive quantification of nonhuman primate dynamic\n                    <sup>18<\/sup>\n                    F-FDG PET imaging"],"prefix":"10.1088","volume":"66","author":[{"given":"Xueqi","family":"Chen","sequence":"first","affiliation":[{"name":"Peking University First Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sulei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Peking University First Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianhua","family":"Zhang","sequence":"additional","affiliation":[{"name":"Peking University First Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lixin","family":"Chen","sequence":"additional","affiliation":[{"name":"Peking University First Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rongfu","family":"Wang","sequence":"additional","affiliation":[{"name":"Peking University First Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yun","family":"Zhou","sequence":"additional","affiliation":[{"name":"Peking University First Hospital"},{"name":"Washington University"},{"name":"Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, 201807,"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2021,3,12]]},"reference":[{"key":"pmbabe83bbib1","doi-asserted-by":"publisher","first-page":"748","DOI":"10.1007\/s11307-015-0895-8","type":"journal-article","article-title":"Determination of the input function at the entry of the tissue of interest and its impact on PET kinetic modeling parameters","volume":"17","author":"Bentourkia","year":"2015","journal-title":"Mol. Imaging Biol."},{"key":"pmbabe83bbib2","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1109\/42.774165","type":"journal-article","article-title":"A standardized blood sampling scheme in quantitative FDG-PET studies","volume":"18","author":"Bentourkia","year":"1999","journal-title":"IEEE Trans. Med. Imaging"},{"key":"pmbabe83bbib3","doi-asserted-by":"publisher","first-page":"e89282","DOI":"10.1371\/journal.pone.0089282","type":"journal-article","article-title":"Dynamic positron emission tomography image restoration via a kinetics-induced bilateral filter","volume":"9","author":"Bian","year":"2014","journal-title":"PLoS One"},{"key":"pmbabe83bbib4","doi-asserted-by":"publisher","first-page":"11S","DOI":"10.2967\/jnumed.108.057182","type":"journal-article","article-title":"Standards for PET image acquisition and quantitative data analysis","volume":"50","author":"Boellaard","year":"2009","journal-title":"J. Nucl. Med."},{"key":"pmbabe83bbib5","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1007\/s00259-014-2961-x","type":"journal-article","article-title":"FDG PET\/CT: EANM procedure guidelines for tumour imaging: version 2.0","volume":"42","author":"Boellaard","year":"2015","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"pmbabe83bbib6","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1080\/17460441.2017.1271320","type":"journal-article","article-title":"Non human primate models for Alzheimer\u2019s disease-related research and drug discovery","volume":"12","author":"Van Dam","year":"2017","journal-title":"Expert Opin. Drug Dis."},{"key":"pmbabe83bbib7","doi-asserted-by":"publisher","first-page":"4812","DOI":"10.1007\/s00330-018-5966-1","type":"journal-article","article-title":"Does whole-body Patlak F-FDG PET imaging improve lesion detectability in clinical oncology?","volume":"29","author":"Fahrni","year":"2019","journal-title":"Eur. Radiol."},{"key":"pmbabe83bbib8","doi-asserted-by":"publisher","first-page":"576470","DOI":"10.1155\/2013\/576470","type":"journal-article","article-title":"Using dynamic contrast-enhanced magnetic resonance imaging data to constrain a positron emission tomography kinetic model: theory and simulations","volume":"2013","author":"Fluckiger","year":"2013","journal-title":"Int. J. Biomed. Imaging"},{"key":"pmbabe83bbib9","doi-asserted-by":"publisher","first-page":"E413","DOI":"10.1152\/ajpendo.00284.2017","type":"journal-article","article-title":"Free fatty acid flux measured using [1-(11)C]palmitate positron emission tomography and [U-(13)C]palmitate in humans","volume":"314","author":"Han","year":"2018","journal-title":"Am. J. Physiol. Endocrinol. Metab."},{"key":"pmbabe83bbib10","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.1109\/TMI.2014.2305113","type":"journal-article","article-title":"An analysis of whole body tracer kinetics in dynamic PET studies with application to image-based blood input function extraction","volume":"33","author":"Huang","year":"2014","journal-title":"IEEE Trans. Med. Imaging"},{"key":"pmbabe83bbib11","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1186\/s13550-016-0230-7","type":"journal-article","article-title":"Comparison of the image-derived radioactivity and blood-sample radioactivity for estimating the clinical indicators of the efficacy of boron neutron capture therapy (BNCT): 4-borono-2-(18)F-fluoro-phenylalanine (FBPA) PET study","volume":"6","author":"Isohashi","year":"2016","journal-title":"EJNMMI Res."},{"key":"pmbabe83bbib12","doi-asserted-by":"publisher","first-page":"7391","DOI":"10.1088\/0031-9155\/58\/20\/7391","type":"journal-article","article-title":"Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application","volume":"58","author":"Karakatsanis","year":"2013","journal-title":"Phys. Med. Biol."},{"key":"pmbabe83bbib13","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1186\/s13550-015-0149-4","type":"journal-article","article-title":"Radiation dosimetry of [(18)F]VAT in nonhuman primates","volume":"5","author":"Karimi","year":"2015","journal-title":"EJNMMI Res."},{"key":"pmbabe83bbib14","doi-asserted-by":"publisher","first-page":"7889","DOI":"10.1088\/0031-9155\/58\/22\/7889","type":"journal-article","article-title":"Novel system using microliter order sample volume for measuring arterial radioactivity concentrations in whole blood and plasma for mouse PET dynamic study","volume":"58","author":"Kimura","year":"2013","journal-title":"Phys. Med. Biol."},{"key":"pmbabe83bbib15","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1021\/cn500269g","type":"journal-article","article-title":"Development of [(11)C]MFTC for PET imaging of fatty acid amide hydrolase in rat and monkey brains","volume":"6","author":"Kumata","year":"2015","journal-title":"ACS Chem. Neurosci."},{"key":"pmbabe83bbib16","doi-asserted-by":"publisher","first-page":"1283","DOI":"10.1002\/mds.26302","type":"journal-article","article-title":"Reproducibility of a parkinsonism-related metabolic brain network in non-human primates: a descriptive pilot study with FDG PET","volume":"30","author":"Ma","year":"2015","journal-title":"Mov. Disord."},{"key":"pmbabe83bbib17","doi-asserted-by":"publisher","first-page":"3103","DOI":"10.1109\/TBME.2013.2267778","type":"journal-article","article-title":"Noninvasive estimation of the input function for dynamic mouse 18F-FDG microPET studies","volume":"60","author":"Mu","year":"2013","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"pmbabe83bbib18","doi-asserted-by":"publisher","first-page":"e22931","DOI":"10.1002\/ajp.22931","type":"journal-article","article-title":"Generation of genetically engineered non-human primate models of brain function and neurological disorders","volume":"81","author":"Park","year":"2019","journal-title":"Am. J. Primatol."},{"key":"pmbabe83bbib19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/jcbfm.1983.1","type":"journal-article","article-title":"Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data","volume":"3","author":"Patlak","year":"1983","journal-title":"J. Cereb. Blood Flow Metab."},{"key":"pmbabe83bbib20","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1007\/s12264-014-1465-9","type":"journal-article","article-title":"Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses","volume":"30","author":"Seo","year":"2014","journal-title":"Neurosci. Bull."},{"key":"pmbabe83bbib21","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1186\/2191-219X-3-66","type":"journal-article","article-title":"Comparison between kinetic modelling and graphical analysis for the quantification of [18F]fluoromethylcholine uptake in mice","volume":"3","author":"Slaets","year":"2013","journal-title":"EJNMMI Res."},{"key":"pmbabe83bbib22","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1016\/j.jcmg.2012.11.015","type":"journal-article","article-title":"Variation in quantitative myocardial perfusion due to arterial input selection","volume":"6","author":"Vasquez","year":"2013","journal-title":"JACC Cardiovasc. Imaging"},{"key":"pmbabe83bbib23","first-page":"928","type":"journal-article","article-title":"Differential diagnosis of pulmonary lesions by parametric imaging in (18)F-FDG PET\/CT dynamic multi-bed scanning","volume":"18","author":"Wang","year":"2013","journal-title":"J. BUON."},{"key":"pmbabe83bbib24","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1007\/s00259-006-0224-1","type":"journal-article","article-title":"Quantification of FDG PET studies using standardised uptake values in multi-centre trials: effects of image reconstruction, resolution and ROI definition parameters","volume":"34","author":"Westerterp","year":"2007","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"pmbabe83bbib25","doi-asserted-by":"publisher","first-page":"1986","DOI":"10.1038\/jcbfm.2011.107","type":"journal-article","article-title":"Image-derived input function for brain PET studies: many challenges and few opportunities","volume":"31","author":"Zanotti-Fregonara","year":"2011","journal-title":"J. Cereb. Blood Flow Metab."},{"key":"pmbabe83bbib26","doi-asserted-by":"publisher","first-page":"1825","DOI":"10.1038\/jcbfm.2009.93","type":"journal-article","article-title":"Comparison of eight methods for the estimation of the image-derived input function in dynamic [(18)F]-FDG PET human brain studies","volume":"29","author":"Zanotti-Fregonara","year":"2009","journal-title":"J. Cereb. Blood Flow Metab."},{"key":"pmbabe83bbib27","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1006\/nimg.2001.1021","type":"journal-article","article-title":"Improved parametric image generation using spatial-temporal analysis of dynamic PET studies","volume":"15","author":"Zhou","year":"2002","journal-title":"Neuroimage"},{"key":"pmbabe83bbib28","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1016\/j.neuroimage.2008.09.021","type":"journal-article","article-title":"A consistent and efficient graphical analysis method to improve the quantification of reversible tracer binding in radioligand receptor dynamic PET studies","volume":"44","author":"Zhou","year":"2009","journal-title":"Neuroimage"},{"key":"pmbabe83bbib29","doi-asserted-by":"publisher","first-page":"2947","DOI":"10.1016\/j.neuroimage.2009.11.028","type":"journal-article","article-title":"Multi-graphical analysis of dynamic PET","volume":"49","author":"Zhou","year":"2010","journal-title":"Neuroimage"},{"key":"pmbabe83bbib30","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1007\/s11307-018-1241-8","type":"journal-article","article-title":"Quantitative analysis of heterogeneous [F]FDG static (SUV) vs. patlak (Ki) whole-body PET imaging using different segmentation methods: a simulation study","volume":"21","author":"Zhuang","year":"2019","journal-title":"Mol. Imaging Biol."},{"key":"pmbabe83bbib31","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1148\/rg.2016150102","type":"journal-article","article-title":"Role of optimal quantification of FDG PET imaging in the clinical practice of radiology","volume":"36","author":"Ziai","year":"2016","journal-title":"Radiographics"},{"key":"pmbabe83bbib32","doi-asserted-by":"publisher","first-page":"165004","DOI":"10.1088\/1361-6560\/aad444","type":"journal-article","article-title":"Relative Patlak plot for dynamic PET parametric imaging without the need for early-time input function","volume":"63","author":"Zuo","year":"2018","journal-title":"Phys. Med. Biol."}],"container-title":["Physics in Medicine &amp; Biology"],"original-title":[],"link":[{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/abe83b","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/abe83b\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/abe83b\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/abe83b\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T17:02:52Z","timestamp":1778778172000},"score":1,"resource":{"primary":{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/abe83b"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,12]]},"references-count":32,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2021,3,12]]},"published-print":{"date-parts":[[2021,3,21]]}},"URL":"https:\/\/doi.org\/10.1088\/1361-6560\/abe83b","relation":{},"ISSN":["0031-9155","1361-6560"],"issn-type":[{"value":"0031-9155","type":"print"},{"value":"1361-6560","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,12]]},"assertion":[{"value":"Noninvasive quantification of nonhuman primate dynamic\n                      18\n                      F-FDG PET imaging","name":"article_title","label":"Article Title"},{"value":"Physics in Medicine & Biology","name":"journal_title","label":"Journal Title"},{"value":"paper","name":"article_type","label":"Article Type"},{"value":"\u00a9 2021 The Author(s). Published on behalf of Institute of Physics and Engineering in Medicine by IOP Publishing Ltd","name":"copyright_information","label":"Copyright Information"},{"value":"2020-07-31","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2021-02-19","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2021-03-12","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}