{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T08:52:14Z","timestamp":1791967934447,"version":"4.3.4"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T00:00:00Z","timestamp":1606089600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T00:00:00Z","timestamp":1606089600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100004340","name":"Siemens USA","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004340","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1 TR000142"],"award-info":[{"award-number":["UL1 TR000142"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1S10RR029245"],"award-info":[{"award-number":["1S10RR029245"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["EJNMMI Phys"],"published-print":{"date-parts":[[2020,12]]},"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n \n Arterial blood sampling is the gold standard method to obtain the arterial input function (AIF) for quantification of whole body (WB) dynamic\n 18<\/jats:sup>\n F-FDG PET imaging. However, this procedure is invasive and not typically available in clinical environments. As an alternative, we compared AIFs to population-based input functions (PBIFs) using two normalization methods: area under the curve (AUC) and extrapolated initial plasma concentration (\n C<\/jats:italic>\n P<\/jats:sub>\n *(0)). To scale the PBIFs, we tested two methods: (1) the AUC of the image-derived input function (IDIF) and (2) the estimated\n C<\/jats:italic>\n P<\/jats:sub>\n *(0). The aim of this study was to validate IDIF and PBIF for FDG oncological WB PET studies by comparing to the gold standard arterial blood sampling.\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n The Feng\n 18<\/jats:sup>\n F-FDG plasma concentration model was applied to estimate AIF parameters (\n n<\/jats:italic>\n = 23). AIF normalization used either AUC(0\u201360\u2009min) or\n C<\/jats:italic>\n P<\/jats:sub>\n *(0), estimated from an exponential fit.\n C<\/jats:italic>\n P<\/jats:sub>\n *(0) is also described as the ratio of the injected dose (\n ID<\/jats:italic>\n ) to initial distribution volume (\n iDV<\/jats:italic>\n ).\n iDV<\/jats:italic>\n was modeled using the subject height and weight, with coefficients that were estimated in 23 subjects. In 12 oncological patients, we computed IDIF (from the aorta) and PBIFs with scaling by the AUC of the IDIF from 4 time windows (15\u201345, 30\u201360, 45\u201375, 60\u201390\u2009min) (PBIF\n AUC<\/jats:sub>\n ) and estimated\n C<\/jats:italic>\n P<\/jats:sub>\n *(0) (PBIF\n iDV<\/jats:sub>\n ). The IDIF and PBIFs were compared with the gold standard AIF, using AUC values and Patlak\n K<\/jats:italic>\n i<\/jats:sub>\n values.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The IDIF underestimated the AIF at early times and overestimated it at later times. Thus, based on the AUC and\n K<\/jats:italic>\n i<\/jats:sub>\n comparison, 30\u201360\u2009min was the most accurate time window for PBIF\n AUC<\/jats:sub>\n ; later time windows for scaling underestimated\n K<\/jats:italic>\n i<\/jats:sub>\n (\u2212\u20096 \u00b1 8 to \u2212\u200913 \u00b1 9%). Correlations of AUC between AIF and IDIF, PBIF\n AUC(30\u201360)<\/jats:sub>\n , and PBIF\n iDV<\/jats:sub>\n were 0.91, 0.94, and 0.90, respectively. The bias of\n K<\/jats:italic>\n i<\/jats:sub>\n was \u2212\u20099 \u00b1 10%, \u2212\u20091 \u00b1 8%, and 3 \u00b1 9%, respectively.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Both PBIF scaling methods provided good mean performance with moderate variation. Improved performance can be obtained by refining IDIF methods and by evaluating PBIFs with test-retest data.<\/jats:p>\n <\/jats:sec>","DOI":"10.1186\/s40658-020-00330-x","type":"journal-article","created":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T04:08:35Z","timestamp":1606104515000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":81,"title":["Assessment of population-based input functions for Patlak imaging of whole body dynamic 18F-FDG PET"],"prefix":"10.1186","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4408-2621","authenticated-orcid":false,"given":"Mika","family":"Naganawa","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jean-Dominique","family":"Gallezot","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vijay","family":"Shah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tim","family":"Mulnix","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Colin","family":"Young","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Dias","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming-Kai","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne M.","family":"Smith","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard E.","family":"Carson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,11,23]]},"reference":[{"key":"330_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/jcbfm.1983.1","volume":"3","author":"CS Patlak","year":"1983","unstructured":"Patlak CS, Blasberg RG, Fenstermacher JD. 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This study was approved by the Yale University Human Investigation Committee and the Yale-New Haven Hospital Radiation Safety Committee.Informed consent was obtained from all patients included in this study.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"VS and AS are employees of Siemens Healthineers.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"67"}}