{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T04:30:14Z","timestamp":1772166614049,"version":"3.50.1"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T00:00:00Z","timestamp":1713225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T00:00:00Z","timestamp":1713225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"National Institute of Health","award":["P30-AG072972"],"award-info":[{"award-number":["P30-AG072972"]}]},{"name":"Lena Bainer Alzheimer Research Fund","award":["n\/A"],"award-info":[{"award-number":["n\/A"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["EJNMMI Res"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Kinetic modeling of\n                      <jats:sup>18<\/jats:sup>\n                      F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic\n                      <jats:sup>18<\/jats:sup>\n                      F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      <jats:sup>18<\/jats:sup>\n                      F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer\u2019s disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30\u00a0s after injection. Dynamic time-activity curves (TACs) for 110\u00a0min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (V\n                      <jats:sub>T<\/jats:sub>\n                      , V\n                      <jats:sub>s<\/jats:sub>\n                      ) in key brain regions with early amyloid accumulation. Non-displaceable binding potential (\n                      <jats:inline-formula>\n                        <jats:tex-math>$$ {BP}_{ND})$$<\/jats:tex-math>\n                      <\/jats:inline-formula>\n                      was also calculated from the multi-reference tissue model (MRTM).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Amyloid-positive (AD) patients showed the highest V\n                      <jats:sub>T<\/jats:sub>\n                      and V\n                      <jats:sub>S<\/jats:sub>\n                      in anterior cingulate, posterior cingulate, and precuneus, consistent with\n                      <jats:inline-formula>\n                        <jats:tex-math>$$ {BP}_{ND}$$<\/jats:tex-math>\n                      <\/jats:inline-formula>\n                      analysis.\n                      <jats:inline-formula>\n                        <jats:tex-math>$$ {BP}_{ND} $$<\/jats:tex-math>\n                      <\/jats:inline-formula>\n                      and V\n                      <jats:sub>T<\/jats:sub>\n                      from kinetic models were correlated (r\u00b2 = 0.46,\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20092\n                      <jats:inline-formula>\n                        <jats:tex-math>$$ {e}^{-16})$$<\/jats:tex-math>\n                      <\/jats:inline-formula>\n                      with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. V\n                      <jats:sub>T<\/jats:sub>\n                      from 2TCM was highly correlated (\n                      <jats:inline-formula>\n                        <jats:tex-math>$$ {r}^{2}$$<\/jats:tex-math>\n                      <\/jats:inline-formula>\n                      = 0.65,\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20092\n                      <jats:inline-formula>\n                        <jats:tex-math>$$ {e}^{-16}$$<\/jats:tex-math>\n                      <\/jats:inline-formula>\n                      ) with Logan graphical V\n                      <jats:sub>T<\/jats:sub>\n                      estimation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      Non-invasive quantification of amyloid binding from total-body\n                      <jats:sup>18<\/jats:sup>\n                      F-florbetaben PET data is feasible using aorta IDIFs with high agreement between kinetic distribution volume parameters compared to\n                      <jats:inline-formula>\n                        <jats:tex-math>$$ {BP}_{ND} $$<\/jats:tex-math>\n                      <\/jats:inline-formula>\n                      in amyloid-positive and amyloid-negative older individuals.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13550-024-01104-7","type":"journal-article","created":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T11:19:33Z","timestamp":1713266373000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Non-invasive quantification of 18F-florbetaben with total-body EXPLORER PET"],"prefix":"10.1186","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-9420-9195","authenticated-orcid":false,"given":"Emily Nicole","family":"Holy","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elizabeth","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anjan","family":"Bhattarai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evan","family":"Fletcher","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evelyn R.","family":"Alfaro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Danielle J.","family":"Harvey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Benjamin A.","family":"Spencer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon R.","family":"Cherry","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Charles S.","family":"DeCarli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Audrey P.","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,4,16]]},"reference":[{"key":"1104_CR1","doi-asserted-by":"publisher","first-page":"624330","DOI":"10.3389\/fnagi.2021.624330","volume":"13","author":"W Bao","year":"2021","unstructured":"Bao W, Xie F, Zuo C, Guan Y, Huang YH. PET neuroimaging of Alzheimer\u2019s Disease: Radiotracers and their utility in Clinical Research. Front Aging Neurosci. 2021;13:624330. https:\/\/doi.org\/10.3389\/fnagi.2021.624330.","journal-title":"Front Aging Neurosci"},{"issue":"3","key":"1104_CR2","doi-asserted-by":"publisher","first-page":"393","DOI":"10.14283\/jpad.2022.48","volume":"9","author":"J Delrieu","year":"2022","unstructured":"Delrieu J, Bateman RJ, Touchon J, Sabbagh M, Cummings J. The future of AD clinical trials with the Advent of Anti-amyloid therapies: an CTAD Task Force Report. J Prev Alzheimers Dis. 2022;9(3):393\u20139. https:\/\/doi.org\/10.14283\/jpad.2022.48.","journal-title":"J Prev Alzheimers Dis"},{"issue":"10","key":"1104_CR3","doi-asserted-by":"publisher","first-page":"682","DOI":"10.1007\/s12149-016-1115-6","volume":"30","author":"WH Choi","year":"2016","unstructured":"Choi WH, Um YH, Jung WS, Kim SH. Automated quantification of amyloid positron emission tomography: a comparison of PMOD and MIMneuro. Ann Nucl Med. 2016;30(10):682\u20139. https:\/\/doi.org\/10.1007\/s12149-016-1115-6.","journal-title":"Ann Nucl Med"},{"key":"1104_CR4","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1016\/j.nicl.2017.04.025","volume":"15","author":"S Bullich","year":"2017","unstructured":"Bullich S, Seibyl J, Catafau AM, et al. Optimized classification of 18F-Florbetaben PET scans as positive and negative using an SUVR quantitative approach and comparison to visual assessment. NeuroImage Clin. 2017;15:325\u201332. https:\/\/doi.org\/10.1016\/j.nicl.2017.04.025.","journal-title":"NeuroImage Clin"},{"key":"1104_CR5","doi-asserted-by":"publisher","first-page":"117953","DOI":"10.1016\/j.neuroimage.2021.117953","volume":"234","author":"F Heeman","year":"2021","unstructured":"Heeman F, Yaqub M, Hendriks J, et al. Parametric imaging of dual-time window [18F]flutemetamol and [18F]florbetaben studies. NeuroImage. 2021;234:117953. https:\/\/doi.org\/10.1016\/j.neuroimage.2021.117953.","journal-title":"NeuroImage"},{"issue":"1","key":"1104_CR6","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1186\/s13550-019-0499-4","volume":"9","author":"F Heeman","year":"2019","unstructured":"Heeman F, Yaqub M, Lopes Alves I, et al. Optimized dual-time-window protocols for quantitative [18F]flutemetamol and [18F]florbetaben PET studies. EJNMMI Res. 2019;9(1):32. https:\/\/doi.org\/10.1186\/s13550-019-0499-4.","journal-title":"EJNMMI Res"},{"issue":"1","key":"1104_CR7","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1007\/s40336-015-0102-6","volume":"3","author":"O Sabri","year":"2015","unstructured":"Sabri O, Seibyl J, Rowe C, Barthel H. Beta-amyloid imaging with florbetaben. Clin Transl Imaging. 2015;3(1):13\u201326. https:\/\/doi.org\/10.1007\/s40336-015-0102-6.","journal-title":"Clin Transl Imaging"},{"issue":"9","key":"1104_CR8","doi-asserted-by":"publisher","first-page":"1533","DOI":"10.1038\/sj.jcbfm.9600493","volume":"27","author":"RB Innis","year":"2007","unstructured":"Innis RB, Cunningham VJ, Delforge J, et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab off J Int Soc Cereb Blood Flow Metab. 2007;27(9):1533\u20139. https:\/\/doi.org\/10.1038\/sj.jcbfm.9600493.","journal-title":"J Cereb Blood Flow Metab off J Int Soc Cereb Blood Flow Metab"},{"issue":"3","key":"1104_CR9","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1177\/0271678X20918029","volume":"41","author":"F Heeman","year":"2021","unstructured":"Heeman F, Yaqub M, Lopes Alves I, et al. Simulating the effect of cerebral blood flow changes on regional quantification of [18F]flutemetamol and [18F]florbetaben studies. J Cereb Blood Flow Metab. 2021;41(3):579\u201389. https:\/\/doi.org\/10.1177\/0271678X20918029.","journal-title":"J Cereb Blood Flow Metab"},{"key":"1104_CR10","unstructured":"Morris ED, Endres CJ, Schmidt KC, Christian BT Jr, Fisher RFM. RE. Kinetic Modeling in Positron Emission Tomography."},{"key":"1104_CR11","volume-title":"Introduction to modeling in Physiology and Medicine","author":"CC Cobeli","year":"2019","unstructured":"Cobeli CC. Introduction to modeling in Physiology and Medicine. 2nd ed. London: Elsevier\/Academic; 2019.","edition":"2"},{"issue":"381","key":"1104_CR12","doi-asserted-by":"publisher","first-page":"eaaf6169","DOI":"10.1126\/scitranslmed.aaf6169","volume":"9","author":"SR Cherry","year":"2017","unstructured":"Cherry SR, Badawi RD, Karp JS, Moses WW, Price P, Jones T. Total-body imaging: transforming the role of positron emission tomography. Sci Transl Med. 2017;9(381):eaaf6169. https:\/\/doi.org\/10.1126\/scitranslmed.aaf6169.","journal-title":"Sci Transl Med"},{"issue":"6","key":"1104_CR13","doi-asserted-by":"publisher","first-page":"861","DOI":"10.2967\/jnumed.120.250597","volume":"62","author":"BA Spencer","year":"2021","unstructured":"Spencer BA, Berg E, Schmall JP, et al. Performance evaluation of the uEXPLORER Total-Body PET\/CT scanner based on NEMA NU 2-2018 with additional tests to characterize PET scanners with a long Axial Field of View. J Nucl Med off Publ Soc Nucl Med. 2021;62(6):861\u201370. https:\/\/doi.org\/10.2967\/jnumed.120.250597.","journal-title":"J Nucl Med off Publ Soc Nucl Med"},{"issue":"10","key":"1104_CR14","doi-asserted-by":"publisher","first-page":"1986","DOI":"10.1038\/jcbfm.2011.107","volume":"31","author":"P Zanotti-Fregonara","year":"2011","unstructured":"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(10):1986\u201398. https:\/\/doi.org\/10.1038\/jcbfm.2011.107.","journal-title":"J Cereb Blood Flow Metab"},{"issue":"13","key":"1104_CR15","doi-asserted-by":"publisher","first-page":"2368","DOI":"10.1007\/s00259-018-4081-5","volume":"45","author":"SH Cho","year":"2018","unstructured":"Cho SH, Shin JH, Jang H, et al. Amyloid involvement in subcortical regions predicts cognitive decline. Eur J Nucl Med Mol Imaging. 2018;45(13):2368\u201376. https:\/\/doi.org\/10.1007\/s00259-018-4081-5.","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"3","key":"1104_CR16","doi-asserted-by":"publisher","first-page":"299","DOI":"10.2967\/jnumed.119.226498","volume":"60","author":"RD Badawi","year":"2019","unstructured":"Badawi RD, Shi H, Hu P, et al. First Human Imaging Studies with the EXPLORER Total-Body PET Scanner*. J Nucl Med. 2019;60(3):299\u2013303. https:\/\/doi.org\/10.2967\/jnumed.119.226498.","journal-title":"J Nucl Med"},{"issue":"8","key":"1104_CR17","doi-asserted-by":"publisher","first-page":"1274","DOI":"10.2967\/jnumed.121.262668","volume":"63","author":"G Wang","year":"2022","unstructured":"Wang G, Nardo L, Parikh M, et al. Total-body PET multiparametric imaging of Cancer using a Voxelwise Strategy of Compartmental modeling. J Nucl Med off Publ Soc Nucl Med. 2022;63(8):1274\u201381. https:\/\/doi.org\/10.2967\/jnumed.121.262668.","journal-title":"J Nucl Med off Publ Soc Nucl Med"},{"issue":"1","key":"1104_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cpet.2020.09.006","volume":"16","author":"L Nardo","year":"2021","unstructured":"Nardo L, Abdelhafez YG, Spencer BA, Badawi RD. Clinical implementation of total-body PET\/CT at University of California, Davis. PET Clin. 2021;16(1):1\u20137. https:\/\/doi.org\/10.1016\/j.cpet.2020.09.006.","journal-title":"PET Clin"},{"key":"1104_CR19","unstructured":"Committe for Medicinal Products for Human Use (CHMP). Florbetaben (18F). Published Online Dec 19, 2013."},{"issue":"5","key":"1104_CR20","doi-asserted-by":"publisher","first-page":"723","DOI":"10.2967\/jnumed.112.107185","volume":"54","author":"GA Becker","year":"2013","unstructured":"Becker GA, Ichise M, Barthel H, et al. PET quantification of 18F-florbetaben binding to \u03b2-amyloid deposits in human brains. J Nucl Med off Publ Soc Nucl Med. 2013;54(5):723\u201331. https:\/\/doi.org\/10.2967\/jnumed.112.107185.","journal-title":"J Nucl Med off Publ Soc Nucl Med"},{"issue":"3","key":"1104_CR21","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1007\/s10967-010-0514-8","volume":"284","author":"M Patt","year":"2010","unstructured":"Patt M, Schildan A, Barthel H, et al. Metabolite analysis of [18F]Florbetaben (BAY 94-9172) in human subjects: a substudy within a proof of mechanism clinical trial. J Radioanal Nucl Chem. 2010;284(3):557\u201362. https:\/\/doi.org\/10.1007\/s10967-010-0514-8.","journal-title":"J Radioanal Nucl Chem"},{"issue":"3","key":"1104_CR22","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1002\/hbm.10062","volume":"17","author":"SM Smith","year":"2002","unstructured":"Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17(3):143\u201355. https:\/\/doi.org\/10.1002\/hbm.10062.","journal-title":"Hum Brain Mapp"},{"issue":"2","key":"1104_CR23","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/s1361-8415(01)00036-6","volume":"5","author":"M Jenkinson","year":"2001","unstructured":"Jenkinson M, Smith S. A global optimisation method for robust affine registration of brain images. Med Image Anal. 2001;5(2):143\u201356. https:\/\/doi.org\/10.1016\/s1361-8415(01)00036-6.","journal-title":"Med Image Anal"},{"issue":"2","key":"1104_CR24","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1006\/nimg.2002.1132","volume":"17","author":"M Jenkinson","year":"2002","unstructured":"Jenkinson M, Bannister P, Brady M, Smith S. Improved optimization for the Robust and Accurate Linear Registration and Motion correction of brain images. NeuroImage. 2002;17(2):825\u201341. https:\/\/doi.org\/10.1006\/nimg.2002.1132.","journal-title":"NeuroImage"},{"key":"1104_CR25","doi-asserted-by":"publisher","unstructured":"Klein A, Tourville J. 101 Labeled Brain Images and a Consistent Human Cortical Labeling Protocol. Front Neurosci. 2012;6. Accessed June 21, 2023. https:\/\/www.frontiersin.org\/articles\/https:\/\/doi.org\/10.3389\/fnins.2012.00171.","DOI":"10.3389\/fnins.2012.00171"},{"issue":"5","key":"1104_CR26","doi-asserted-by":"publisher","first-page":"738","DOI":"10.2967\/jnumed.119.238113","volume":"62","author":"T Feng","year":"2021","unstructured":"Feng T, Zhao Y, Shi H, et al. Total-body quantitative Parametric Imaging of Early Kinetics of 18F-FDG. J Nucl Med off Publ Soc Nucl Med. 2021;62(5):738\u201344. https:\/\/doi.org\/10.2967\/jnumed.119.238113.","journal-title":"J Nucl Med off Publ Soc Nucl Med"},{"issue":"1","key":"1104_CR27","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","volume":"57","author":"Y Benjamini","year":"1995","unstructured":"Benjamini Y, Hochberg Y. Controlling the false Discovery rate: a practical and powerful Approach to multiple testing. J R Stat Soc Ser B Methodol. 1995;57(1):289\u2013300. https:\/\/doi.org\/10.1111\/j.2517-6161.1995.tb02031.x.","journal-title":"J R Stat Soc Ser B Methodol"},{"key":"1104_CR28","unstructured":"R Core Team. (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https:\/\/www.R-project.org\/."},{"issue":"1","key":"1104_CR29","doi-asserted-by":"publisher","first-page":"1214","DOI":"10.1038\/s41467-017-01150-x","volume":"8","author":"S Palmqvist","year":"2017","unstructured":"Palmqvist S, Sch\u00f6ll M, Strandberg O, et al. Earliest accumulation of \u03b2-amyloid occurs within the default-mode network and concurrently affects brain connectivity. Nat Commun. 2017;8(1):1214. https:\/\/doi.org\/10.1038\/s41467-017-01150-x.","journal-title":"Nat Commun"},{"issue":"2","key":"1104_CR30","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1007\/s00259-022-05958-8","volume":"50","author":"JL Ebenau","year":"2023","unstructured":"Ebenau JL, Visser D, Verfaillie SCJ, et al. Cerebral blood flow, amyloid burden, and cognition in cognitively normal individuals. Eur J Nucl Med Mol Imaging. 2023;50(2):410\u201322. https:\/\/doi.org\/10.1007\/s00259-022-05958-8.","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"4","key":"1104_CR31","doi-asserted-by":"publisher","first-page":"e0122920","DOI":"10.1371\/journal.pone.0122920","volume":"10","author":"Y Su","year":"2015","unstructured":"Su Y, Blazey TM, Snyder AZ, et al. Quantitative amyloid imaging using image-derived arterial input function. PLoS ONE. 2015;10(4):e0122920. https:\/\/doi.org\/10.1371\/journal.pone.0122920.","journal-title":"PLoS ONE"},{"issue":"supplement 1","key":"1104_CR32","first-page":"520","volume":"60","author":"E Li","year":"2019","unstructured":"Li E, Cherry S, Tarantal A, et al. Identificationand comparisonof image-derived input functions using total-body PET. J Nucl Med. 2019;60(supplement 1):520\u2013520.","journal-title":"J Nucl Med"},{"issue":"5","key":"1104_CR33","doi-asserted-by":"publisher","first-page":"2265","DOI":"10.1073\/pnas.1917379117","volume":"117","author":"X Zhang","year":"2020","unstructured":"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. 2020;117(5):2265\u20137. https:\/\/doi.org\/10.1073\/pnas.1917379117.","journal-title":"Proc Natl Acad Sci"},{"issue":"4","key":"1104_CR34","doi-asserted-by":"publisher","first-page":"e0232141","DOI":"10.1371\/journal.pone.0232141","volume":"15","author":"A Girard","year":"2020","unstructured":"Girard A, Saint-Jalmes H, Chaboub N, et al. Optimization of time frame binning for FDOPA uptake quantification in glioma. PLoS ONE. 2020;15(4):e0232141. https:\/\/doi.org\/10.1371\/journal.pone.0232141.","journal-title":"PLoS ONE"},{"issue":"1","key":"1104_CR35","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1186\/s13550-023-01050-w","volume":"13","author":"T Volpi","year":"2023","unstructured":"Volpi T, Maccioni L, Colpo M, et al. An update on the use of image-derived input functions for human PET studies: new hopes or old illusions? EJNMMI Res. 2023;13(1):97. https:\/\/doi.org\/10.1186\/s13550-023-01050-w.","journal-title":"EJNMMI Res"},{"issue":"11","key":"1104_CR36","doi-asserted-by":"publisher","first-page":"1740","DOI":"10.2967\/jnumed.115.171652","volume":"57","author":"AM Catafau","year":"2016","unstructured":"Catafau AM, Bullich S, Seibyl JP, et al. Cerebellar Amyloid-\u03b2 plaques: how frequent are they, and do they influence 18F-Florbetaben SUV ratios? J Nucl Med off Publ Soc Nucl Med. 2016;57(11):1740\u20135. https:\/\/doi.org\/10.2967\/jnumed.115.171652.","journal-title":"J Nucl Med off Publ Soc Nucl Med"},{"key":"1104_CR37","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1186\/s13550-020-00714-1","volume":"10","author":"F Heeman","year":"2020","unstructured":"Heeman F, Hendriks J, Lopes Alves I, et al. [11\u00a0C]PIB amyloid quantification: effect of reference region selection. EJNMMI Res. 2020;10:123. https:\/\/doi.org\/10.1186\/s13550-020-00714-1.","journal-title":"EJNMMI Res"},{"issue":"supplement 2","key":"1104_CR38","first-page":"2329","volume":"63","author":"Y Wang","year":"2022","unstructured":"Wang Y, Nardo L, Spencer B, et al. Multi-organ metabolic changes in COVID-19 recovery measured with total-body dynamic 18F-FDG PET. J Nucl Med. 2022;63(supplement 2):2329\u20132329.","journal-title":"J Nucl Med"},{"issue":"10","key":"1104_CR39","doi-asserted-by":"publisher","first-page":"3508","DOI":"10.1007\/s00259-022-05784-y","volume":"49","author":"HG Pemberton","year":"2022","unstructured":"Pemberton HG, Collij LE, Heeman F, et al. Quantification of amyloid PET for future clinical use: a state-of-the-art review. Eur J Nucl Med Mol Imaging. 2022;49(10):3508\u201328. https:\/\/doi.org\/10.1007\/s00259-022-05784-y.","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"8","key":"1104_CR40","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.2967\/jnumed.109.063305","volume":"50","author":"N Nelissen","year":"2009","unstructured":"Nelissen N, Laere KV, Thurfjell L, et al. Phase 1 study of the Pittsburgh compound B derivative 18F-Flutemetamol in healthy volunteers and patients with probable Alzheimer Disease. J Nucl Med. 2009;50(8):1251\u20139. https:\/\/doi.org\/10.2967\/jnumed.109.063305.","journal-title":"J Nucl Med"},{"key":"1104_CR41","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1186\/s13550-018-0412-6","volume":"8","author":"H Sari","year":"2018","unstructured":"Sari H, Erlandsson K, Marner L, et al. Non-invasive kinetic modelling of PET tracers with radiometabolites using a constrained simultaneous estimation method: evaluation with 11\u00a0C-SB201745. EJNMMI Res. 2018;8:58. https:\/\/doi.org\/10.1186\/s13550-018-0412-6.","journal-title":"EJNMMI Res"},{"issue":"9","key":"1104_CR42","doi-asserted-by":"publisher","first-page":"5145","DOI":"10.1118\/1.4961012","volume":"43","author":"D Hardiansyah","year":"2016","unstructured":"Hardiansyah D, Guo W, Kletting P, Mottaghy FM, Glatting G. Time-integrated activity coefficient estimation for radionuclide therapy using PET and a pharmacokinetic model: a simulation study on the effect of sampling schedule and noise. Med Phys. 2016;43(9):5145\u201354. https:\/\/doi.org\/10.1118\/1.4961012.","journal-title":"Med Phys"},{"issue":"7","key":"1104_CR43","doi-asserted-by":"publisher","first-page":"796","DOI":"10.3390\/ph15070796","volume":"15","author":"IH Bartelink","year":"2022","unstructured":"Bartelink IH, van de Stadt EA, Leeuwerik AF, et al. Physiologically based pharmacokinetic (PBPK) modeling to Predict PET Image Quality of three generations EGFR TKI in Advanced-Stage NSCLC patients. Pharmaceuticals. 2022;15(7):796. https:\/\/doi.org\/10.3390\/ph15070796.","journal-title":"Pharmaceuticals"}],"container-title":["EJNMMI Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13550-024-01104-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13550-024-01104-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13550-024-01104-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T11:21:12Z","timestamp":1713266472000},"score":1,"resource":{"primary":{"URL":"https:\/\/ejnmmires.springeropen.com\/articles\/10.1186\/s13550-024-01104-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,16]]},"references-count":43,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["1104"],"URL":"https:\/\/doi.org\/10.1186\/s13550-024-01104-7","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-3764930\/v1","asserted-by":"object"}]},"ISSN":["2191-219X"],"issn-type":[{"value":"2191-219X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,16]]},"assertion":[{"value":"20 December 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 March 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 April 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The UC Davis Institutional Review Board approved this protocol and written informed consent was obtained for all subjects involved in the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and\/or national research committee and with the 1964 Helsinki declaration.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Consent to publish has been received from all participants.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"No potential conflicts of interest relevant to this article exist.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"39"}}