{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T20:45:31Z","timestamp":1793047531843,"version":"4.5.0"},"reference-count":25,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2016,7,21]],"date-time":"2016-07-21T00:00:00Z","timestamp":1469059200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Cereb Blood Flow Metab"],"published-print":{"date-parts":[[2017,4]]},"abstract":"<jats:p>\n                    Kinetic analysis of\n                    <jats:sup>18<\/jats:sup>\n                    F-fluorodeoxyglucose positron emission tomography data requires an accurate knowledge the arterial input function. The gold standard method to measure the arterial input function requires collection of arterial blood samples and is an invasive method. Measuring an image derived input function is a non-invasive alternative but is challenging due to partial volume effects caused by the limited spatial resolution of the positron emission tomography scanners. In this work, a practical image derived input function extraction method is presented, which only requires segmentation of the carotid arteries from MR images. The simulation study results showed that at least 92% of the true intensity could be recovered after the partial volume correction. Results from 19 subjects showed that the mean cerebral metabolic rate of glucose calculated using arterial samples and partial volume corrected image derived input function were 26.9 and 25.4\u2009mg\/min\/100\u2009g, respectively, for the grey matter and 7.2 and 6.7\u2009mg\/min\/100\u2009g for the white matter. No significant difference in the estimated cerebral metabolic rate of glucose values was observed between arterial samples and corrected image derived input function (p\u2009&gt;\u20090.12 for grey matter and white matter). Hence, the presented image derived input function extraction method can be a practical alternative to noninvasively analyze dynamic\n                    <jats:sup>18<\/jats:sup>\n                    F-fluorodeoxyglucose data without the need for blood sampling.\n                  <\/jats:p>","DOI":"10.1177\/0271678x16656197","type":"journal-article","created":{"date-parts":[[2016,6,24]],"date-time":"2016-06-24T20:49:09Z","timestamp":1466801349000},"page":"1398-1409","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":71,"title":["Estimation of an image derived input function with MR-defined carotid arteries in FDG-PET human studies using a novel partial volume correction method"],"prefix":"10.1177","volume":"37","author":[{"given":"Hasan","family":"Sari","sequence":"first","affiliation":[{"name":"Institute of Nuclear Medicine, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kjell","family":"Erlandsson","sequence":"additional","affiliation":[{"name":"Institute of Nuclear Medicine, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ian","family":"Law","sequence":"additional","affiliation":[{"name":"Department of Clinical Physiology, Nuclear Medicine and PET, University of Copenhagen, Copenhagen, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henrik BW","family":"Larsson","sequence":"additional","affiliation":[{"name":"Department of Clinical Physiology, Nuclear Medicine and PET, University of Copenhagen, Copenhagen, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastien","family":"Ourselin","sequence":"additional","affiliation":[{"name":"Centre for Medical Image Computing, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon","family":"Arridge","sequence":"additional","affiliation":[{"name":"Centre for Medical Image Computing, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Atkinson","sequence":"additional","affiliation":[{"name":"Center for Medical Imaging, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brian F","family":"Hutton","sequence":"additional","affiliation":[{"name":"Institute of Nuclear Medicine, University College London, London, UK"},{"name":"Centre for Medical Radiation Physics, University of Wollongong, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2016,7,21]]},"reference":[{"key":"bibr1-0271678X16656197","doi-asserted-by":"publisher","DOI":"10.1097\/01.wcb.0000045042.03034.42"},{"key":"bibr2-0271678X16656197","doi-asserted-by":"publisher","DOI":"10.1038\/jcbfm.1983.1"},{"key":"bibr3-0271678X16656197","doi-asserted-by":"publisher","DOI":"10.1016\/0165-0173(82)90018-2"},{"key":"bibr4-0271678X16656197","doi-asserted-by":"publisher","DOI":"10.1016\/0020-7101(93)90049-C"},{"key":"bibr5-0271678X16656197","doi-asserted-by":"publisher","DOI":"10.1007\/BF01728767"},{"key":"bibr6-0271678X16656197","first-page":"945","volume":"47","author":"De Geus-Oei LF","year":"2006","journal-title":"J Nucl Med"},{"key":"bibr7-0271678X16656197","first-page":"1622","volume":"42","author":"Van der Weerdt AP","year":"2001","journal-title":"J Nucl Med"},{"key":"bibr8-0271678X16656197","doi-asserted-by":"publisher","DOI":"10.1038\/jcbfm.2011.107"},{"key":"bibr9-0271678X16656197","doi-asserted-by":"crossref","unstructured":"Berradja K, Boughanmi N and Bentourkia M. 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