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Estimation of an image derived input function with MR-defined carotid arteries in FDG-PET human studies using a novel partial volume correction method

Research output: Contribution to journalArticle

Hasan Sari, Kjell Erlandsson, Ian Law, Henrik B.W. Larsson, Sebastien Ourselin, Simon Arridge, David Atkinson, Brian F. Hutton

Original languageEnglish
Pages (from-to)1398-1409
Number of pages12
JournalJournal of Cerebral Blood Flow and Metabolism
Issue number4
Early online date21 Jul 2017
Publication statusPublished - 2017



King's Authors


Kinetic analysis of 18F-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 mg/min/100 g, respectively, for the grey matter and 7.2 and 6.7 mg/min/100 g 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>0.12 for grey matter and white matter). Hence, the presented image derived input function extraction method can be a practical alternative to noninvasively analyze dynamic 18F-fluorodeoxyglucose data without the need for blood sampling.

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