2016
DOI: 10.1177/0271678x16656197
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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

Abstract: Kinetic analysis of 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 der… Show more

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Cited by 55 publications
(68 citation statements)
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“…However in PET studies of the brain, calculation of the IDIF is challenged by two factors: PVE [231,232] due to the small size of the blood pools, and subject motion [232,233]. Various approaches have been proposed to extract an accurate IDIF that can be classified into PET-only based methods [232,[234][235][236][237][238][239][240][241][242][243][244], stand-alone PET and MR-based methods [228,245,246], and fully-integrated PET/MR-based methods [247][248][249]. Combined PET/MR can potentially allow researchers to address the aforementioned challenges (PVE and subject motion) in an automatic way [228,248,249], in addition to bearing a logistic advantage.…”
Section: Kinetic Modeling and Image Derived Input Function (Idif)mentioning
confidence: 99%
See 1 more Smart Citation
“…However in PET studies of the brain, calculation of the IDIF is challenged by two factors: PVE [231,232] due to the small size of the blood pools, and subject motion [232,233]. Various approaches have been proposed to extract an accurate IDIF that can be classified into PET-only based methods [232,[234][235][236][237][238][239][240][241][242][243][244], stand-alone PET and MR-based methods [228,245,246], and fully-integrated PET/MR-based methods [247][248][249]. Combined PET/MR can potentially allow researchers to address the aforementioned challenges (PVE and subject motion) in an automatic way [228,248,249], in addition to bearing a logistic advantage.…”
Section: Kinetic Modeling and Image Derived Input Function (Idif)mentioning
confidence: 99%
“…However, the TA varies significantly with the quality of the underlying image data, thus, limiting the reproducibility Here, C P represents the blood activity and C 1 , C 2 the activity concentration of each tissue over time t. K1, k2, etc., are the rate constants that define the rate of tracer movement between compartments. This figure was adapted from Sari et al [228], with permission of SAGE Publications, Ltd.…”
Section: Multi-parametric Imaging (Mpi)mentioning
confidence: 99%
“…To obviate the need for the arterial input function (AIF) in brain studies, several methodologies have been proposed to extract an image-derived input function (IDIF) directly from PET images (4)(5)(6)(7)(8)(9)(10)(11)(12). These studies demonstrated that the extraction of an IDIF from a dynamic PET dataset requires 3 main tasks: the accurate definition of a blood-pool region, the accurate correction for subject motion, and the exact correction of extracted time-activity curves for partial-volume effects because of the small diameter of the internal carotid arteries.…”
mentioning
confidence: 99%
“…In past implementations, an IDIF was extracted either from PET/CT data in conjunction with a separate MRI scan (4,6,10,12) or from a fully integrated PET/MRI protocol (7,8,11,13). In particular, taking advantage of methodologic advances provided by fully integrated PET/MRI allows the 3 challenges mentioned earlier to be addressed in a straightforward manner.…”
mentioning
confidence: 99%
“…With combined PET/MRI systems, it is possible to develop kinetic models that utilise both dynamic PET and dynamic MRI data for parameter estimation [105]. These systems can also be useful for non-invasive estimation of the input function, which is normally required for kinetic modelling [106].…”
Section: Accounting For Temporal Changesmentioning
confidence: 99%