Endocannabinoid tone has recently been implicated in a number of prevalent neuropsychiatric conditions. [11 C]CURB is the first available positron emission tomography (PET) radiotracer for imaging fatty acid amide hydrolase (FAAH), the enzyme which metabolizes the prominent endocannabinoid anandamide. Here, we sought to determine the most suitable kinetic modeling approach for quantifying [11 C]CURB that binds selectively to FAAH. Six healthy volunteers were scanned with arterial blood sampling for 90 minutes. Kinetic parameters were estimated regionally using a one-tissue compartment model (TCM), a 2-TCM with and without irreversible trapping, and an irreversible 3-TCM. The 2-TCM with irreversible trapping provided the best identifiability of PET outcome measures among the approaches studied (coefficient of variation (COV) of the net influx constant K i and the composite parameter lk 3 (l ¼ K 1 /k 2 ) o5%, and COV(k 3 )o10%). Reducing scan time to 60 minutes did not compromise the identifiability of rate constants. Arterial spin labeling measures of regional cerebral blood flow were only slightly correlated with K i , but not with k 3 or lk 3 . Our data suggest that lk 3 is sensitive to changes in FAAH activity, therefore, optimal for PET quantification of FAAH activities with [11 C]CURB. Simulations showed that [ 11 C]CURB binding in healthy subjects is far from a flow-limited uptake. C]CURB corresponds with the known distribution of FAAH in rat brain, specifically greater uptake is noted in cerebral cortex, cerebellum, and hippocampus with lowest uptake in the FAAH poor hypothalamus region; (2) administration of the unlabeled FAAH inhibitors URB694 and URB597 decreases brain uptake of [
This paper describes phase maps. A review of the phase unwrapping problem is given. Different structures, in particular fringelines, cutlines, and poles, contained within a phase map are described and their origin and behavior investigated. The problem of phase unwrapping can then be addressed with a better understanding of the source of poles or inconsistencies. This understanding, along with some assumptions about what is being encoded in the phase of a magnetic resonance image, are used to derive a new method for phase unwrapping which relies only on the phase map. The method detects cutlines and distinguishes between noise-induced poles and signal undersampling poles based on the length of the fringelines. The method was shown to be robust to noise and successful in unwrapping challenging clinical cases.
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