On the Uniqueness of Cerebral Blood Flow Measured by the in vivo Autoradiographic Strategy and Positron Emission Tomography

Abstract

Factors are examined in this report which govern the uniqueness and sensitivity of regional cerebral blood flow (rCBF), as determined by an in vivo autoradiographic strategy and positron emission tomography (PET), and a series of theorems is derived which specify conditions under which a unique relationship between cumulative cranial activity of the tracer (C) and regional blood flow (f) may be assured. It is demonstrated that, independent of the specific form of the arterial tracer input function, flow is a unique function of C whenever the start time (T1) of the PET scan is coincident with the start of tracer infusion. Other theorems state that, even for nonzero T1S, a unique solution for flow may be expected, as long as the duration of the scan is sufficiently short. The implementation of this theory is illustrated using arterial tracer activity curves obtained in three normal subjects by a multiple arterial sampling procedure following the bolus i.v. infusion of 20-30 microCi of [15O]water. Based on these arterial curves, it is confirmed that the C vs. f relationship resulting from scan parameters T1 = 0 and T2 = 1.5 min (i.e., a PET scan of 90 s commencing with tracer infusion) has an excellent separation of flow values within the range of physiological interest, whereas a 90-s scan beginning at time T1 = 1.7 min results in poorer separation of flow values and loss of the monotonic relationship between C and f at higher flows. The results of this study serve to clarify the in vivo autoradiographic method for measuring rCBF in humans and help to define favorable study parameters for assuring uniqueness and sensitivity of the flow measurement.

The Effects of Xenon Anesthesia on the Relationship Between Cerebral Glucose Metabolism and Blood Flow in Healthy Subjects: A Positron Emission Tomography Study

“…19,[23][24][25] Preprocessing of the PET Data The preprocessing of imaging data was performed using Statistical Parametric Mapping 26 software (Wellcome Department of Cognitive Neurology, University College London, England) version 99 (SPM99) and Matlab 6.5 for Windows (Math Works, Natick, MA) with a previously described procedure. 21 Each subject's image series was realigned, and the mean image of the realigned images was used in the estimation of the spatial normalization parameters for each subject.…”

Muscle blood flow and flow heterogeneity during exercise studied with positron emission tomography in humans

“…The left side of the equation is the pixel-by-pixel-solved integral of the decay-corrected tissue time±activity curve. A table lookup procedure from the left side to the right side gives a rate constant for ow, f, in the integration time scale T ( Howard et al 1983). Muscle blood¯ow was calculated pixel-by-pixel into¯ow images using a 250-s tissue integration time ).…”

Relationship between limb and muscle blood flow in man.

“…It has been shown that for a small volume element the gas exchange can be modelled mathematically with a single compartment model (lida et al 1986). The autoradiographic method has been widely used to numerically solve the flow (f in ml (100 g)-min') from the following equation (Howard, Ginsberg, Hassel, Lockwood & Freed, 1983):…”

“…The partition coefficient is calculated by dividing the fractional water content of muscle (79%, 75f96 ml (100 g)-1) by the fractional water content of blood (80 ml (100 ml)-') (Snyder, Cook, Nasset, Karhausen, Howells & Tipton, 1975) (Howard et al 1983). Blood flow was calculated pixel by pixel into parametric flow images using a 200 s integration time .…”