Performance Comparison of Parameter Estimation Techniques for the Quantitation of Local Cerebral Blood Flow by Dynamic Positron Computed Tomography

Abstract

Local CBF (LCBF) can be quantitated from positron computed tomographic (PCT) data and physiologically based mathematical models by several general methods. Those using a dynamic sequence of PCT scans allow the simultaneous estimation of both LCBF and p, the indicator's tissue–blood partition coefficient. This article presents a comparison of three rapid estimation techniques for use with inert diffusible radioindicators and serial PCT, each of which is based on the original Kety model. One method, developed in our laboratory, involves minimizing the mean squared discrepancy between measured data and model predictions, whereas the other two methods, recently reported in the literature, are weighted integration techniques that involve multiplying the measured data by time-dependent weighting functions. Simulation studies of noise propagation and other sources of error were performed under a variety of simulated conditions. Functional images of LCBF and p were calculated using each method for both phantom and human subject data. Errors can differ by as much as a factor of 2–3 between methods, with each having its own unique advantages and disadvantages.