The use of alternative forms of graphical analysis to balance bias and precision in PET images

Graphical analysis (GA) is an efficient method for estimating total tissue distribution volume (V(T)) from positron emission tomography (PET) uptake data. The original GA produces a negative bias in V(T) in the presence of noise. Estimates of V(T) using other GA forms have less bias but less precision. Here, we show how the bias terms are related between the GA methods and how using an instrumental variable (IV) can also reduce bias. Results are based on simulations of a two-compartment model with V(T)'s ranging from 10.5 to 64 mL/cm(3) and from PET image data with the tracer [(11)C] DASB ([(11)C]-3-amino-4-(2-dimethylaminomethyl-phenylsulfanyl) benzonitrile). Four estimates of V(T) (or distribution volume ratio (DVR) using a reference tissue) can be easily computed from different formulations of GA including the IV. As noise affects the estimates from all four differently, they generally do not provide the same estimates. By taking the median value of the four estimates, we can decrease the bias and reduce the effect of large values contributing to noisy images. The variance of the four estimates can serve as a guide to the reliability of the median estimate. This may provide a general method for the generation of parametric images with little bias and good precision. Journal of Cerebral Blood Flow & Metabolism (2011) 31, 535-546; doi: 10.1038/jcbfm.2010.123; published online 1 September 2010