1. ^*Molecular Imaging Branch, National Institutes of Mental Health, Bethesda, Maryland, U.S.A.
2. ^†PET Department, Warren G. Magnuson Clinical Center, National Institutes of Health, Bethesda, Maryland, U.S.A.

Correspondence: Masanori Ichise, Building 1 B3–10, One Center Drive MSC0135, Molecular Imaging Branch, National Institutes of Mental Health, Bethesda, MD 20892, U.S.A.; e-mail: masanori.ichise@nih.gov

Received 19 April 2002; Revised 12 June 2002; Accepted 12 June 2002.

Abstract

In an attempt to improve neuroreceptor distribution volume (V) estimates, the authors evaluated three alternative linear methods to Logan graphical analysis (GA): GA using total least squares (TLS), and two multilinear analyses, MA1 and MA2, based on mathematical rearrangement of GA equation and two-tissue compartments, respectively, using simulated and actual PET data of two receptor tracers, [¹⁸F]FCWAY and [¹¹C]MDL 100,907. For simulations, all three methods decreased the noise-induced GA bias (up to 30%) at the expense of increased variability. The bias reduction was most pronounced for MA1, moderate to large for MA2, and modest to moderate for TLS. In addition, GA, TLS, and MA1, methods that used only a portion of the data (T >t *, chosen by an automatic process), showed a small V underestimation for [¹¹C]MDL 100,907 with its slow kinetics, due to selection of t * before the true point of linearity. These noniterative methods are computationally simple, allowing efficient pixelwise parameter estimation. For tracers with kinetics that permit t * to be accurately identified within the study duration, MA1 appears to be the best. For tracers with slow kinetics and low to moderate noise, however, MA2 may provide the lowest bias while maintaining computational ease for pixelwise parameter estimation.