Noise reduction in the simplified reference tissue model for neuroreceptor functional imaging

Abstract

The Simplified Reference Tissue Model (SRTM) produces functional images of receptor binding parameters using an input function derived from a reference region and assuming a model with one tissue compartment. Three parameters are estimated: binding potential (BP), relative delivery (R1), and the reference region clearance constant k'2. Since k'2 should not vary across brain pixels, the authors developed a two-step method (SRTM2) using a global value of k'2. Whole-brain simulations were performed using human input functions and rate constants for [18F]FCWAY, [11C]flumazenil, and [11C]raclopride, and parameter SD and bias were determined for SRTM and SRTM2. The global mean of k'2 was slightly biased (2% to 6%), but the median was unbiased (<1%) and was used as the global value. Binding potential noise reductions with SRTM2 were 4% to 14%, 20% to 53%, and 10% to 30% for [18F]FCWAY, [11C]flumazenil, and [11C]raclopride, respectively, with larger reductions for shorter scans. R1 noise reduction was larger than that of BP. Simulations were also performed to assess bias when the reference and/or tissue regions followed a two-tissue compartment model. Owing to the constrained k'2, SRTM2 showed somewhat larger biases due to violations of the one-compartment model assumption. These studies demonstrate that SRTM2 should be a useful method to improve the quality of neuroreceptor functional images.