Comparative Assessment of Parametric Neuroreceptor Mapping Approaches Based on the Simplified Reference Tissue Model Using [¹¹C]ABP688 PET

Abstract

In recent years, several linearized model approaches for fast and reliable parametric neuroreceptor mapping based on dynamic nuclear imaging have been developed from the simplified reference tissue model (SRTM) equation. All the methods share the basic SRTM assumptions, but use different schemes to alleviate the effect of noise in dynamic-image voxels. Thus, this study aimed to compare those approaches in terms of their performance in parametric image generation. We used the basis function method and MRTM2 (multilinear reference tissue model with two parameters), which require a division process to obtain the distribution volume ratio (DVR). In addition, a linear model with the DVR as a model parameter (multilinear SRTM) was used in two forms: one based on linear least squares and the other based on extension of total least squares (TLS). Assessment using simulated and actual dynamic [ 11 C]ABP688 positron emission tomography data revealed their equivalence with the SRTM, except for different noise susceptibilities. In the DVR image production, the two multilinear SRTM approaches achieved better image quality and regional compatibility with the SRTM than the others, with slightly better performance in the TLS-based method. Keywords: neuroreceptor imaging; parametric image; simplified reference tissue model; total least squares; tracer kinetic modeling INTRODUCTIONThe simplified reference tissue model (SRTM) 1 has been used extensively in quantitative studies of a reversibly binding radiotracer using dynamic positron emission tomography (PET) and single photon emission computed tomography, owing to its noninvasiveness and robustness in the estimation of kinetic parameters. [2][3][4][5] The model parameters have been estimated mainly using nonlinear least squares (NLS), which can provide unbiased solutions for parameter estimation from time-activity curves (TACs) with low-or moderate-level noise. In the use of NLS, however, highly noisy data may bring several limitations such as dependency on initial values, long computation time, and a high level of uncertainty. 2,4,6-8 Therefore, the NLS-based standard SRTM (NLS-SRTM) is undesirable for parametric image generation (voxelby-voxel analysis) characterized by large amounts of voxel data with high-level noise. Consequently, the application of NLS-SRTM is limited to the analysis of regional average TACs that are much less noisy than voxel TACs. 2,4

A regularized full reference tissue model for PET neuroreceptor mapping

“…The model provides a separate estimate of the washout rate constant ( k 2 ′) in the reference region for each voxel or ROI, which motivated a reduced model that provides regularization by fixing the value of k 2 ′ as a global parameter. However, many investigators have noted that different regions provide different values for this rate constant, and the method for defining a global value is not standardized; various reports have suggested using the value in a high binding region (Seneca et al, 2006), or the median or average across either the brain (Wu and Carson, 2002) or a series of ROIs (Ichise et al, 2003, Seo et al, 2015). In contrast to the three-parameter SRTM, the two-parameter variant generally underestimates BP ND in low-binding regions (Schuitemaker et al, 2007), and bias in high-binding regions is smaller and depends upon a subjective choice for k 2 ′.…”

In vivogamma‐aminobutyric acid‐A/benzodiazepine receptor availability and genetic liability in asymptomatic individuals with high genetic loading of schizophrenia: A [11C]flumazenil positron emission tomography study

“…The reference-tissue input was obtained from the pons. Then, BP ND maps of [11C]flumazenil were generated from the native-space dynamic images using a TLS-based linearization of SRTM (Seo et al, 2015), which is robust to high-level noise in voxel TACs.…”

Milkshake Acutely Stimulates Dopamine Release in Ventral and Dorsal Striatum in Healthy-Weight Individuals and Patients with Severe Obesity Undergoing Bariatric Surgery: A Pilot Study

“…We note that this represents an a priori power calculation that was conducted for the purposes of obtaining pilot data to support further work rather than for conducting a fully-powered analysis. Pre-meal BP ND and post-meal BP ND were estimated using the multilinear reference tissue method with 2 parameters (MRTM2) [ 34 , 35 ] for functional striatum subdivisions (5 per side) using the cerebellum as the reference region.…”