Comparison between the ROI based and pixel based analysis for neuroreceptor studies performed on the high resolution research tomograph (HRRT)

Abstract

Parametric imaging refers to evaluating kinetic model parameters from time activity curves (TACs) estimated from every image pixel in contrast to region of interest (ROI) based analysis where the parameters are evaluated from TACs derived from predefined ROIs. Parametric imaging is thus more sensitive to statistical and motion induced noise. Here we evaluate the feasibility of parametric imaging for two modeling approaches, the simplified reference tissue model (RTM) and the tissue input Logan graphical method (L), for data acquired on the high resolution research tomograph (HRRT). The small image pixel size of this tomograph makes the image pixel values particularly sensitive to statistical noise and to artifacts due to subject motion. Comparing parametric BP estimates to those obtained with the ROI based approach a large downward bias (up to 28%) was observed for the Logan approach, while no bias was observed for the RTM method. The correlation between the BP values obtained with the ROI and parametric approach was better and less affected by motion for RTM (r2 > 0.9) compared to L (r2 > 0.45). The correlation between the BP obtained with the two methods was found to be significantly affected by patient motion and in general better for the ROI based approach. We conclude that parametric imaging on the HRRT is feasible for selected modeling approaches.