Analysis of PET Image Quality Using 2D vs 3D ROIs in Small Spheres

Abstract

Modern positron emission tomography (PET) systems have substantially improved insensitivity, timing performance, and reconstruction methods; however, the conventional NEMA image-quality phantom remains limited in evaluating sub-centimeter lesion de- tectability. This work investigated the image quality of small-sphere PET using an exper- imental image-quality phantom designed to extend conventional NEMA-style assessment into the sub-centimeter regime, along with an automated analysis workflow for reproducible metric extraction. A second whole-body phantom containing multiple small spheres was also evaluated in a more anthropomorphic geometry. An automated MATLAB-based pipeline was developed to process PET DICOM data, localize sphere centers, define regions of interest, and compute contrast recovery coefficient (CRC), coefficient of variation (CoV), and contrast-to-noise ratio (CNR). The experimen- tal phantom was evaluated across multiple PET/CT systems and reconstruction settings. Results showed that averaged-frame localization closely matched static acquisition, with a mean whole-phantom percent error of less than 1%. CRC and CNR increased with sphere diameter, and the greatest reconstruction-dependent differences were observed for the small- est spheres. In the whole-body phantom, the expected tradeoff between contrast recovery and background variability was observed. Overall, this work demonstrates the value of smaller-sphere phantom designs for more sensitive evaluation of modern PET image quality.