An algorithm for automated ROI definition in water or epoxy-filled NEMA NU-2 image quality phantoms.

Abstract

Drawing regions of interest (ROIs) in positron emission tomography/computed tomography (PET/CT) scans of the National Electrical Manufacturers Association (NEMA) NU‐2 Image Quality (IQ) phantom is a time‐consuming process that allows for interuser variability in the measurements. In order to reduce operator effort and allow batch processing of IQ phantom images, we propose a fast, robust, automated algorithm for performing IQ phantom sphere localization and analysis. The algorithm is easily altered to accommodate different configurations of the IQ phantom. The proposed algorithm uses information from both the PET and CT image volumes in order to overcome the challenges of detecting the smallest spheres in the PET volume. This algorithm has been released as an open‐source plug‐in to the Osirix medical image viewing software package. We test the algorithm under various noise conditions, positions within the scanner, air bubbles in the phantom spheres, and scanner misalignment conditions. The proposed algorithm shows runtimes between 3 and 4 min and has proven to be robust under all tested conditions, with expected sphere localization deviations of less than 0.2 mm and variations of PET ROI mean and maximum values on the order of 0.5% and 2%, respectively, over multiple PET acquisitions. We conclude that the proposed algorithm is stable when challenged with a variety of physical and imaging anomalies, and that the algorithm can be a valuable tool for those who use the NEMA NU‐2 IQ phantom for PET/CT scanner acceptance testing and QA/QC.PACS number: 87.57.C‐