New standards for phantom image quality and SUV harmonization range for multicenter oncology PET studies.

Not only visual interpretation for lesion detection, staging, and characterization, but also quantitative treatment response assessment are key roles for F-FDG PET in oncology. In multicenter oncology PET studies, image quality standardization and SUV harmonization are essential to obtain reliable study outcomes. Standards for image quality and SUV harmonization range should be regularly updated according to progress in scanner performance. Accordingly, the first aim of this study was to propose new image quality reference levels to ensure small lesion detectability. The second aim was to propose a new SUV harmonization range and an image noise criterion to minimize the inter-scanner and intra-scanner SUV variabilities. We collected a total of 37 patterns of images from 23 recent PET/CT scanner models using the NEMA NU2 image quality phantom. PET images with various acquisition durations of 30-300 s and 1800 s were analyzed visually and quantitatively to derive visual detectability scores of the 10-mm-diameter hot sphere, noise-equivalent count (NEC), 10-mm sphere contrast (Q), background variability (N), contrast-to-noise ratio (Q/N), image noise level (CV), and SUVmax and SUVpeak for hot spheres (10-37 mm diameters). We calculated a reference level for each image quality metric, so that the 10-mm sphere can be visually detected. The SUV harmonization range and the image noise criterion were proposed with consideration of overshoot due to point-spread function (PSF) reconstruction. We proposed image quality reference levels as follows: Q/N ≥ 2.5 and CV ≤ 14.1%. The 10th-90th percentiles in the SUV distributions were defined as the new SUV harmonization range. CV ≤ 10% was proposed as the image noise criterion, because the intra-scanner SUV variability significantly depended on CV. We proposed new image quality reference levels to ensure small lesion detectability. A new SUV harmonization range (in which PSF reconstruction is applicable) and the image noise criterion were also proposed for minimizing the SUV variabilities. Our proposed new standards will facilitate image quality standardization and SUV harmonization of multicenter oncology PET studies. The reliability of multicenter oncology PET studies will be improved by satisfying the new standards.