Method to determine the statistical technical variability of SUV metrics

• Published in: EJNMMI physics Vol. 9; no. 1; pp. 40 - 16
• Main Authors: De Luca, Giulia M. R., Habraken, Jan B. A.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 06.06.2022; Springer Nature B.V; SpringerOpen
• Subjects: Applied and Technical Physics; Biological variation; Coefficient of variation; Computational Mathematics and Numerical Analysis; Emission analysis; Engineering; Evaluation; Glucose; Image reconstruction; Imaging; Mathematical analysis; Medical imaging; Medicine; Medicine & Public Health; Nuclear Medicine; Original Research; PET quantification; Physics; Positron emission; Radiology; Scanners; Standard uptake value; Tomography; Variation in standard uptake value; Standard uptake value; PET quantification; Variation in standard uptake value
• ISSN: 2197-7364; 2197-7364
• DOI: 10.1186/s40658-022-00470-2

Background The Standardized Uptake Value (SUV) Max, SUVMean, and SUVPeak are metrics used to quantify positron emission tomography (PET) images. In order to assess the significance of a change in these metrics for diagnostic purposes, it is relevant to know their variation. The sources of variation can be biological or technical. In this study, we present a method to determine the statistical technical variation of SUV in PET images. Results This method was tested on a NEMA quality phantom with spheres of various diameters with a full-length acquisition time of 150 s per bed position and foreground-to-background activity ratio of F 18 -2-fluoro-2-deoxy- d -glucose (FDG) of 10:1. Our method divides the 150 s acquisition into subsets with statistically independent frames of shorter reconstruction length. SUVMax, Mean and Peak were calculated for each reconstructed image in a subset. The coefficient of variation of SUV within each subset has been used to estimate the expected coefficient of variation at 150 s reconstruction length. We report the largest coefficient of variation of the SUV metrics for the smallest sphere and the smallest variation for the largest sphere. The expected variation at 150 s reconstruction length does not exceed 6% for the smallest sphere and 2% for the largest sphere. Conclusions With the presented method, we aim to determine the statistical technical variation of SUV. The method enables the evaluation of the effect of SUV metric choice (Max, Mean, Peak) and lesion size on the technical variation and, therefore, to evaluate its relevance on the total variation of the SUV value between clinical studies.