학술논문

Comparison of PET/CT SUV metrics across different clinical software platforms.
Document Type
Article
Source
Clinical Imaging. Sep2022, Vol. 89, p104-108. 5p.
Subject
*SPORT utility vehicles
*COMPUTED tomography
*SYSTEMS software
*NUCLEAR medicine
*SOFTWARE measurement
*COMPUTER software
Language
ISSN
0899-7071
Abstract
To assess the agreement of SUV metrics across the different clinical PET reading software platforms available at our institution. PET/CT images were reviewed on four different FDA-approved software platforms: syngoMMWP VE36A and syngo.via VB30A (Siemens), Intellispace Portal 9.0 (Philips), and Encore 6.7 (MIM Software). A total of thirty SUV measurements were derived from ten 18F-FDG PET/CT oncology studies. A volume of interest (VOI) was drawn around the primary tumor to determine lesion SUV max and a 3 cm diameter spherical VOI was placed in the right lobe of the liver to determine liver SUV mean and liver SUV max. For lesion SUV max , statistically significant differences were found for syngoMMWP VE36A vs syngo.via VB30A (p = 0.002), syngoMMWP VE36A vs Intellispace Portal 9.0 (p = 0.002), and syngoMMWP VE36A vs Encore 6.7 (p = 0.001), respectively. For liver SUV max , a statistically significant difference was found for syngoMMWP VE36A vs syngo.via VB30A (p = 0.033) only, whereas for liver SUV mean , no statistically significant differences were determined. A small systematic bias was found between syngoMMWP VE36A and all other platforms for lesion SUV max. Significant differences and systematic biases were observed when measuring lesion SUV max using different reader software systems. Although these differences may not be clinically significant, this bias could confound outcomes for quantitative, precision-research protocols. Hence, it is important for nuclear medicine departments to take SUV metric agreement into consideration, especially when transitioning to a new clinical platform. • Standardized Uptake Value measurements are dependent on interpretation software. • Significant differences and systematic biases were found across software platforms. • Biases may not be clinically significant, but may confound research protocols. • Departments should take standardized uptake value agreement into consideration. [ABSTRACT FROM AUTHOR]