Abstract
BACKGROUND: Malignant brain tumors emphasize the importance of O-(2-(18)F-fluoroethyl)-L-tyrosine ((18)F-FET) positron emission tomography (PET) imaging for accurate diagnosis and treatment planning, necessitating standardized quantitative features for reliable assessment. However, the calculation of these features is influenced by acquisition duration, as reducing acquisition time remains a key concern in clinical practice. Furthermore, reconstruction algorithms significantly affect imaging quality. This study aimed to clarify the impact of acquisition duration and reconstruction algorithms on the repeatability of (18)F-FET PET quantitative features in brain tumors. METHODS: A total of 62 patients performing brain (18)F-FET PET/magnetic resonance (MR) examinations were retrospectively enrolled. The PET images were reconstructed using 24 designed schemes, comprising a combination of eight acquisition time windows (3, 5, 7, 10, 13, 15, 17, and 20 min) with three reconstruction algorithms [ordered subset expectation maximization (OSEM), OSEM with time-of-flight (OWT), and HYPER iterative with time-of-flight (HIWT)]. Image quality was evaluated using a 5-point Likert scale. The repeatability of quantitative metabolic and radiomic features between the three algorithms was assessed using intraclass correlation coefficients (ICC), whereas temporal stability between 15, 17, and 20 minutes for each algorithm was validated using the Friedman test. RESULTS: PET reconstruction images at 15, 17, and 20 minutes were considered to provide diagnostic value. The mean standardized uptake value (SUV) and tumor-to-brain ratio (TBR) showed minimal variation with acquisition duration for all three algorithms, with the relative percentage difference (RPD) <1.2% after
15 minutes. The maximum SUV (SUVmax), maximum TBR (TBRmax), metabolic tumor volume (MTV), and total lesion uptake (TLU) became usable when acquisition time exceeded 15 minutes, with an RPD of around 5% or less. There were 8 common metabolic features and 30 radiomics features which demonstrated excellent repeatability between the three algorithms at 15, 17, and 20 minutes. The HIWT algorithm identified 18 stable radiomics features, whereas the OWT identified 2, and the OSEM identified 3. CONCLUSIONS: This study offers a reference for clinically reducing the acquisition time of (18)F-FET PET imaging in brain tumors. It compares the temporal stability of different reconstruction algorithms and identifies metabolic and radiomic features with high repeatability and stability for each. These findings help to optimize imaging protocols and improve the reproducibility of quantitative analysis in (18)F-FET PET studies for brain tumors.