Impact of the healthy control database on brain pet imaging quantification

Abstract

Positron Emission Tomography (PET) is crucial in neurological research and clinical practice, providing information about brain metabolism, especially through the use of [18F]FDG PET, which aids in the diagnosis of conditions such as epilepsy. While quantitative PET analysis can improve diagnostic precision, its results may be influenced by the selection of the healthy control (HC) dataset. This study uses SimPET-generated synthetic data to explore how healthy control database acquired in six different scanners impact quantitative PET analysis, aiming to improve the robustness of clinical quantification methods. To assess the impact of scanner variability, both VOI-based and voxel-based analyses were performed, comparing a synthetic database of epilepsy patients with the different synthetic HC databases. The results show that scanner variability significantly affected the detection of both focal and extended epileptic lesions. These findings highlight the importance of the data harmonization to ensure reliable and accurate PET quantification. In conclusion, while the choice of a locally acquired healthy control database is important, its impact on PET quantification could be limited when comparing scanners of the same generation.