Related Experiment Video
Updated: Nov 8, 2025

Radiotracer Administration for High Temporal Resolution Positron Emission Tomography of the Human Brain: Application to FDG-fPET
Published on: October 22, 2019
Comparison of an in-house acquired brain F-18 FDG PET normal database with commercially available normal data
Robbe Waterschoot1, Yves D'Asseler, Ingeborg Goethals
1Department of Nuclear Medicine, Ghent University Hospital, Gent, Belgium.
Introduction:
Current guidelines recommend the use of semiautomated assessment of F-18 FDG PET brain studies. Accuracy is influenced by the normal data, which requires knowledge of the included subjects and how they were acquired. Due to confidentiality, such information is often not completely disclosed. Our aim was to determine the variation in FDG uptake between several commercially available and our in-house normal database.
Methods:
Our database contains 83 healthy subjects. Outlier detection using SPM further ensured normality, resulting in exclusion of three subjects. The remaining 80 subjects were analyzed using three commercially available software packages. Z-score data per patient and per lobe were extracted and pooled in predefined age groups (18-40, 41-60 and 61-80 years old) with a calculation of mean Z-scores and SD. Correlation between Z-score output of different software was investigated.
Results:
In the 18-40 years age group, frontotemporal hypermetabolism was found with all software. Decreased cerebellar uptake was found with two software packages. Mean Z-scores are closer to zero in the 41-60 years age group compared to the younger group, and mostly within the normal range in the 61-80 years age group with all software. A moderate to high linear correlation between Z-score output was found, but individual Z-scores varied widely.
Conclusions:
The three software packages yielded varying Z-score output, partially explained by an age mismatch between our subjects and subjects in their normal databases. A definitive explanation for the remaining differences is lacking. This emphasizes the importance of age-matched normal data and knowledge of the included databases to allow adequate preprocessing.
![Semi-quantitative Assessment Using [18F]FDG Tracer in Patients with Severe Brain Injury](/_next/image?url=https%3A%2F%2Fcloudfront.jove.com%2FCDNSource%2Fteasers%2F58641.jpg&w=3840&q=50)
