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Modeling the Effects of Age and Sex on Normal Pediatric Brain Metabolism Using18F-FDG PET/CT
Open accessAbstract
Reference databases of pediatric brain metabolism are uncommon, because local brain metabolism evolves significantly with age throughout childhood, limiting their clinical applicability. The aim of this study was to develop mathematic models of regional relative brain metabolism using pediatric 18F-FDG PET with CT data of normal pediatric brains, accounting for sex and age. Methods: PET/CT brain acquisitions were obtained from 88 neurologically normal subjects, aged 6 mo to 18 y. Subjects were assigned to either a development group (n = 59) or a validation group (n = 29). For each subject, commercially available software was used to quantify the relative metabolism of 47 separate brain regions using whole-brain–normalized (WBN) and pons-normalized (PN) activity. The effects of age on regional relative brain metabolism were modeled using multiple linear and nonlinear mathematic equations, and the significance of sex was assessed using the Student t test. Optimal models were selected using the Akaike information criterion. Mean predicted values and 95% prediction intervals were derived for all regions. Model predictions were compared with the validation dataset, and mean predicted error was calculated for all regions using both WBN and PN models. Results: As a function of age, optimal models of regional relative brain metabolism were linear for 9 regions, quadratic for 13, cubic for 6, logarithmic for 12, power law for 7, and modified power law for 2 using WBN data and were linear for 9, quadratic for 25, cubic for 2, logarithmic for 6, and power law for 4 using PN data. Sex differences were found to be statistically significant only in the posterior cingulate cortex for the WBN data. Comparing our models with the validation group resulted in 94.3% of regions falling within the 95% prediction interval for WBN and 94.1% for PN. For all brain regions in the validation group, the error in prediction was 3% ± 0.96% using WBN data and 4.72% ± 1.25% when compared with the PN data (P < 0.0001). Conclusion: Pediatric brain metabolism is a complex function of age and sex. We have developed mathematic models of brain activity that allow for accurate prediction of regional pediatric brain metabolism.
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“Normal brain [18F]FDG uptake varies with age, sex, and the presence or absence of diabetes mellitus [1,6,9,10].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [10]
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Metadata
- Authors
- Turpin, S., Martineau, P., Levasseur, M.-A., & Lambert, R.
- Affiliations
- Centre Hospitalier Universitaire Sainte-Justine (CA)
- University of Ottawa (CA)
- Centre Hospitalier Universitaire de Sherbrooke (CA)
- Venue
- Journal of Nuclear Medicine
- Publisher
- Society of Nuclear Medicine
- Published
- 2017-12-28
- Volume
- 59
- Issue
- 7
- Pages
- 1118-1124
- ISSN
- 0161-5505 (ISSN-L)
- 2159-662X
- OpenAlex
- W2777614217
- Cited by
- 10
- References
- 25
- Citations by year
- 2026: 2 · 2023: 2 · 2022: 3 · 2021: 1 · 2019: 2
- FWCI
- 0.42
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Nuclear Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- 18F-FDG PET, age-related brain development, sex differences, regional brain metabolism, mathematical modeling, reference database, posterior cingulate cortex, brain activity prediction
- MeSH terms
- Positron Emission Tomography Computed Tomography, Aging, Brain, Child, Female, Humans, Male, Models, Biological, Sex Characteristics, Fluorodeoxyglucose F18
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- Turpin, S., Martineau, P., Levasseur, M.-A., & Lambert, R. (2018). Modeling the Effects of Age and Sex on Normal Pediatric Brain Metabolism Using18F-FDG PET/CT. Journal of Nuclear Medicine. https://doi.org/10.2967/jnumed.117.201889
