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Total-body [15O]water PET quantifies cerebral blood flow in neurologically healthy adults aged 21 to 86 years.

Total-body [15O]water PET quantifies cerebral blood flow in neurologically healthy adults aged 21 to…
Photo by Shawn Day / Unsplash
Key Takeaway
Note that total-body [15O]water PET shows high reproducibility but requires large normative datasets for individual clinical interpretation.

This observational study assessed quantitative cerebral blood flow (CBF) using total-body [15O]water PET in a cohort of 302 neurologically healthy adults ranging from 21 to 86 years of age. The primary outcome measured was mean grey matter CBF, while secondary outcomes included inter-individual variability, within-subject variability, and reproducibility. No adverse events, serious adverse events, discontinuations, or tolerability issues were reported during the evaluation.

The analysis revealed a mean grey matter CBF of 46.1 mL/(min*dL). Advancing age was associated with a decline in CBF of approximately 7% per decade. Additionally, higher body mass index correlated with lower CBF, estimated at approximately -6% per 10 kg/m2. Sex differences were observed, with women exhibiting higher CBF than men by approximately 7.5%; this disparity was explained by lower blood hemoglobin concentrations in women.

Within-subject reproducibility was characterized as high, supported by intraclass correlation coefficients ranging from 0.78 to 0.89. A key limitation identified was the restricted clinical interpretation of individual CBF measurements due to the absence of large normative datasets that account for physiological variability across the adult lifespan. The practice relevance of these findings suggests that total-body [15O]water PET may enable automated detection of abnormal brain perfusion in clinical PET imaging settings.

Study Details

Sample sizen = 51
EvidenceLevel 5
PublishedApr 2026
View Original Abstract ↓
BackgroundQuantitative cerebral blood flow (CBF) measured with [15O]water positron emission tomography (PET) is the reference standard for quantifying brain perfusion. However, clinical interpretation of individual CBF measurements is limited by the absence of large normative datasets accounting for physiological variability across the adult lifespan. Long-axial field-of-view PET enables high-sensitivity quantitative [15O]water perfusion imaging without arterial blood sampling, allowing normative characterization of cerebral perfusion at unprecedented scale. The aim of this study was to establish normative and covariate-adjusted models of cerebral blood flow across the adult lifespan using total-body [15O]water PET. MethodsQuantitative CBF measurements were obtained in 302 neurologically healthy adults (age 21-86 years) using total-body [15O]water PET. Linear mixed-effects models were used to evaluate the effects of age, sex, body mass index (BMI), and blood hemoglobin concentration on CBF and to generate normative prediction models across the adult lifespan. Between-subject and within-subject variability were estimated from repeated scans in a subset of participants (n=51). ResultsMean grey matter CBF was 46.1 mL/(min*dL), with substantial inter-individual variability but high within-subject reproducibility (intraclass correlation coefficients 0.78-0.89). Advancing age was associated with a decline in CBF of approximately 7% per decade (p_FDR < 10-12). Higher BMI was associated with lower CBF (approximately -6% per 10 kg/m2; p_FDR < 0.01). Women exhibited higher CBF than men (approximately 7.5%), but this difference was largely explained by lower blood hemoglobin concentration in women. Covariate-adjusted models were used to generate normative predictions and prediction intervals describing expected CBF across adulthood. ConclusionThis study establishes a normative database of quantitative cerebral blood flow across the adult lifespan using high-sensitivity [15O]water PET. Age, BMI, and hemoglobin are major determinants of inter-individual variability in CBF. The resulting generative models provide a quantitative reference framework for interpreting cerebral perfusion measurements and may enable automated detection of abnormal brain perfusion in clinical PET imaging.
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