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Normalization in PET group comparison studies--the importance of a valid reference region
Per Borghammer1, Kristjana Yr Jonsdottir2, Paul Cumming2
1PET center, Aarhus University Hospitals, Denmark; Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Denmark.
Global mean normalization in cerebral blood flow (CBF) PET studies can create artifactual age and hepatic encephalopathy (HE) effects. Normalizing to white matter (WM) provides more reliable CBF results.
Area of Science:
- Neuroimaging
- Cerebrovascular physiology
- Medical physics
Background:
- Positron emission tomography (PET) studies often normalize cerebral blood flow (CBF) to the global mean to reduce interindividual variation.
- This normalization method assumes no significant group differences in global CBF, which can lead to biased physiological interpretations if violated.
Purpose of the Study:
- To investigate the impact of global mean normalization on CBF measurements in aging and hepatic encephalopathy (HE).
- To evaluate alternative normalization strategies for more accurate CBF assessment.
Main Methods:
- Quantitative [15O]H2O PET scans were acquired in 45 healthy subjects and 14 HE patients.
- CBF was analyzed using volume-of-interest and voxel-based statistics.
- Comparisons included absolute CBF, and CBF normalized to gray matter (GM) and white matter (WM) means, alongside simulation experiments.
Main Results:
- In healthy aging, CBF remained unchanged in WM and central regions, but showed artifactual increases with GM mean normalization.
- Similar artifactual increases in CBF were observed in HE patients and simulation experiments when using global mean normalization.
- Normalization to the WM mean yielded less biased results.
Conclusions:
- Global mean normalization can introduce spurious findings in CBF studies, particularly when subtle group differences in global CBF exist.
- Previous studies using global mean normalization may have led to inaccurate physiological interpretations.
- Normalization to the central white matter (WM) is a more robust method for analyzing CBF in aging and HE, and potentially other conditions.
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