Abstract
The cerebellum is the region most commonly used as a reference when normalizing the intensity of perfusion images acquired using magnetic resonance imaging (MRI) in Alzheimer’s disease (AD) studies. In addition, the cerebellum provides unbiased estimations with nuclear medicine techniques. However, no reports confirm the cerebellum as an optimal reference region in MRI studies or evaluate the consequences of using different normalization regions. In this study, we address the effect of using the cerebellum, whole-brain white matter, and whole-brain cortical gray matter in the normalization of cerebral blood flow (CBF) parametric maps by comparing patients with stable mild cognitive impairment (MCI), patients with AD and healthy controls. According to our results, normalization by whole-brain cortical gray matter enables more sensitive detection of perfusion abnormalities in AD patients and reveals a larger number of affected regions than data normalized by the cerebellum or whole-brain white matter. Therefore, the cerebellum is not the most valid reference region in MRI studies for early stages of AD. After normalization by whole-brain cortical gray matter, we found a significant decrease in CBF in both parietal lobes and an increase in CBF in the right medial temporal lobe. We found no differences in perfusion between patients with stable MCI and healthy controls either before or after normalization.
Highlights
Alterations in cerebral hemodynamic processes are thought to be involved in the pathogenesis of Alzheimer’s disease (AD) [1,2,3]
We address the effect of using different regions for normalization in an analysis of cerebral blood flow (CBF) parametric maps comparing patients with mild cognitive impairment (MCI), AD patients and healthy controls
CBF data normalized by whole-brain cortical gray matter (GM) showed significantly lower CBF mean values in the right and left parietal lobes and higher mean values in the right medial temporal lobe in AD patients than in the control group (Fig. 2)
Summary
Alterations in cerebral hemodynamic processes are thought to be involved in the pathogenesis of Alzheimer’s disease (AD) [1,2,3]. Measurement of cerebral perfusion using functional imaging may provide useful information for early detection and tracking of AD. This assessment has been carried out using nuclear medicine techniques, such as positron emission tomography (PET) or single-photon emission computed tomography (SPECT). Perfusion MRI is affected by wide physiological variability in perfusion measurements across subjects. This variability, which is due to uncontrolled biological and experimental factors [9], makes it difficult to detect group differences, especially in small samples. In order to achieve more sensitive detection of disease-dependent patterns of altered perfusion, variability can be improved by normalizing data before performing comparative analysis
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