Effective diagnosis of Alzheimer’s disease (AD) and Mild Cognitive Impairment (MCI), a
transitional state between normal and AD, is of great importance in dementia research. Different neuroimaging
biomarkers for AD may be potentially different and complementary in the diagnosis of AD.
It is necessary to combine multimodal neuroimaging biomarkers simultaneously for the higher classification accuracy and
more effective diagnosis. In this study, Magnetic Resonance Imaging (MRI) and Fluorine-18 deoxyglucose (FDG) positron
emission tomography (PET) were firstly analysed separately, then biomarkers from both MRI and FDG-PET were
combined using logistic regression and fisher linear discrimination, widely used approaches to combine multiple variables
for the simultaneous analysis. The results showed that MRI and FDG-PET biomarkers were all sensitive to the AD diagnosis,
although some differences existed. Combining information from multiple brain regions or from multimodal neuroimaging
data sets could increase the accuracy of distinguishing AD or MCI patients from NC group, instead of causing information
Keywords: Alzheimer’s disease (AD), mild cognitive impairment (MCI), neuroimaging biomarker, MRI, FDG-PET.
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