This automated analysis approach shows that the information provided by normalized FDG uptake and DAT is not redundant for the differential diagnosis of dementia and that taking into account both normalized FDG uptake and DAT uptake allows a better classification of individual patients. These results further support the usefulness of both modalities in the clinical workup of dementia.

The identification of subtle brain changes that are associated with mild cognitive impairment (MCI), the at-risk stage of Alzheimer’s disease, is still a challenging task. Different from existing works, which employ multimodal data (e.g., MRI, PET or CSF) to identify MCI subjects from normal elderly controls, we use four MRI sequences, including T1-weighted MRI (T1), Diffusion Tensor Imaging (DTI), Resting-State functional MRI (RS-fMRI) and Arterial Spin Labeling (ASL) perfusion imaging. Since these MRI sequences simultaneously capture various aspects of brain structure and function during clinical routine scan, it simplifies finding the relationship between subjects by incorporating the mutual information among them. To this end, we devise a hypergraph-based semi-supervised learning algorithm. In particular, we first construct a hypergraph for each of MRI sequences separately using a star expansion method with both the training and testing data. A centralized learning is then performed to model the optimal relevance between subjects by incorporating mutual information between different MRI sequences. We then combine all centralized hypergraphs by learning the optimal weight of each hypergraph based on the minimum Laplacian. We apply our proposed method on a cohort of 41 consecutive MCI subjects and 63 age-and-gender matched controls with four MRI sequences. Our method achieves at least a 7.61% improvement in classification accuracy compared to state-of-the-art methods using multiple MRI data.

Assessment of amyloid deposits is a critical step for the identification of Alzheimer disease (AD) signature in asymptomatic elders. Whether the different amyloid processing methods impacts on the quality of clinico-radiological correlations is still unclear. We directly compared in 155 elderly controls with extensive neuropsychological testing at baseline and 4.5 years follow-up three approaches: (i) operator-dependent standard visual reading, (ii) operator-independent automatic SUVR with four different reference regions, and (iii) novel operator and region of reference-independent automatic Aβ-index. The coefficient of variance was used to examine inter-individual variability for each processing method. Using visually-established amyloid positivity as the gold standard, the area under the receiver operating characteristic curve (ROC) was computed. Linear regression models were used to assess the association between changes in continuous cognitive score and amyloid uptake values. In SUVR analyses, the coefficient of variance varied from 1.718 to 1.762 according to the area of reference and was of − 3.045 for the Aβ-index method. Compared to the visual rating, Aβ-index method showed the largest area under the ROC curve [0.9568 (95% CI 0.9252, 0.98833)]. The best cut-off score was of − 0.3359 with sensitivity and specificity values of 0.97 and 0.83, respectively. Only the Aß-index was related to more severe decrement of cognitive performances [regression coefficient: 9.103 (95% CI 1.148, 17.058)]. The Aβ-index is considered as preferred option in asymptomatic elders, since it is operator-independent, avoids the selection of reference area, is closer to established visual scoring and correlates with the evolution of cognitive performances.

Alzheimer disease (AD) neuropathologic changes are b-amyloid (Ab) deposition, pathologic tau, and neurodegeneration. Dual-phase amyloid PET might be able to evaluate Ab deposition and neurodegeneration with a single tracer injection. Early-phase amyloid PET scans provide a proxy for cerebral perfusion, which has shown good correlations with neural dysfunction measured through metabolic consumption, whereas the late frames depict amyloid distribution. Our study aimed to assess the comparability between early-phase amyloid PET scans and 18 F-FDG PET brain topography at the individual level and their ability to discriminate patients. Methods: One hundred sixty-six subjects evaluated at the Geneva Memory Center, ranging from no cognitive impairment to mild cognitive impairment and dementia, underwent early-phase amyloid PET-using either 18 F-florbetapir (eFBP) (n 5 94) or 18 F-flutemetamol (eFMM) (n 5 72)-and 18 F-FDG PET. Ab status was assessed. SUV ratios (SUVRs) were extracted to evaluate the correlation of eFBP/eFMM and their respective 18 F-FDG PET scans. The single-subject procedure was applied to investigate hypometabolism and hypoperfusion maps and their spatial overlap by the Dice coefficient. Receiver-operating-characteristic analyses were performed to compare the discriminative power of eFBP/eFMM and 18