Multimodal Discrimination of Alzheimer's Disease Based on Regional Cortical Atrophy and Hypometabolism

Abstract

Structural MR image (MRI) and 18F-Fluorodeoxyglucose-positron emission tomography (FDG-PET) have been widely employed in diagnosis of both Alzheimer's disease (AD) and mild cognitive impairment (MCI) pathology, which has led to the development of methods to distinguish AD and MCI from normal controls (NC). Synaptic dysfunction leads to a reduction in the rate of metabolism of glucose in the brain and is thought to represent AD progression. FDG-PET has the unique ability to estimate glucose metabolism, providing information on the distribution of hypometabolism. In addition, patients with AD exhibit significant neuronal loss in cerebral regions, and previous AD research has shown that structural MRI can be used to sensitively measure cortical atrophy. In this paper, we introduced a new method to discriminate AD from NC based on complementary information obtained by FDG and MRI. For accurate classification, surface-based features were employed and 12 predefined regions were selected from previous studies based on both MRI and FDG-PET. Partial least square linear discriminant analysis was employed for making diagnoses. We obtained 93.6% classification accuracy, 90.1% sensitivity, and 96.5% specificity in discriminating AD from NC. The classification scheme had an accuracy of 76.5% and sensitivity and specificity of 46.5% and 89.6%, respectively, for discriminating MCI from AD. Our method exhibited a superior classification performance compared with single modal approaches and yielded parallel accuracy to previous multimodal classification studies using MRI and FDG-PET.

Fig 1. Mapping on FDG uptake and wPVE to the cortical surface.

The intensity profile (green line) is derived for each pair of corresponding vertices and divided into five equal proportions to make intermediate vertices (red points). FDG uptake (black curve) and wPVE values (gray curve) of intermediate vertices are interpolated from neighborhood voxels (orange points).

Fig 2. The eleven selected regions on the surface-based AAL template known as neurodegenerative regions.

The names of these regions are as follows: angular gyrus, inferior frontal gyrus, inferior occipital gyrus, medial occipital gyrus, middle temporal gyrus, parahippocampal gyrus, posterior cingulate gyrus, precuneus, rectus gyrus, superior occipital gyrus, and supramarginal gyrus.

Fig 3. ROC curve results.

ROC curves are plots of sensitivity and specificity of SMF and SSF for distinguishing AD/NC (left), AD/MCI (middle), and MCI/AD (right). The AU-ROC is included in the figure legend. In every case, SMF (blue) exhibited higher performance than SSF (FDG: red and MRI: green).

Fig 4. Plot representing the correlation between whole brain mean value of PVE maps and cortical thickness.

Both PVE maps were significantly correlated with cortical thickness. swPVE exhibited a higher correlation (r = 0.792) than that of iPVE (r = 0.785).