Results: 2

1.
Figure 2:

Figure 2:. From: Predicting Cognitive Decline in Subjects at Risk for Alzheimer Disease by Using Combined Cerebrospinal Fluid, MR Imaging, and PET Biomarkers.

Receiver operating characteristic curves for all of the logistic regression models for predicting conversion from MCI to AD. Of the three biomarkers alone, FDG PET added the most prognostic information with an area under the curve (AUC) of 0.874, compared with MR imaging (area under the curve = 0.741) and CSF proteins (area under the curve = 0.695).

Jennifer L. Shaffer, et al. Radiology. 2013 February;266(2):583-591.
2.
Figure 1:

Figure 1:. From: Predicting Cognitive Decline in Subjects at Risk for Alzheimer Disease by Using Combined Cerebrospinal Fluid, MR Imaging, and PET Biomarkers.

Example components from separate ICAs. Z threshold was 1.5. Both components significantly differentiated converters from nonconverters. Left: The MR imaging component (Comp) highlights in red the bilateral medial temporal lobes, inferior and lateral temporal lobes, and anterior and inferior frontal lobes, consistent with atrophy in these regions in converters. Negative signal, noted in blue, is seen in the periventricular white matter, consistent with higher levels of white matter disease in converters. Right: The FDG PET component highlights in red the temporoparietal lobes, right greater than left, and the posterior cingulate region, consistent with hypometabolism in these regions in converters.

Jennifer L. Shaffer, et al. Radiology. 2013 February;266(2):583-591.

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