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Link to original content: https://pubmed.ncbi.nlm.nih.gov/19004525/
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. 2010 Oct;31(10):1669-78.
doi: 10.1016/j.neurobiolaging.2008.09.012. Epub 2008 Nov 11.

Plaque and tangle imaging and cognition in normal aging and Alzheimer's disease

Meredith N Braskie  1 , Andrea D Klunder, Kiralee M Hayashi, Hillary Protas, Vladimir Kepe, Karen J Miller, S-C Huang, Jorge R Barrio, Linda M Ercoli, Prabha Siddarth, Nagichettiar Satyamurthy, Jie Liu, Arthur W Toga, Susan Y Bookheimer, Gary W Small, Paul M Thompson
Affiliations

Plaque and tangle imaging and cognition in normal aging and Alzheimer's disease

Meredith N Braskie et al. Neurobiol Aging. 2010 Oct.

Abstract

Amyloid plaques and tau neurofibrillary tangles, the pathological hallmarks of Alzheimer's disease (AD), begin accumulating in the healthy human brain decades before clinical dementia symptoms can be detected. There is great interest in how this pathology spreads in the living brain and its association with cognitive deterioration. Using MRI-derived cortical surface models and four-dimensional animation techniques, we related cognitive ability to positron emission tomography (PET) signal from 2-(1-{6-[(2-[F-18]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile ([(18)F]FDDNP), a molecular imaging probe for plaques and tangles. We examined this relationship at each cortical surface point in 23 older adults (10 cognitively intact, 6 with amnestic mild cognitive impairment, 7 with AD). [(18)F]FDDNP-PET signal was highly correlated with cognitive performance, even in cognitively intact subjects. Animations of [(18)F]FDDNP signal growth with decreased cognition across all subjects (http://www.loni.ucla.edu/ approximately thompson/FDDNP/video.html) mirrored the classic Braak and Braak trajectory in lateral temporal, parietal, and frontal cortices. Regions in which cognitive performance was significantly correlated with [(18)F]FDDNP signal include those that deteriorate earliest in AD, suggesting the potential utility of [(18)F]FDDNP for early diagnosis.

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Figures

Fig. 1
Fig. 1
Increasing [18F]FDDNP and declining cognition. Cortical maps show that as [18F]FDDNP signal (DVR) increased at each cortical surface point (across all subjects), cognitive performance decreased (see Section 2 for calculation of composite test scores). Regions of significant correlation (p < 0.05), color-coded in red, follow the profile of tangle and plaque accumulation characteristic of mild AD, as established in large-scale post mortem mapping studies (Braak and Braak, 1991). Corresponding maps did not show regions where both [18F]FDDNP signal and cognition increased together (not shown here; maps are blue with p > 0.05 at all voxels). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)
Fig. 2
Fig. 2
[18F]FDDNP and cognition in cognitively intact subjects. Frontal regions of the right lateral cortical surface showed elevated [18F]FDDNP signal in healthy normal subjects with poorer cognitive performance when correlation analyses were restricted to cognitively intact subjects (controls only). Cortical maps show similar correlations between [18F]FDDNP signal and composite cognitive score as in Fig. 1, but in a more restricted region. Dorsolateral prefrontal regions are implicated in executive function, which is among the functions required for optimal performance on the neuropsychological tests. Additional correlations were found in parietal association areas; the left lateral hemisphere did not show broad regions with correlations (shown on the right panels here). Corroborating these results, maps of regions in which [18F]FDDNP signal and cognition in cognitively intact subjects increased together showed no effects, as expected (not shown). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)
Fig. 3
Fig. 3
Time-lapse films calibrating maps of [18F]FDDNP signal versus cognition. Projected mean [18F]FDDNP signal (DVR) can be calculated for various cognition scores based on the relationship of [18F]FDDNP signal with cognition in the subjects studied. Here we show projected signal for subjects who scored (A) high normal (2 standard deviations above age-normal), (B) at age-normal levels (Z score = 0), (C) low normal (2 standard deviations lower than age-normal), and (D) at impaired levels (4 standard deviations below age-normal). Red colors denote regions in which greater predicted [18F]FDDNP signal is associated with lower cognitive Z scores at each cortical point based on a nonlinear spatially varying model. The parameterization of disease stages is based on cross-sectional data, but it is plausible that a comparable trajectory would be followed for each cognitive stage in an individual subject, albeit with variable timing across individuals. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)
Fig. 4
Fig. 4
ROI analysis. Scatterplot graphs and linear regressions show the relationship between the composite cognitive scores and average [18F]FDDNP signal in (A) frontal lobe, (B) parietal lobe, (C) lateral temporal lobe, and (D) posterior cingulate gyrus across all subjects. Average [18F]FDDNP signal from both hemispheres was pooled for these analyses.
Fig. 5
Fig. 5
PET-MRI correlation. (A) Maps of the pointwise significance between [18F]FDDNP signal and cortical thickness in millimeters, are shown in 20 subjects. (B) Maps of the pointwise correlation (Pearson’s r value) are shown for the same relationship. These maps show that there is no detectable residual correlation between PET and cortical thickness, and therefore the PET effects observed in Figs. 1 and 2 are not confounded by the effects of atrophy. Thickness and PET signal are orthogonal (not correlated) except in very small, scattered regions not overlapping with the main effects in Figs. 1 and 2. The left frontal pole effects cover no more than 5% of the cortex, so they are likely false positives (5% false positives are expected in any null map thresholded at p = 0.05).
Fig. 6
Fig. 6
Maps of post mortem amyloid load and cortical thickness. (A) Images, which were adapted from Fig. 1 of a previously published paper (Braak and Braak, 1991) (copyright Springer-Verlag, 1991), with kind permission of the authors, Springer Science, and Business Media, display the classic post mortem amyloid deposition pattern. Images displayed in (B) also have been previously published (Thompson et al., 2003) (copyright 2003 by the Society for Neuroscience), and show thinner average gray matter in AD patients (mean MMSE = 18) compared with controls at an initial scan (top right) and a follow-up scan 1.5 years later, when the mean MMSE for AD patients dropped to 13 (bottom right). The pattern of cortical thinning and post mortem amyloid deposition displayed previously in patients with mild to moderate AD (upper panels) mirrors those regions demonstrating a significant correlation between cognitive function and [18F]FDDNP signal in Fig. 1 of the current study [adapted with permission from the authors and publishers].
See this image and copyright information in PMC

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