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Comparative Study
. 2011 Dec;32(12):2322.e19-27.
doi: 10.1016/j.neurobiolaging.2010.05.023. Epub 2010 Jul 1.

Prediction of MCI to AD conversion, via MRI, CSF biomarkers, and pattern classification

Affiliations
Comparative Study

Prediction of MCI to AD conversion, via MRI, CSF biomarkers, and pattern classification

Christos Davatzikos et al. Neurobiol Aging. 2011 Dec.

Abstract

Magnetic resonance imaging (MRI) patterns were examined together with cerebrospinal fluid (CSF) biomarkers in serial scans of Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with mild cognitive impairment (MCI). The SPARE-AD score, summarizing brain atrophy patterns, was tested as a predictor of short-term conversion to Alzheimer's disease (AD). MCI individuals that converted to AD (MCI-C) had mostly positive baseline SPARE-AD (Spatial Pattern of Abnormalities for Recognition of Early AD) and atrophy in temporal lobe gray matter (GM) and white matter (WM), posterior cingulate/precuneous, and insula. MCI individuals that converted to AD had mostly AD-like baseline CSF biomarkers. MCI nonconverters (MCI-NC) had mixed baseline SPARE-AD and CSF values, suggesting that some MCI-NC subjects may later convert. Those MCI-NC with most negative baseline SPARE-AD scores (normal brain structure) had significantly higher baseline Mini Mental State Examination (MMSE) scores (28.67) than others, and relatively low annual rate of Mini Mental State Examination decrease (-0.25). MCI-NC with midlevel baseline SPARE-AD displayed faster annual rates of SPARE-AD increase (indicating progressing atrophy). SPARE-AD and CSF combination improved prediction over individual values. In summary, both SPARE-AD and CSF biomarkers showed high baseline sensitivity, however, many MCI-NC had abnormal baseline SPARE-AD and CSF biomarkers. Longer follow-up will elucidate the specificity of baseline measurements.

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Figures

Fig. 1
Fig. 1
Maps of the t-statistics showing differences between MCI-C and MCI-NC. (a) and (b) show significantly more GM in MCI-NC relative to MCI-C (red/yellow), and areas of relatively increased periventricular WM tissue that appears gray in T1 images, likely due to Leukoaraiosis, in MCI-C relatively to MCI-NC (blue). (c) and (d) show regions of relatively reduced WM in MCI-C relative to MCI-NC (red/yellow). Temporal, prefrontal and orbitofrontal reduced WM are evident, along with periventricular loss likely due to Leukoaraiosis, and with white matter in the vicinity of the precuneous. (e) and (f) show the difference in rate of GM change over time (“beta” maps) between MCI-C and MCI-NC. Red/yellow reflects relatively more rapidly increasing gray-looking tissue in MCI-C, likely due to progression of Leukoaraiosis. Regions of relatively higher loss of GM tissue in MCI-C are shown in blue, reflecting higher rate of atrophy in MCI-C. Images are in radiology convention. T-maps were thresholded at the p=0.05 level.
Fig. 2
Fig. 2
The histograms of baseline SPARE-AD scores for MCI-C (left) and MCI-NC (right).
Fig. 3
Fig. 3
Trajectories of average SPARE-AD scores for MCI-C and sub-groups of MCI-NC. Scan #3 is on the average 12 months after Scan #1.
Fig. 4
Fig. 4
Scatterplots of SPARE-AD against CSF markers Aβ42 and t-tau. The two oblique lines represent the SVM classifiers achieving two different levels of sensitivity, i.e. correct classification of MCI-C: ~82% (dotted line) and ~92% (solid line).

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