Preclinical prediction of Alzheimer's disease using SPECT

Abstract

Background: Regional cerebral perfusion measured by single photon emission computed tomography (SPECT) was examined as a preclinical predictor of the development of Alzheimer's disease (AD).

Methods: Singular value decomposition was used to produce 20 SPECT factors (known as vectors) (n=152). Vector scores were then computed for four groups (n=136), differing in cognitive status: Group 1--normal controls at both baseline and follow-up; Group 2--subjects with "questionable" AD at both baseline and follow-up; Group 3--subjects with questionable AD at baseline who converted to AD on follow-up (Converters); Group 4--subjects with AD at baseline. All SPECT data in the analyses were gathered at baseline.

Results: The four groups could be distinguished on the basis of their baseline SPECT data (p < or = 0.00005; hit rate=83%). Regional decreases in perfusion were most prominent among Converters in the hippocampal-amygdaloid complex, the posterior cingulate, the anterior thalamus, and the anterior cingulate. Inclusion of apolipoprotein E status did not significantly improve the discrimination.

Conclusions: SPECT data gathered and analyzed in this manner may be useful as one aspect of the preclinical prediction of AD. Three of the four brain regions important for discriminating Converters from normal controls involve a distributed brain network pertaining to memory, suggesting that this network may be selectively affected in the earliest stages of AD.