Journal
JOURNAL OF NUCLEAR MEDICINE
Volume 60, Issue 4, Pages 536-540Publisher
SOC NUCLEAR MEDICINE INC
DOI: 10.2967/jnumed.118.210518
Keywords
neurology; PET; Alzheimer disease; amyloid; florbetapir; mathematic modeling
Funding
- NIA NIH HHS [U01 AG024904] Funding Source: Medline
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Amyloid-beta (A beta) plays a key role in the pathogenesis of Alzheimer disease (AD) and can be imaged in vivo using F-18-florbetapir PET. A composite SUV ratio (SUVr) is a commonly used outcome measure for quantifying the global A beta burden; however, sensitivity is suboptimal and can lead to low power in clinical trials. We introduce amyloid load, A beta(L), as a novel biomarker to quantify the global A beta burden along with an automated algorithm for its calculation (Amyloid(IQ)). A beta(L) is evaluated on cross-sectional and longitudinal data obtained from the Alzheimer's Disease Neuroimaging Initiative. The cross-sectional data consisted of 769 subjects across the disease spectrum (211 healthy controls, 223 patients with early mild cognitive impairment, 204 with late mild cognitive impairment, and 132 with AD). The distributions of A beta(L) in the 4 different classifications were compared, and the same analyses were applied to a composite SUVr outcome measure. The effect sizes (Hedges g) between all but one classification were higher for A beta(L) than for composite SUVr, with the mean difference being 46%. Of the patients with early mild cognitive impairment, 147 had a 2-y follow-up scan, and the effect size between baseline and follow-up for A beta(L) was 0.49, compared with 0.36 for a composite SUVr, demonstrating an equivalent increase in power for longitudinal data. These results offer evidence that A beta(L) will be a valuable outcome measure in future A beta imaging studies, providing a substantial increase in power over currently used SUVr methods.
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