BackgroundSemiquantitative methods such as the standardized uptake value ratio (SUVR) require normalization of the radiotracer activity to a reference tissue to monitor changes in the accumulation of amyloid-β (Aβ) plaques measured with positron emission tomography (PET). The objective of this study was to evaluate the effect of reference tissue normalization in a test–retest 18F-florbetapir SUVR study using cerebellar gray matter, white matter (two different segmentation masks), brainstem, and corpus callosum as reference regions.MethodsWe calculated the correlation between 18F-florbetapir PET and concurrent cerebrospinal fluid (CSF) Aβ1–42 levels in a late mild cognitive impairment cohort with longitudinal PET and CSF data over the course of 2 years. In addition to conventional SUVR analysis using mean and median values of normalized brain radiotracer activity, we investigated a new image analysis technique—the weighted two-point correlation function (wS2)—to capture potentially more subtle changes in Aβ-PET data.ResultsCompared with the SUVRs normalized to cerebellar gray matter, all cerebral-to-white matter normalization schemes resulted in a higher inverse correlation between PET and CSF Aβ1–42, while the brainstem normalization gave the best results (high and most stable correlation). Compared with the SUVR mean and median values, the wS2 values were associated with the lowest coefficient of variation and highest inverse correlation to CSF Aβ1–42 levels across all time points and reference regions, including the cerebellar gray matter.ConclusionsThe selection of reference tissue for normalization and the choice of image analysis method can affect changes in cortical 18F-florbetapir uptake in longitudinal studies.

BackgroundAmyloid-beta (Aβ) imaging with positron emission tomography (PET) holds promise for detecting the presence of Aβ plaques in the cortical gray matter. Many image analyses focus on regional average measurements of tracer activity distribution; however, considerable additional information is available in the images. Metrics that describe the statistical properties of images, such as the two-point correlation function (S2), have found wide applications in astronomy and materials science. S2 provides a detailed characterization of spatial patterns in images typically referred to as clustering or flocculence. The objective of this study was to translate the two-point correlation method into Aβ-PET of the human brain using 11C-Pittsburgh compound B (11C-PiB) to characterize longitudinal changes in the tracer distribution that may reflect changes in Aβ plaque accumulation.MethodsWe modified the conventional S2 metric, which is primarily used for binary images and formulated a weighted two-point correlation function (wS2) to describe nonbinary, real-valued PET images with a single statistical function. Using serial 11C-PiB scans, we calculated wS2 functions from two-dimensional PET images of different cortical regions as well as three-dimensional data from the whole brain. The area under the wS2 functions was calculated and compared with the mean/median of the standardized uptake value ratio (SUVR). For three-dimensional data, we compared the area under the wS2 curves with the subjects’ cerebrospinal fluid measures.ResultsOverall, the longitudinal changes in wS2 correlated with the increase in mean SUVR but showed lower variance. The whole brain results showed a higher inverse correlation between the cerebrospinal Aβ and wS2 than between the cerebrospinal Aβ and SUVR mean/median. We did not observe any confounding of wS2 by region size or injected dose.ConclusionThe wS2 detects subtle changes and provides additional information about the binding characteristics of radiotracers and Aβ accumulation that are difficult to verify with mean SUVR alone.