Measurement of Longitudinal β-Amyloid Change with ¹⁸F-Florbetapir PET and Standardized Uptake Value Ratios

Abstract

The accurate measurement of β-amyloid (Aβ) change using amyloid PET imaging is important for Alzheimer disease research and clinical trials but poses several unique challenges. In particular, reference region measurement instability may lead to spurious changes in cortical regions of interest. To optimize our ability to measure 18F-florbetapir longitudinal change, we evaluated several candidate regions of interest and their influence on cortical florbetapir change over a 2-y period in participants from the Alzheimer Disease Neuroimaging Initiative (ADNI). Methods We examined the agreement in cortical florbetapir change detected using 6 candidate reference regions (cerebellar gray matter, whole cerebellum, brain stem/pons, eroded subcortical white matter [WM], and 2 additional combinations of these regions) in 520 ADNI subjects. We used concurrent cerebrospinal fluid Aβ1–42 measurements to identify subgroups of ADNI subjects expected to remain stable over follow-up (stable Aβ group; n = 14) and subjects expected to increase (increasing Aβ group; n = 91). We then evaluated reference regions according to whether cortical change was minimal in the stable Aβ group and cortical retention increased in the increasing Aβ group. Results There was poor agreement across reference regions in the amount of cortical change observed across all 520 ADNI subjects. Within the stable Aβ group, however, cortical florbetapir change was 1%–2% across all reference regions, indicating high consistency. In the increasing Aβ group, cortical increases were significant with all reference regions. Reference regions containing WM (as opposed to cerebellum or pons) enabled detection of cortical change that was more physiologically plausible and more likely to increase over time. Conclusion Reference region selection has an important influence on the detection of florbetapir change. Compared with cerebellum or pons alone, reference regions that included subcortical WM resulted in change measurements that are more accurate. In addition, because use of WM-containing reference regions involves dividing out cortical signal contained in the reference region (via partial-volume effects), use of these WM-containing regions may result in more conservative estimates of actual change. Future analyses using different tracers, tracer–kinetic models, pipelines, and comparisons with other biomarkers will further optimize our ability to accurately measure Aβ changes over time.

Spatiotemporal Distribution of β-Amyloid in Alzheimer Disease Is the Result of Heterogeneous Regional Carrying Capacities

“…Analysis of longitudinal studies has either been restricted to short time windows of no more than 2 years (19)(20)(21) or to studying the average deposition across the whole cortex (22). Thus, despite the large amount of in vivo data collected, a full characterisation of the spatiotemporal distribution of Aβ has yet to be performed.…”

Improved Power for Characterizing Longitudinal Amyloid-β PET Changes and Evaluating Amyloid-Modifying Treatments with a Cerebral White Matter Reference Region

“…Although longitudinal analyses have the potential to track the progression of fibrillar Ab deposition over time, to relate this progression to progressive clinical decline, and to evaluate putative Ab-modifying treatments in therapeutic trials, we and others (18)(19)(20)(21)(22) have noted substantial variability in longitudinal florbetapir PET measurements of changes in fibrillar Ab deposition. Some of this variability appears to exceed that expected on the basis of biologic grounds alone (e.g., SUVR changes of .50%, in either direction, over a matter of weeks).…”

“…In this article, we describe the use of a cerebral white matter reference ROI to reduce the variability in longitudinal florbetapir SUVRs, to improve the sensitivity for detecting corresponding increases, and to improve the power for evaluating Ab-modifying treatments-an approach that is also being evaluated by other groups (18)(19)(20)(21)(22). Although cross-sectional cerebral-to-cerebral white matter SUVRs could be affected by the combined effects of fibrillar Ab and partial-volume averaging, we surmised that this confound could be at least partly reduced in the assessment of longitudinal data because between-session differences in white matter measurements (including those related to the combined effects of small gray matter Ab PET changes and partialvolume averaging) would be relatively small.…”

“…(In the accompanying report, Landau et al used baseline cerebrospinal fluid Ab 1-42 levels and longitudinal florbetapir PET data from the ADNI to demonstrate that a cerebral white matter reference ROI was more accurate than a cerebellar ROI in terms of its accuracy in distinguishing subjects who were expected to have longitudinal SUVR increases from those who were expected to have SUVRs that remained stable over time (22). Their data support the use of a white matter reference ROI in the analysis of longitudinal florbetapir PET scans.…”

Amyloid negativity in patients with clinically diagnosed Alzheimer disease and MCI

“…The testretest reliability of the SUVRs was approximately 1.2% 6 0.8% (absolute mean change and SD in stable amyloid-negative controls), as reported previously. 17 Ninety-eight percent of patients with MCI and 100% of patients with AD who were florbetapir1 at baseline remained positive. Four of 54 (7%) patients with MCI and (1/9) 11% of patients with AD who were florbetapir2 at baseline were positive at follow-up.…”