Early detection of amyloid load using 18F-florbetaben PET

Abstract

Background: A low amount and extent of Aβ deposition at early stages of Alzheimer's disease (AD) may limit the use of previously developed pathology-proven composite SUVR cutoffs. This study aims to characterize the population with earliest abnormal Aβ accumulation using ¹⁸F-florbetaben PET. Quantitative thresholds for the early (SUVR_early) and established (SUVR_estab) Aβ deposition were developed, and the topography of early Aβ deposition was assessed. Subsequently, Aβ accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aβ deposition.

Methods: The study population consisted of 686 subjects (n = 287 (cognitively normal healthy controls), n = 166 (subjects with subjective cognitive decline (SCD)), n = 129 (subjects with MCI), and n = 101 (subjects with AD dementia)). Three categories in the Aβ-deposition continuum were defined based on the developed SUVR cutoffs: Aβ-negative subjects, subjects with early Aβ deposition ("gray zone"), and subjects with established Aβ pathology.

Results: SUVR using the whole cerebellum as the reference region and centiloid (CL) cutoffs for early and established amyloid pathology were 1.10 (13.5 CL) and 1.24 (35.7 CL), respectively. Cingulate cortices and precuneus, frontal, and inferior lateral temporal cortices were the regions showing the initial pathological tracer retention. Subjects in the "gray zone" or with established Aβ pathology accumulated more amyloid over time than Aβ-negative subjects. After a 4-year clinical follow-up, none of the Aβ-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aβ pathology progressed. Tau deposition was infrequent in those subjects without established Aβ pathology.

Conclusions: This study supports the utility of using two cutoffs for amyloid PET abnormality defining a "gray zone": a lower cutoff of 13.5 CL indicating emerging Aβ pathology and a higher cutoff of 35.7 CL where amyloid burden levels correspond to established neuropathology findings. These cutoffs define a subset of subjects characterized by pre-AD dementia levels of amyloid burden that precede other biomarkers such as tau deposition or clinical symptoms and accelerated amyloid accumulation. The determination of different amyloid loads, particularly low amyloid levels, is useful in determining who will eventually progress to dementia. Quantitation of amyloid provides a sensitive measure in these low-load cases and may help to identify a group of subjects most likely to benefit from intervention.

Trial registration: Data used in this manuscript belong to clinical trials registered in ClinicalTrials.gov ( NCT00928304 , NCT00750282 , NCT01138111 , NCT02854033 ) and EudraCT (2014-000798-38).

Keywords: Alzheimer’s disease; Amyloid-beta; Florbetaben; Mild cognitive impairment; PET; Subjective memory complainers.

Fig. 1

Histograms of standardized uptake value ratios (SUVRs) and cortex centiloids (CLs) in young healthy controls (n = 65, dataset #1), fitted Gaussian distribution (red), and SUVR cutoff derived for the detection of early Aβ pathology (red dashed line)

Fig. 2

Receiver operating characteristic curves obtained using MRI-derived regions of interest (ROIs, left) and centiloid (right) used to derive standardized uptake value ratio cutoffs for the established Alzheimer’s disease pathology from a group of elderly healthy controls (n = 66) and subjects with AD dementia (n = 73, dataset #2)

Fig. 3

Heat maps of standardized uptake value ratios (SUVRs, left) and ΔSUVRs (=SUVR − SUVR(t = T₅₀)) (right) of all the participants in the analysis (n = 686, datasets #1, #2, #3, #4, and #5). Each column of the heat map represents one subject of the sample. The subjects were sorted according to their composite SUVR (increasing from left to right)

Fig. 4

Histograms of composite standardized uptake value ratios (SUVRs) and centiloids (CLs) for the sample of subjective cognitive decline (SCD) (n = 168, dataset #3) subjects at baseline (first column) and at follow-up (central column). Red and blue lines represent the SUVR abnormality cutoffs for early Aβ detection and established Aβ pathology, respectively. The rate of Aβ accumulation in SCD (and 95% confidence interval in red) in three categories of the composite SUVR continuum (Aβ-negative, gray zone, and established Aβ deposition) is shown on the right column. ROI region of interest

Fig. 5

Histograms of composite standardized uptake value ratios (SUVRs) and centiloids (CLs) for the sample of mild cognitive impairment (MCI) (n = 44, dataset #4) subjects are shown on the top row. Subjects that progressed to Alzheimer’s disease (AD) dementia after a 4-year clinical follow-up are shown in gray. Red and blue lines represent the SUVR abnormality cutoffs for early Aβ detection and established Aβ pathology, respectively. The rate of Aβ accumulation in MCI subjects (and 95% confidence interval in red) in three categories of the composite SUVR continuum: Aβ-negative, gray zone, and with established Aβ deposition, is shown on the bottom row. ROI region of interest

Fig. 6

Scatter plots of Flortaucipir (FTP) standardized uptake value ratios (SUVRs) versus ¹⁸F-florbetaben composite SUVRs using MRI-based regions of interest (ROIs, top row) and FTP SUVRs versus centiloids (CLs, bottom row) (n = 270, dataset #5). Red and blue lines represent the composite SUVR abnormality cutoffs for early Aβ detection and established Aβ pathology, respectively

Fig. 7

Sensitivities, specificities, and agreement rates between visual assessment and quantitative assessment when using several cutoffs to dichotomize the sample (top row) and composite standardized uptake value ratio (SUVR) versus subject identifier (bottom row) (n = 416) (datasets #1, #2, #3, and #4). Red and blue lines represent the composite SUVR abnormality cutoffs for early Aβ detection and established Aβ pathology, respectively. ROI region of interest, CL centiloid