Amyloid-β imaging with Pittsburgh compound B and florbetapir: comparing radiotracers and quantification methods

Abstract

(11)C-Pittsburgh compound B ((11)C-PiB) and (18)F-florbetapir amyloid-β (Aβ) PET radioligands have had a substantial impact on Alzheimer disease research. Although there is evidence that both radioligands bind to fibrillar Aβ in the brain, direct comparisons in the same individuals have not been reported. Here, we evaluated PiB and florbetapir in a retrospective convenience sample of cognitively normal older controls, patients with mild cognitive impairment, and patients with Alzheimer disease from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

Methods: From the ADNI database, 32 participants were identified who had undergone at least 1 PiB study and subsequently underwent a florbetapir study approximately 1.5 y after the last PiB study. Cortical PiB and florbetapir retention was quantified using several different methods to determine the effect of preprocessing factors (such as smoothing and reference region selection) and image processing pipelines.

Results: There was a strong association between PiB and florbetapir cortical retention ratios (Spearman ρ = 0.86-0.95), and these were slightly lower than cortical retention ratios for consecutive PiB scans (Spearman ρ = 0.96-0.98) made approximately 1.1 y apart. Cortical retention ratios for Aβ-positive subjects tended to be higher for PiB than for florbetapir images, yielding slopes for linear regression of florbetapir against PiB of 0.59-0.64. Associations between consecutive PiB scans and between PiB and florbetapir scans remained strong, regardless of processing methods such as smoothing, spatial normalization to a PET template, and use of reference regions. The PiB-florbetapir association was used to interconvert cutoffs for Aβ positivity and negativity between the 2 radioligands, and these cutoffs were highly consistent in their assignment of Aβ status.

Conclusion: PiB and florbetapir retention ratios were strongly associated in the same individuals, and this relationship was consistent across several data analysis methods, despite scan-rescan intervals of more than a year. Cutoff thresholds for determining positive or negative Aβ status can be reliably transformed from PiB to florbetapir units or vice versa using a population scanned with both radioligands.

FIGURE 1

Axial slices of PiB and florbetapir scans are shown for 2 representative subjects, cognitively normal control with low tracer retention (top) and AD patient with high tracer retention in cortex relative to cerebellum, reflecting widespread fibrillar amyloid (bottom).

FIGURE 2

Cortical retention ratios are shown for consecutive PiB and florbetapir scans obtained for same participants and processed using pons (A), whole cerebellum (B), and cerebellar gray matter (C) for intensity normalization. Initial diagnosis at enrollment and any subsequent diagnostic change are represented by shape markers. Stable normal cognition or MCI diagnosis is represented with solid shapes, individuals who progressed are represented with unfilled shapes, and single individual who regressed from MCI to normal is represented with gray-filled square. Raw data were analyzed with PET-template method. Regression equations and Spearman rank correlation coefficients (ρ) are shown for each scatterplot.

FIGURE 3

Cortical retention ratios for 2 consecutive PiB scans and PiB scan followed by florbetapir scan obtained for same participants are compared at different levels of preprocessing and data analysis methods. All cortical retention ratios were normalized using whole cerebellum. Top 2 rows show raw data (not at uniform voxel size or smoothing) (A) and unsmoothed data (at uniform voxel size but not uniform smoothing) (B), both processed using PET-template method. Bottom 2 rows show unsmoothed (C) and smoothed data (uniform voxel size and smoothing) (D) processed with Freesurfer method. Thus, middle 2 rows both show unsmoothed data that differs only on basis of which processing method was used (PET template [B], Freesurfer [C]). Regression equations and Spearman rank correlation coefficients (ρ) are shown for each scatterplot.

FIGURE 4

PiB threshold of 1.47 (14) that is based on data normalized to cerebellar gray matter can be converted to florbetapir threshold of 1.13, using raw data and whole-cerebellum normalization.