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Review
. 2022 Aug;49(10):3508-3528.
doi: 10.1007/s00259-022-05784-y. Epub 2022 Apr 7.

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Affiliations
Review

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Hugh G Pemberton et al. Eur J Nucl Med Mol Imaging. 2022 Aug.

Abstract

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.

Keywords: Alzheimer’s; Amyloid; Brain; Centiloid; Dementia; PET; Quantification; SUVr.

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Conflict of interest statement

HP, GF, MB, and CB are all employees of GE Healthcare. SB and AS are employees of Life Molecular Imaging GmbH. VG has received funding from the Swiss National Science Foundation (project n. 185028, 188355, and 169876), the Velux Foundation, the Schmidheiny Foundation, and research/teaching support through her institution from Siemens Healthineers, GE Healthcare, Roche, Merck, Cerveau Technologies, and Life Molecular Imaging. FB is a steering committee and iDMC member of studies by Biogen, Merck, Roche, and EISAI. He is a consultant to Roche, Biogen, Merck, IXICO, Jansen, and Combinostics. He has research agreements with Novartis, Merck, Biogen, GE, and Roche and is co-founder of Queen Square Analytics Ltd. His research is sponsored by the NIHR-UCLH Biomedical Research Centre, UK MS Society, MAGNIMS-ECTRIMS, EC-H2020, EC-JU (IMI), and EPSRC.

Figures

Fig. 1
Fig. 1
Illustrative PET images derived from the five most commonly used amyloid tracers on different patients. The left column shows Aß negative subjects (all ~0 Centiloid) and right column shows Aß positive subjects (all ~50 Centiloid, for further details, see “Centiloid scaling” section). Colour schemes used for regulatory approved tracers are in line with each of their FDA label prescribing information: [18F]flutemetamol (https://www.accessdata.fda.gov/drugsatfda_docs/label/2016/203137s005lbl.pdf), [18F]florbetaben (https://www.accessdata.fda.gov/drugsatfda_docs/label/2014/204677s000lbl.pdf), [18F]florbetapir (https://www.accessdata.fda.gov/drugsatfda_docs/label/2012/202008s000lbl.pdf)
Fig. 2
Fig. 2
Example of the most common reference and target regions used when generating SUVr
Fig. 3
Fig. 3
Bar graph showing the increasing use of CLs in academic publications. The numbers were obtained through a PubMed search for “Centiloid” in all fields on 7th September 2021
Fig. 4
Fig. 4
Summary of the various CL thresholds established in the literature and in use for clinical current clinical trial inclusion
Fig. 5
Fig. 5
Example of quantitative metrics computed on two subjects from the AIBL dataset scanned with [18F]flutemetamol. Low amyloid uptake (left image) and high amyloid uptake (right image), including demographics. It was not possible to compute AMYQ due to the proprietary nature of the software. Abbreviations: mini-mental state examination (MMSE), standardised uptake value ratio (SUVr); amyloid-β (Aβ)

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