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Quantification of amyloid PET for future clinical use: a state-of-the-art review
Open accessAbstract
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.
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![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)](/paper-figures/068040bb8ced46d1a05aad7df56160b1/quantification-of-amyloid-pet-for-future-clinical-use-a-state-of-the-art-review-figure-1.jpg)
![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)](/paper-figures/955d5ef0c83f48fc958387a393b02d7f/quantification-of-amyloid-pet-for-future-clinical-use-a-state-of-the-art-review-figure-5.jpg)
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“Moreover, the range from 12 Centiloids to 30 Centiloids has been proposed to reflect the ‘gray zone’ of Aβ deposition24.”
From Plasma p-tau231 and p-tau217 as state markers of amyloid-β pathology in preclinical Alzheimer’s disease (2022) · cites this paper as [24]
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Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria
Dubois, B., Feldman, H. H., Jacova, C., DeKosky, S. T., Barberger-Gateau, P., Cummings, J., Delacourte, A., Galasko, D., Gauthier, S., Jicha, G., et al. (2007) · The Lancet Neurology · doi:10.1016/s1474-4422(07)70178-3 · Cited by 4,411
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Phases of Aβ-deposition in the human brain and its relevance for the development of AD
Thal, D. R., Rüb, U., Orantes, M., & Braak, H. (2002) · Neurology · doi:10.1212/wnl.58.12.1791 · Cited by 3,490
Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria
Dubois, B., Feldman, H. H., Jacova, C., Hampel, H., Molinuevo, J. L., Blennow, K., DeKosky, S. T., Gauthier, S., Selkoe, D., Bateman, R., et al. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70090-0 · Cited by 3,321
The antibody aducanumab reduces Aβ plaques in Alzheimer’s disease
Sevigny, J., Chiao, P., Bussière, T., Weinreb, P. H., Williams, L., Maier, M., Dunstan, R., Salloway, S., Chen, T., Ling, Y., et al. (2016) · Nature · doi:10.1038/nature19323 · Cited by 3,059
Amyloid deposition as the central event in the aetiology of Alzheimer’s disease
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Metadata
- Authors
- Pemberton, H. G., Collij, L. E., Heeman, F., Bollack, A., Shekari, M., Salvadó, G., Alves, I. L., Garcia, D. V., Battle, M., Buckley, C., Stephens, A. W., Bullich, S., Garibotto, V., Barkhof, F., Gispert, J. D., Farrar, G., & on behalf of the AMYPAD consortium
- Affiliations
- UCL Queen Square Institute of Neurology (GB)
- Amsterdam University Medical Centers (NL)
- University College London (GB)
- Universitat Pompeu Fabra (ES)
- Lund University (SE)
- University of Geneva (CH)
- Corresponding author
- Pemberton, Hugh G.
- ORCID
- Venue
- European Journal of Nuclear Medicine and Molecular Imaging
- Published
- 2022-04-07
- Volume
- 49
- Issue
- 10
- Pages
- 3508-3528
- ISSN
- 1619-7070 (ISSN-L)
- 1619-7089
- PMC
- PMC9308604
- OpenAlex
- W4225623397
- Cited by
- 226
- References
- 220
- Citations by year
- 2026: 61 · 2025: 71 · 2024: 64 · 2023: 25 · 2022: 5
- FWCI
- 7.10
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- European Journal of Nuclear Medicine and Molecular Imaging (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
- Archive ouverte UNIGE (University of Geneva) (publishedVersion, other-oa)
- Pure Amsterdam UMC (submittedVersion, cc-by)
- UCL Discovery (University College London) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Repositori digital de la UPF (Universitat Pompeu Fabra) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Innovative Medicines Initiative (115952)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Keywords
- amyloid PET quantification, amyloid-beta, Alzheimer's disease, fluorine-18 radiotracer, aducanumab, treatment response monitoring, cognitive decline prediction, patient selection for clinical trials, amyloid imaging
- MeSH terms
- Alzheimer Disease, Amyloid, Amyloidosis, Brain, Humans, Amyloid beta-Peptides, Positron-Emission Tomography, Cognitive Dysfunction
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