TY - JOUR
T1 - Quantification of amyloid PET for future clinical use
T2 - a state-of-the-art review
AU - Pemberton, Hugh G.
AU - Collij, Lyduine E.
AU - Heeman, Fiona
AU - Bollack, Ariane
AU - Shekari, Mahnaz
AU - Salvadó, Gemma
AU - Alves, Isadora Lopes
AU - Garcia, David Vallez
AU - Battle, Mark
AU - Buckley, Christopher
AU - Stephens, Andrew W.
AU - Bullich, Santiago
AU - Garibotto, Valentina
AU - Barkhof, Frederik
AU - on behalf of the AMYPAD Consortium
AU - Gispert, Juan Domingo
AU - Farrar, Gill
N1 - Funding Information: The project leading to this publication has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115952. This Joint Undertaking receives the support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This communication reflects the views of the authors and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein. Funding Information: 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. Publisher Copyright: © 2022, The Author(s).
PY - 2022/8
Y1 - 2022/8
N2 - 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.
AB - 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.
KW - Alzheimer’s
KW - Amyloid
KW - Brain
KW - Centiloid
KW - Dementia
KW - PET
KW - Quantification
KW - SUVr
UR - http://www.scopus.com/inward/record.url?scp=85127735553&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/s00259-022-05784-y
DO - https://doi.org/10.1007/s00259-022-05784-y
M3 - Review article
C2 - 35389071
SN - 1619-7070
VL - 49
SP - 3508
EP - 3528
JO - European journal of nuclear medicine and molecular imaging
JF - European journal of nuclear medicine and molecular imaging
IS - 10
ER -