Parametric imaging of dual-time window [18 F]flutemetamol and [18 F]florbetaben studies

Optimal pharmacokinetic models for quantifying amyloid beta (Aβ) burden using both [18F]flutemetamol and [18F]florbetaben scans have previously been identified at a region of interest (ROI) level. The purpose of this study was to determine optimal quantitative methods for parametric analyses of [18F...

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Autores: Heeman, Fiona, Yaqub, Maqsood, Hendriks, Janine, Bader, Ilona, Barkhof, Frederik, Gispert, Juan Domingo, van Berckel, Bart N. M., Lopes Alves, Isadora, Lammertsma, Adriaan A.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/48827
Acceso en línea:http://hdl.handle.net/10230/48827
http://dx.doi.org/10.1016/j.neuroimage.2021.117953
Access Level:acceso abierto
Palabra clave:Amyloid PET
PET quantification
Parametric imaging
[(18)F]florbetaben
[(18)F]flutemetamol
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network_name_str España
repository_id_str
spelling Parametric imaging of dual-time window [18 F]flutemetamol and [18 F]florbetaben studiesHeeman, FionaYaqub, MaqsoodHendriks, JanineBader, IlonaBarkhof, FrederikGispert, Juan Domingovan Berckel, Bart N. M.Lopes Alves, IsadoraLammertsma, Adriaan A.Amyloid PETPET quantificationParametric imaging[(18)F]florbetaben[(18)F]flutemetamolOptimal pharmacokinetic models for quantifying amyloid beta (Aβ) burden using both [18F]flutemetamol and [18F]florbetaben scans have previously been identified at a region of interest (ROI) level. The purpose of this study was to determine optimal quantitative methods for parametric analyses of [18F]flutemetamol and [18F]florbetaben scans. Forty-six participants were scanned on a PET/MR scanner using a dual-time window protocol and either [18F]flutemetamol (N=24) or [18F]florbetaben (N=22). The following parametric approaches were used to derive DVR estimates: reference Logan (RLogan), receptor parametric mapping (RPM), two-step simplified reference tissue model (SRTM2) and multilinear reference tissue models (MRTM0, MRTM1, MRTM2), all with cerebellar grey matter as reference tissue. In addition, a standardized uptake value ratio (SUVR) was calculated for the 90-110 min post injection interval. All parametric images were assessed visually. Regional outcome measures were compared with those from a validated ROI method, i.e. DVR derived using RLogan. Visually, RPM, and SRTM2 performed best across tracers and, in addition to SUVR, provided highest AUC values for differentiating between Aβ-positive vs Aβ-negative scans ([18F]flutemetamol: range AUC=0.96-0.97 [18F]florbetaben: range AUC=0.83-0.85). Outcome parameters of most methods were highly correlated with the reference method (R2≥0.87), while lowest correlation were observed for MRTM2 (R2=0.71-0.80). Furthermore, bias was low (≤5%) and independent of underlying amyloid burden for MRTM0 and MRTM1. The optimal parametric method differed per evaluated aspect; however, the best compromise across aspects was found for MRTM0 followed by SRTM2, for both tracers. SRTM2 is the preferred method for parametric imaging because, in addition to its good performance, it has the advantage of providing a measure of relative perfusion (R1), which is useful for measuring disease progression.Elsevier202120212021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/48827http://dx.doi.org/10.1016/j.neuroimage.2021.117953reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésNeuroimage. 2021;234:117953© 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/488272026-05-29T05:05:01Z
dc.title.none.fl_str_mv Parametric imaging of dual-time window [18 F]flutemetamol and [18 F]florbetaben studies
title Parametric imaging of dual-time window [18 F]flutemetamol and [18 F]florbetaben studies
spellingShingle Parametric imaging of dual-time window [18 F]flutemetamol and [18 F]florbetaben studies
Heeman, Fiona
Amyloid PET
PET quantification
Parametric imaging
[(18)F]florbetaben
[(18)F]flutemetamol
title_short Parametric imaging of dual-time window [18 F]flutemetamol and [18 F]florbetaben studies
title_full Parametric imaging of dual-time window [18 F]flutemetamol and [18 F]florbetaben studies
title_fullStr Parametric imaging of dual-time window [18 F]flutemetamol and [18 F]florbetaben studies
title_full_unstemmed Parametric imaging of dual-time window [18 F]flutemetamol and [18 F]florbetaben studies
title_sort Parametric imaging of dual-time window [18 F]flutemetamol and [18 F]florbetaben studies
dc.creator.none.fl_str_mv Heeman, Fiona
Yaqub, Maqsood
Hendriks, Janine
Bader, Ilona
Barkhof, Frederik
Gispert, Juan Domingo
van Berckel, Bart N. M.
Lopes Alves, Isadora
Lammertsma, Adriaan A.
author Heeman, Fiona
author_facet Heeman, Fiona
Yaqub, Maqsood
Hendriks, Janine
Bader, Ilona
Barkhof, Frederik
Gispert, Juan Domingo
van Berckel, Bart N. M.
Lopes Alves, Isadora
Lammertsma, Adriaan A.
author_role author
author2 Yaqub, Maqsood
Hendriks, Janine
Bader, Ilona
Barkhof, Frederik
Gispert, Juan Domingo
van Berckel, Bart N. M.
Lopes Alves, Isadora
Lammertsma, Adriaan A.
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Amyloid PET
PET quantification
Parametric imaging
[(18)F]florbetaben
[(18)F]flutemetamol
topic Amyloid PET
PET quantification
Parametric imaging
[(18)F]florbetaben
[(18)F]flutemetamol
description Optimal pharmacokinetic models for quantifying amyloid beta (Aβ) burden using both [18F]flutemetamol and [18F]florbetaben scans have previously been identified at a region of interest (ROI) level. The purpose of this study was to determine optimal quantitative methods for parametric analyses of [18F]flutemetamol and [18F]florbetaben scans. Forty-six participants were scanned on a PET/MR scanner using a dual-time window protocol and either [18F]flutemetamol (N=24) or [18F]florbetaben (N=22). The following parametric approaches were used to derive DVR estimates: reference Logan (RLogan), receptor parametric mapping (RPM), two-step simplified reference tissue model (SRTM2) and multilinear reference tissue models (MRTM0, MRTM1, MRTM2), all with cerebellar grey matter as reference tissue. In addition, a standardized uptake value ratio (SUVR) was calculated for the 90-110 min post injection interval. All parametric images were assessed visually. Regional outcome measures were compared with those from a validated ROI method, i.e. DVR derived using RLogan. Visually, RPM, and SRTM2 performed best across tracers and, in addition to SUVR, provided highest AUC values for differentiating between Aβ-positive vs Aβ-negative scans ([18F]flutemetamol: range AUC=0.96-0.97 [18F]florbetaben: range AUC=0.83-0.85). Outcome parameters of most methods were highly correlated with the reference method (R2≥0.87), while lowest correlation were observed for MRTM2 (R2=0.71-0.80). Furthermore, bias was low (≤5%) and independent of underlying amyloid burden for MRTM0 and MRTM1. The optimal parametric method differed per evaluated aspect; however, the best compromise across aspects was found for MRTM0 followed by SRTM2, for both tracers. SRTM2 is the preferred method for parametric imaging because, in addition to its good performance, it has the advantage of providing a measure of relative perfusion (R1), which is useful for measuring disease progression.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/48827
http://dx.doi.org/10.1016/j.neuroimage.2021.117953
url http://hdl.handle.net/10230/48827
http://dx.doi.org/10.1016/j.neuroimage.2021.117953
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Neuroimage. 2021;234:117953
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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