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dc.creatorChincarini, A. (A.)-
dc.creatorPeira, E. (E.)-
dc.creatorMorbelli, S. (S.)-
dc.creatorPardini, M. (M.)-
dc.creatorBauckneht, M. (M.)-
dc.creatorArbizu, J. (Javier)-
dc.creatorCastelo-Branco, M. (M.)-
dc.creatorBüsing, K.A. (K. A.)-
dc.creatorMendonça, A. (A.) de-
dc.creatorDidic, M. (M.)-
dc.creatorDottorini, M. (M.)-
dc.creatorEngelborghs, S. (S.)-
dc.creatorFerrarese, C. (C.)-
dc.creatorFrisoni, G.B. (G. B.)-
dc.creatorGaribotto, V. (V.)-
dc.creatorGuedj, E. (E.)-
dc.creatorHausner, L. (L.)-
dc.creatorHugon, J. (J.)-
dc.creatorVerhaeghe, J. (J.)-
dc.creatorMecocci, P. (P.)-
dc.creatorMusarra, M. (M.)-
dc.creatorQueneau, M. (M.)-
dc.creatorRiverol, M. (Mario)-
dc.creatorSantana, I. (I.)-
dc.creatorGuerra, U.P. (U. P.)-
dc.creatorNobili, F. (F.)-
dc.date.accessioned2022-01-18T09:27:19Z-
dc.date.available2022-01-18T09:27:19Z-
dc.date.issued2019-
dc.identifier.citationChincarini, A. (A.); Peira, E. (E.); Morbelli, S. (S.); et al. "Semi-quantification and grading of amyloid PET: A project of the European Alzheimer's Disease Consortium (EADC)". NeuroImage: Clinical. 23 (2019), 2019, 101846es_ES
dc.identifier.issn2213-1582-
dc.identifier.urihttps://hdl.handle.net/10171/62739-
dc.description.abstractBackground amyloid-PET reading has been classically implemented as a binary assessment, although the clinical experience has shown that the number of borderline cases is non negligible not only in epidemiological studies of asymptomatic subjects but also in naturalistic groups of symptomatic patients attending memory clinics. In this work we develop a model to compare and integrate visual reading with two independent semi-quantification methods in order to obtain a tracer-independent multi-parametric evaluation. Methods We retrospectively enrolled three cohorts of cognitively impaired patients submitted to 18F-florbetaben (53 subjects), 18F-flutemetamol (62 subjects), 18F-florbetapir (60 subjects) PET/CT respectively, in 6 European centres belonging to the EADC. The 175 scans were visually classified as positive/negative following approved criteria and further classified with a 5-step grading as negative, mild negative, borderline, mild positive, positive by 5 independent readers, blind to clinical data. Scan quality was also visually assessed and recorded. Semi-quantification was based on two quantifiers: the standardized uptake value (SUVr) and the ELBA method. We used a sigmoid model to relate the grading with the quantifiers. We measured the readers accord and inconsistencies in the visual assessment as well as the relationship between discrepancies on the grading and semi-quantifications. Conclusion It is possible to construct a map between different tracers and different quantification methods without resorting to ad-hoc acquired cases. We used a 5-level visual scale which, together with a mathematical model, delivered cut-offs and transition regions on tracers that are (largely) independent from the population. All fluorinated tracers appeared to have the same contrast and discrimination ability with respect to the negative-to-positive grading. We validated the integration of both visual reading and different quantifiers in a more robust framework thus bridging the gap between a binary and a user-independent continuous scale.es_ES
dc.description.sponsorshipM.P. receives research support from Novartis and Nutricia and received fees for advisory board participation from Novartis and Merck. V.G. was supported by the Swiss National Science Foundation (under grant SNF 320030_169876) and by the Velux Stiftung (project n. 1123). E.P. was supported by Airalzh Onlus – COOP Italia (grant number 138812/Rep n° 2459).es_ES
dc.language.isoenges_ES
dc.publisherElsevier BVes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectAmyloid PETes_ES
dc.subjectVisual assessmentes_ES
dc.subjectSemi-quantificationes_ES
dc.titleSemi-quantification and grading of amyloid PET: A project of the European Alzheimer's Disease Consortium (EADC)es_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.noteThis is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).es_ES
dc.identifier.doi10.1016/j.nicl.2019.101846-
dadun.citation.number2019es_ES
dadun.citation.publicationNameNeuroImage: Clinicales_ES
dadun.citation.startingPage101846es_ES
dadun.citation.volume23es_ES

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