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Visual assessment of [(18)F]flutemetamol PET images can detect early amyloid pathology and grade its extent

PURPOSE: To investigate the sensitivity of visual read (VR) to detect early amyloid pathology and the overall utility of regional VR. METHODS: [(18)F]Flutemetamol PET images of 497 subjects (ALFA+ N = 352; ADC N = 145) were included. Scans were visually assessed according to product guidelines, reco...

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Autores principales: Collij, Lyduine E., Salvadó, Gemma, Shekari, Mahnaz, Lopes Alves, Isadora, Reimand, Juhan, Wink, Alle Meije, Zwan, Marissa, Niñerola-Baizán, Aida, Perissinotti, Andrés, Scheltens, Philip, Ikonomovic, Milos D., Smith, Adrian P. L., Farrar, Gill, Molinuevo, José Luis, Barkhof, Frederik, Buckley, Christopher J., van Berckel, Bart N. M., Gispert, Juan Domingo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175297/
https://www.ncbi.nlm.nih.gov/pubmed/33615397
http://dx.doi.org/10.1007/s00259-020-05174-2
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author Collij, Lyduine E.
Salvadó, Gemma
Shekari, Mahnaz
Lopes Alves, Isadora
Reimand, Juhan
Wink, Alle Meije
Zwan, Marissa
Niñerola-Baizán, Aida
Perissinotti, Andrés
Scheltens, Philip
Ikonomovic, Milos D.
Smith, Adrian P. L.
Farrar, Gill
Molinuevo, José Luis
Barkhof, Frederik
Buckley, Christopher J.
van Berckel, Bart N. M.
Gispert, Juan Domingo
author_facet Collij, Lyduine E.
Salvadó, Gemma
Shekari, Mahnaz
Lopes Alves, Isadora
Reimand, Juhan
Wink, Alle Meije
Zwan, Marissa
Niñerola-Baizán, Aida
Perissinotti, Andrés
Scheltens, Philip
Ikonomovic, Milos D.
Smith, Adrian P. L.
Farrar, Gill
Molinuevo, José Luis
Barkhof, Frederik
Buckley, Christopher J.
van Berckel, Bart N. M.
Gispert, Juan Domingo
author_sort Collij, Lyduine E.
collection PubMed
description PURPOSE: To investigate the sensitivity of visual read (VR) to detect early amyloid pathology and the overall utility of regional VR. METHODS: [(18)F]Flutemetamol PET images of 497 subjects (ALFA+ N = 352; ADC N = 145) were included. Scans were visually assessed according to product guidelines, recording the number of positive regions (0–5) and a final negative/positive classification. Scans were quantified using the standard and regional Centiloid (CL) method. The agreement between VR-based classification and published CL-based cut-offs for early (CL = 12) and established (CL = 30) pathology was determined. An optimal CL cut-off maximizing Youden’s index was derived. Global and regional CL quantification was compared to VR. Finally, 28 post-mortem cases from the [(18)F]flutemetamol phase III trial were included to assess the percentage agreement between VR and neuropathological classification of neuritic plaque density. RESULTS: VR showed excellent agreement against CL = 12 (κ = .89, 95.2%) and CL = 30 (κ = .88, 95.4%) cut-offs. ROC analysis resulted in an optimal CL = 17 cut-off against VR (sensitivity = 97.9%, specificity = 97.8%). Each additional positive VR region corresponded to a clear increase in global CL. Regional VR was also associated with regional CL quantification. Compared to mCERAD(SOT)-based classification (i.e., any region mCERAD(SOT) > 1.5), VR was in agreement in 89.3% of cases, with 13 true negatives, 12 true positives, and 3 false positives (FP). Regional sparse-to-moderate neuritic and substantial diffuse Aβ plaque was observed in all FP cases. Regional VR was also associated with regional plaque density. CONCLUSION: VR is an appropriate method for assessing early amyloid pathology and that grading the extent of visual amyloid positivity could present clinical value. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-020-05174-2.
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spelling pubmed-81752972021-06-17 Visual assessment of [(18)F]flutemetamol PET images can detect early amyloid pathology and grade its extent Collij, Lyduine E. Salvadó, Gemma Shekari, Mahnaz Lopes Alves, Isadora Reimand, Juhan Wink, Alle Meije Zwan, Marissa Niñerola-Baizán, Aida Perissinotti, Andrés Scheltens, Philip Ikonomovic, Milos D. Smith, Adrian P. L. Farrar, Gill Molinuevo, José Luis Barkhof, Frederik Buckley, Christopher J. van Berckel, Bart N. M. Gispert, Juan Domingo Eur J Nucl Med Mol Imaging Original Article PURPOSE: To investigate the sensitivity of visual read (VR) to detect early amyloid pathology and the overall utility of regional VR. METHODS: [(18)F]Flutemetamol PET images of 497 subjects (ALFA+ N = 352; ADC N = 145) were included. Scans were visually assessed according to product guidelines, recording the number of positive regions (0–5) and a final negative/positive classification. Scans were quantified using the standard and regional Centiloid (CL) method. The agreement between VR-based classification and published CL-based cut-offs for early (CL = 12) and established (CL = 30) pathology was determined. An optimal CL cut-off maximizing Youden’s index was derived. Global and regional CL quantification was compared to VR. Finally, 28 post-mortem cases from the [(18)F]flutemetamol phase III trial were included to assess the percentage agreement between VR and neuropathological classification of neuritic plaque density. RESULTS: VR showed excellent agreement against CL = 12 (κ = .89, 95.2%) and CL = 30 (κ = .88, 95.4%) cut-offs. ROC analysis resulted in an optimal CL = 17 cut-off against VR (sensitivity = 97.9%, specificity = 97.8%). Each additional positive VR region corresponded to a clear increase in global CL. Regional VR was also associated with regional CL quantification. Compared to mCERAD(SOT)-based classification (i.e., any region mCERAD(SOT) > 1.5), VR was in agreement in 89.3% of cases, with 13 true negatives, 12 true positives, and 3 false positives (FP). Regional sparse-to-moderate neuritic and substantial diffuse Aβ plaque was observed in all FP cases. Regional VR was also associated with regional plaque density. CONCLUSION: VR is an appropriate method for assessing early amyloid pathology and that grading the extent of visual amyloid positivity could present clinical value. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-020-05174-2. Springer Berlin Heidelberg 2021-02-22 2021 /pmc/articles/PMC8175297/ /pubmed/33615397 http://dx.doi.org/10.1007/s00259-020-05174-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Collij, Lyduine E.
Salvadó, Gemma
Shekari, Mahnaz
Lopes Alves, Isadora
Reimand, Juhan
Wink, Alle Meije
Zwan, Marissa
Niñerola-Baizán, Aida
Perissinotti, Andrés
Scheltens, Philip
Ikonomovic, Milos D.
Smith, Adrian P. L.
Farrar, Gill
Molinuevo, José Luis
Barkhof, Frederik
Buckley, Christopher J.
van Berckel, Bart N. M.
Gispert, Juan Domingo
Visual assessment of [(18)F]flutemetamol PET images can detect early amyloid pathology and grade its extent
title Visual assessment of [(18)F]flutemetamol PET images can detect early amyloid pathology and grade its extent
title_full Visual assessment of [(18)F]flutemetamol PET images can detect early amyloid pathology and grade its extent
title_fullStr Visual assessment of [(18)F]flutemetamol PET images can detect early amyloid pathology and grade its extent
title_full_unstemmed Visual assessment of [(18)F]flutemetamol PET images can detect early amyloid pathology and grade its extent
title_short Visual assessment of [(18)F]flutemetamol PET images can detect early amyloid pathology and grade its extent
title_sort visual assessment of [(18)f]flutemetamol pet images can detect early amyloid pathology and grade its extent
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175297/
https://www.ncbi.nlm.nih.gov/pubmed/33615397
http://dx.doi.org/10.1007/s00259-020-05174-2
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