Literature DB >> 25745095

Measurement of longitudinal β-amyloid change with 18F-florbetapir PET and standardized uptake value ratios.

Susan M Landau1, Allison Fero2, Suzanne L Baker2, Robert Koeppe3, Mark Mintun4, Kewei Chen5, Eric M Reiman5, William J Jagust6.   

Abstract

UNLABELLED: The accurate measurement of β-amyloid (Aβ) change using amyloid PET imaging is important for Alzheimer disease research and clinical trials but poses several unique challenges. In particular, reference region measurement instability may lead to spurious changes in cortical regions of interest. To optimize our ability to measure (18)F-florbetapir longitudinal change, we evaluated several candidate regions of interest and their influence on cortical florbetapir change over a 2-y period in participants from the Alzheimer Disease Neuroimaging Initiative (ADNI).
METHODS: We examined the agreement in cortical florbetapir change detected using 6 candidate reference regions (cerebellar gray matter, whole cerebellum, brain stem/pons, eroded subcortical white matter [WM], and 2 additional combinations of these regions) in 520 ADNI subjects. We used concurrent cerebrospinal fluid Aβ1-42 measurements to identify subgroups of ADNI subjects expected to remain stable over follow-up (stable Aβ group; n = 14) and subjects expected to increase (increasing Aβ group; n = 91). We then evaluated reference regions according to whether cortical change was minimal in the stable Aβ group and cortical retention increased in the increasing Aβ group.
RESULTS: There was poor agreement across reference regions in the amount of cortical change observed across all 520 ADNI subjects. Within the stable Aβ group, however, cortical florbetapir change was 1%-2% across all reference regions, indicating high consistency. In the increasing Aβ group, cortical increases were significant with all reference regions. Reference regions containing WM (as opposed to cerebellum or pons) enabled detection of cortical change that was more physiologically plausible and more likely to increase over time.
CONCLUSION: Reference region selection has an important influence on the detection of florbetapir change. Compared with cerebellum or pons alone, reference regions that included subcortical WM resulted in change measurements that are more accurate. In addition, because use of WM-containing reference regions involves dividing out cortical signal contained in the reference region (via partial-volume effects), use of these WM-containing regions may result in more conservative estimates of actual change. Future analyses using different tracers, tracer-kinetic models, pipelines, and comparisons with other biomarkers will further optimize our ability to accurately measure Aβ changes over time.
© 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Entities:  

Keywords:  Alzheimer’s disease; PET imaging; amyloid

Mesh:

Substances:

Year:  2015        PMID: 25745095      PMCID: PMC5313473          DOI: 10.2967/jnumed.114.148981

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  24 in total

1.  Amyloid-beta plaque growth in cognitively normal adults: longitudinal [11C]Pittsburgh compound B data.

Authors:  Andrei G Vlassenko; Mark A Mintun; Chengjie Xiong; Yvette I Sheline; Alison M Goate; Tammie L S Benzinger; John C Morris
Journal:  Ann Neurol       Date:  2011-11       Impact factor: 10.422

2.  Association of lifetime cognitive engagement and low β-amyloid deposition.

Authors:  Susan M Landau; Shawn M Marks; Elizabeth C Mormino; Gil D Rabinovici; Hwamee Oh; James P O'Neil; Robert S Wilson; William J Jagust
Journal:  Arch Neurol       Date:  2012-05

3.  Simplified quantification of Pittsburgh Compound B amyloid imaging PET studies: a comparative analysis.

Authors:  Brian J Lopresti; William E Klunk; Chester A Mathis; Jessica A Hoge; Scott K Ziolko; Xueling Lu; Carolyn C Meltzer; Kurt Schimmel; Nicholas D Tsopelas; Steven T DeKosky; Julie C Price
Journal:  J Nucl Med       Date:  2005-12       Impact factor: 10.057

4.  Amyloid-β imaging with Pittsburgh compound B and florbetapir: comparing radiotracers and quantification methods.

Authors:  Susan M Landau; Christopher Breault; Abhinay D Joshi; Michael Pontecorvo; Chester A Mathis; William J Jagust; Mark A Mintun
Journal:  J Nucl Med       Date:  2012-11-19       Impact factor: 10.057

5.  Optimizing regions-of-interest composites for capturing treatment effects on brain amyloid in clinical trials.

Authors:  Volha Tryputsen; Allitia DiBernardo; Mahesh Samtani; Gerald P Novak; Vaibhav A Narayan; Nandini Raghavan
Journal:  J Alzheimers Dis       Date:  2015       Impact factor: 4.472

6.  18F-flutemetamol amyloid imaging in Alzheimer disease and mild cognitive impairment: a phase 2 trial.

Authors:  Rik Vandenberghe; Koen Van Laere; Adrian Ivanoiu; Eric Salmon; Christine Bastin; Eric Triau; Steen Hasselbalch; Ian Law; Allan Andersen; Alex Korner; Lennart Minthon; Gaëtan Garraux; Natalie Nelissen; Guy Bormans; Chris Buckley; Rikard Owenius; Lennart Thurfjell; Gill Farrar; David J Brooks
Journal:  Ann Neurol       Date:  2010-09       Impact factor: 10.422

7.  Comparison of 11C-PiB and 18F-florbetaben for Aβ imaging in ageing and Alzheimer's disease.

Authors:  Victor L Villemagne; Rachel S Mulligan; Svetlana Pejoska; Kevin Ong; Gareth Jones; Graeme O'Keefe; J Gordon Chan; Kenneth Young; Henri Tochon-Danguy; Colin L Masters; Christopher C Rowe
Journal:  Eur J Nucl Med Mol Imaging       Date:  2012-03-08       Impact factor: 9.236

8.  Performance characteristics of amyloid PET with florbetapir F 18 in patients with alzheimer's disease and cognitively normal subjects.

Authors:  Abhinay D Joshi; Michael J Pontecorvo; Chrisopher M Clark; Alan P Carpenter; Danna L Jennings; Carl H Sadowsky; Lee P Adler; Karel D Kovnat; John P Seibyl; Anupa Arora; Krishnendu Saha; Jason D Burns; Mark J Lowrey; Mark A Mintun; Daniel M Skovronsky
Journal:  J Nucl Med       Date:  2012-02-13       Impact factor: 10.057

9.  Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects.

Authors:  Leslie M Shaw; Hugo Vanderstichele; Malgorzata Knapik-Czajka; Christopher M Clark; Paul S Aisen; Ronald C Petersen; Kaj Blennow; Holly Soares; Adam Simon; Piotr Lewczuk; Robert Dean; Eric Siemers; William Potter; Virginia M-Y Lee; John Q Trojanowski
Journal:  Ann Neurol       Date:  2009-04       Impact factor: 10.422

10.  Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study.

Authors:  Victor L Villemagne; Samantha Burnham; Pierrick Bourgeat; Belinda Brown; Kathryn A Ellis; Olivier Salvado; Cassandra Szoeke; S Lance Macaulay; Ralph Martins; Paul Maruff; David Ames; Christopher C Rowe; Colin L Masters
Journal:  Lancet Neurol       Date:  2013-03-08       Impact factor: 44.182

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  118 in total

1.  Long-term Changes in 18F-Flutemetamol Uptake in Nondemented Older Adults.

Authors:  Kevin Duff; Kevin P Horn; John M Hoffman
Journal:  Alzheimer Dis Assoc Disord       Date:  2019 Apr-Jun       Impact factor: 2.703

2.  Quantitative molecular imaging of cardiac amyloidosis: The journey has begun.

Authors:  Sharmila Dorbala; Marie Foley Kijewski; Mi-Ae Park
Journal:  J Nucl Cardiol       Date:  2015-07-16       Impact factor: 5.952

3.  A Fully Automatic Technique for Precise Localization and Quantification of Amyloid-β PET Scans.

Authors:  Mouna Tahmi; Wassim Bou-Zeid; Qolamreza R Razlighi
Journal:  J Nucl Med       Date:  2019-06-06       Impact factor: 10.057

4.  Reciprocal Predictive Relationships between Amyloid and Tau Biomarkers in Alzheimer's Disease Progression: An Empirical Model.

Authors:  Saffire H Krance; Hugo Cogo-Moreira; Jennifer S Rabin; Sandra E Black; Walter Swardfager
Journal:  J Neurosci       Date:  2019-07-26       Impact factor: 6.167

5.  Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER) Methodology for Research and Clinical Brain PET Applications.

Authors:  Fabio Raman; Sameera Grandhi; Charles F Murchison; Richard E Kennedy; Susan Landau; Erik D Roberson; Jonathan McConathy
Journal:  J Alzheimers Dis       Date:  2019       Impact factor: 4.472

6.  Amyloid Load: A More Sensitive Biomarker for Amyloid Imaging.

Authors:  Alex Whittington; Roger N Gunn
Journal:  J Nucl Med       Date:  2018-09-06       Impact factor: 10.057

Review 7.  Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials.

Authors:  Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; John C Morris; Ronald C Petersen; Andrew J Saykin; Leslie M Shaw; Arthur W Toga; John Q Trojanowski
Journal:  Alzheimers Dement       Date:  2017-03-22       Impact factor: 21.566

8.  Randomized Trial of Verubecestat for Prodromal Alzheimer's Disease.

Authors:  Michael F Egan; James Kost; Tiffini Voss; Yuki Mukai; Paul S Aisen; Jeffrey L Cummings; Pierre N Tariot; Bruno Vellas; Christopher H van Dyck; Merce Boada; Ying Zhang; Wen Li; Christine Furtek; Erin Mahoney; Lyn Harper Mozley; Yi Mo; Cyrille Sur; David Michelson
Journal:  N Engl J Med       Date:  2019-04-11       Impact factor: 91.245

9.  Aβ-related hyperactivation in frontoparietal control regions in cognitively normal elderly.

Authors:  Hwamee Oh; Jason Steffener; Qolamreza R Razlighi; Christian Habeck; Dan Liu; Yunglin Gazes; Sarah Janicki; Yaakov Stern
Journal:  Neurobiol Aging       Date:  2015-08-24       Impact factor: 4.673

10.  Nonlinear Distributional Mapping (NoDiM) for harmonization across amyloid-PET radiotracers.

Authors:  Michael J Properzi; Rachel F Buckley; Jasmeer P Chhatwal; Michael C Donohue; Cristina Lois; Elizabeth C Mormino; Keith A Johnson; Reisa A Sperling; Aaron P Schultz
Journal:  Neuroimage       Date:  2018-11-17       Impact factor: 6.556

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