Quantitative Amyloid Imaging in Autosomal Dominant Alzheimer’s Disease: Results from the DIAN Study Group

PLOS ONE, Dec 2019

Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer’s Network (DIAN), an autosomal dominant Alzheimer’s disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer’s disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid imaging in different study populations using different amyloid imaging tracers is warranted.

A PDF file should load here. If you do not see its contents the file may be temporarily unavailable at the journal website or you do not have a PDF plug-in installed and enabled in your browser.

Alternatively, you can download the file locally and open with any standalone PDF reader:

https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0152082&type=printable

Quantitative Amyloid Imaging in Autosomal Dominant Alzheimer’s Disease: Results from the DIAN Study Group

March Quantitative Amyloid Imaging in Autosomal Dominant Alzheimer's Disease: Results from the DIAN Study Group Yi Su 0 1 2 Tyler M. Blazey 0 1 2 Christopher J. Owen 0 1 2 Jon J. Christensen 0 1 2 Karl Friedrichsen 0 1 2 Nelly Joseph-Mathurin 0 1 2 Qing Wang 0 1 2 Russ C. Hornbeck 0 1 2 Beau M. Ances 0 2 Abraham Z. Snyder 0 1 2 Lisa A. Cash 0 1 2 Robert A. Koeppe 0 2 William E. Klunk 0 2 Douglas Galasko 0 2 Adam M. Brickman 0 2 Eric McDade 0 2 John M. Ringman 0 2 Paul M. Thompson 0 2 Andrew J. Saykin 0 2 5 Bernardino Ghetti 0 2 5 Reisa A. Sperling 0 2 Keith A. Johnson 0 2 Stephen P. Salloway 0 2 Peter R. Schofield 0 2 6 Colin L. Masters 0 2 Victor L. Villemagne 0 2 Nick C. Fox 0 2 Stefan Förster 0 2 4 Kewei Chen 0 2 Eric M. Reiman 0 2 Chengjie Xiong 0 2 Daniel S. Marcus 0 1 2 Michael W. Weiner 0 2 3 John C. Morris 0 2 Randall J. Bateman 0 2 Tammie L. S. Benzinger 0 1 2 Dominantly Inherited Alzheimer Network 0 2 0 Alzheimer's Disease Research Center ( 1 0 Massachusetts General Hospital, Harvard Medical School , Boston , Massachusetts, United States of America, 11 Butler Hospital and Brown University , Providence, Rhode Island , United States of America 2 Editor: Karl Herholz, University of Manchester , UNITED KINGDOM 3 Department of Radiology, University of California San Francisco , San Francisco, California , United States of America 4 Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) München/Tübingen and Dept. of Nuclear Medicine, Technische Universität München , München, Germany , 16 Banner Alzheimer's Institute, Banner Health , 901 E. Willetta Street, Phoenix , Arizona, United States of America, 17 Division of Biostatistics, Washington University School of Medicine , Saint Louis, Missouri , United States of America 5 Department of Radiology, Indiana University , Indianapolis, Indiana , United States of America 6 Neuroscience Research Australia and School of Medical Sciences, University of New South Wales , Sydney, New South Wales , Australia , 13 The Florey Institute and the University of Melbourne , Parkville, Victoria , Australia , 14 Dememtia Research Centre, Institute of Neurology , London , Great Britain Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to - OPEN ACCESS Data Availability Statement: In accordance with policies put in place by the DIAN Steering Committee, patient and imaging data are available upon request. The full policy regarding data access as well as instructions for submitting requests for data access are available here: http://www.dian-info.org/ resourcedb/default.htm. the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer’s Network (DIAN), an autosomal dominant Alzheimer’s disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the by the Clinical and Translational Science Award (CTSA) program (https://www.ctsacentral.org/) of National Institute of Health (http://www.nih.gov/): UL1TR000448. AZS and DSM received funds from National Institute of Neurological Disorders and Stroke (http://www.ninds.nih.gov/): P30NS048056; JCM and TLSB received funds from National Institute of Ageing (http://www.nia.nih.gov/): P01AG026276, U19AG032438, P50AG005681, P01AG003991. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer’s disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid ima (...truncated)


This is a preview of a remote PDF: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0152082&type=printable

Yi Su, Tyler M. Blazey, Christopher J. Owen, Jon J. Christensen, Karl Friedrichsen, Nelly Joseph-Mathurin, Qing Wang, Russ C. Hornbeck, Beau M. Ances, Abraham Z. Snyder, Lisa A. Cash, Robert A. Koeppe, William E. Klunk, Douglas Galasko, Adam M. Brickman, Eric McDade, John M. Ringman, Paul M. Thompson, Andrew J. Saykin, Bernardino Ghetti, Reisa A. Sperling, Keith A. Johnson, Stephen P. Salloway, Peter R. Schofield, Colin L. Masters, Victor L. Villemagne, Nick C. Fox, Stefan Förster, Kewei Chen, Eric M. Reiman, Chengjie Xiong, Daniel S. Marcus, Michael W. Weiner, John C. Morris, Randall J. Bateman, Tammie L. S. Benzinger, Dominantly Inherited Alzheimer Network. Quantitative Amyloid Imaging in Autosomal Dominant Alzheimer’s Disease: Results from the DIAN Study Group, PLOS ONE, 2016, Volume 11, Issue 3, DOI: 10.1371/journal.pone.0152082