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Comparison of Pittsburgh compound B and florbetapir in crossâ sectional and longitudinal studies

dc.contributor.authorSu, Yi
dc.contributor.authorFlores, Shaney
dc.contributor.authorWang, Guoqiao
dc.contributor.authorHornbeck, Russ C.
dc.contributor.authorSpeidel, Benjamin
dc.contributor.authorJoseph‐mathurin, Nelly
dc.contributor.authorVlassenko, Andrei G.
dc.contributor.authorGordon, Brian A.
dc.contributor.authorKoeppe, Robert A.
dc.contributor.authorKlunk, William E.
dc.contributor.authorJack, Clifford R.
dc.contributor.authorFarlow, Martin R.
dc.contributor.authorSalloway, Stephen
dc.contributor.authorSnider, Barbara J.
dc.contributor.authorBerman, Sarah B.
dc.contributor.authorRoberson, Erik D.
dc.contributor.authorBrosch, Jared
dc.contributor.authorJimenez‐velazques, Ivonne
dc.contributor.authorDyck, Christopher H.
dc.contributor.authorGalasko, Douglas
dc.contributor.authorYuan, Shauna H.
dc.contributor.authorJayadev, Suman
dc.contributor.authorHonig, Lawrence S.
dc.contributor.authorGauthier, Serge
dc.contributor.authorHsiung, Ging‐yuek R.
dc.contributor.authorMasellis, Mario
dc.contributor.authorBrooks, William S.
dc.contributor.authorFulham, Michael
dc.contributor.authorClarnette, Roger
dc.contributor.authorMasters, Colin L.
dc.contributor.authorWallon, David
dc.contributor.authorHannequin, Didier
dc.contributor.authorDubois, Bruno
dc.contributor.authorPariente, Jeremie
dc.contributor.authorSanchez‐valle, Raquel
dc.contributor.authorMummery, Catherine
dc.contributor.authorRingman, John M.
dc.contributor.authorBottlaender, Michel
dc.contributor.authorKlein, Gregory
dc.contributor.authorMilosavljevic‐ristic, Smiljana
dc.contributor.authorMcDade, Eric
dc.contributor.authorXiong, Chengjie
dc.contributor.authorMorris, John C.
dc.contributor.authorBateman, Randall J.
dc.contributor.authorBenzinger, Tammie L.S.
dc.date.accessioned2020-01-13T15:16:26Z
dc.date.availableWITHHELD_12_MONTHS
dc.date.available2020-01-13T15:16:26Z
dc.date.issued2019-12
dc.identifier.citationSu, Yi; Flores, Shaney; Wang, Guoqiao; Hornbeck, Russ C.; Speidel, Benjamin; Joseph‐mathurin, Nelly ; Vlassenko, Andrei G.; Gordon, Brian A.; Koeppe, Robert A.; Klunk, William E.; Jack, Clifford R.; Farlow, Martin R.; Salloway, Stephen; Snider, Barbara J.; Berman, Sarah B.; Roberson, Erik D.; Brosch, Jared; Jimenez‐velazques, Ivonne ; Dyck, Christopher H.; Galasko, Douglas; Yuan, Shauna H.; Jayadev, Suman; Honig, Lawrence S.; Gauthier, Serge; Hsiung, Ging‐yuek R. ; Masellis, Mario; Brooks, William S.; Fulham, Michael; Clarnette, Roger; Masters, Colin L.; Wallon, David; Hannequin, Didier; Dubois, Bruno; Pariente, Jeremie; Sanchez‐valle, Raquel ; Mummery, Catherine; Ringman, John M.; Bottlaender, Michel; Klein, Gregory; Milosavljevic‐ristic, Smiljana ; McDade, Eric; Xiong, Chengjie; Morris, John C.; Bateman, Randall J.; Benzinger, Tammie L.S. (2019). "Comparison of Pittsburgh compound B and florbetapir in crossâ sectional and longitudinal studies." Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring 11(C): 180-190.
dc.identifier.issn2352-8729
dc.identifier.issn2352-8729
dc.identifier.urihttps://hdl.handle.net/2027.42/153056
dc.description.abstractIntroductionQuantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound Bâ based and florbetapirâ based amyloid imaging in the same participants from two independent cohorts using a crossover design.MethodsPittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and interâ individual variability of the two tracers were compared using multivariate linear models both crossâ sectionally and longitudinally.ResultsGlobal amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers.DiscussionAlthough the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers.
dc.publisherWiley Periodicals, Inc.
dc.subject.otherPositron emission tomography
dc.subject.otherCentiloid
dc.subject.otherPiB
dc.subject.otherFlorbetapir
dc.subject.otherAmyloid imaging
dc.titleComparison of Pittsburgh compound B and florbetapir in crossâ sectional and longitudinal studies
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelNeurology and Neurosciences
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/153056/1/dad2jdadm201812008.pdf
dc.identifier.doi10.1016/j.dadm.2018.12.008
dc.identifier.sourceAlzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring
dc.identifier.citedreferenceC.C. Rowe, U. Ackerman, W. Browne, R. Mulligan, K.L. Pike, G. O’Keefe, et al. Imaging of amyloid beta in Alzheimer’s disease with 18Fâ BAY94â 9172, a novel PET tracer: proof of mechanism. Lancet Neurol. 7: 2008; 129 â 135
dc.identifier.citedreferenceD.M. Holtzman, J.C. Morris, A.M. Goate. Alzheimer’s Disease: The Challenge of the Second Century. Sci Transl Med. 3: 2011; 77 sr1
dc.identifier.citedreferenceA. Leuzy, K. Chiotis, S.G. Hasselbalch, J.O. Rinne, A. de Mendonca, M. Otto, et al. Pittsburgh compound B imaging and cerebrospinal fluid amyloidâ beta in a multicentre European memory clinic study. Brain. 139: 2016; 2540 â 2553
dc.identifier.citedreferenceD.F. Wong, P.B. Rosenberg, Y. Zhou, A. Kumar, V. Raymont, H.T. Ravert, et al. In vivo imaging of amyloid deposition in Alzheimer disease using the radioligand 18Fâ AVâ 45 (florbetapir [corrected] F 18). J Nucl Med. 51: 2010; 913 â 920
dc.identifier.citedreferenceW.E. Klunk, H. Engler, A. Nordberg, Y. Wang, G. Blomqvist, D.P. Holt, et al. Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compoundâ B. Ann Neurol. 55: 2004; 306 â 319
dc.identifier.citedreferenceV.L. Villemagne, S. Burnham, P. Bourgeat, B. Brown, K.A. Ellis, O. Salvado, et al. Amyloid beta deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease: a prospective cohort study. Lancet Neurol. 12: 2013; 357 â 367
dc.identifier.citedreferenceW.J. Jansen, R. Ossenkoppele, D.L. Knol, B.M. Tijms, P. Scheltens, F.R. Verhey, et al. Prevalence of cerebral amyloid pathology in persons without dementia: a metaâ analysis. JAMA. 313: 2015; 1924 â 1938
dc.identifier.citedreferenceT.L. Benzinger, T. Blazey, C.R. Jack Jr., R.A. Koeppe, Y. Su, C. Xiong, et al. Regional variability of imaging biomarkers in autosomal dominant Alzheimer’s disease. Proc Natl Acad Sci U S A. 110: 2013; E4502 â E4509
dc.identifier.citedreferenceJ.C. Morris, A.L. Price. Pathologic correlates of nondemented aging, mild cognitive impairment, and earlyâ stage Alzheimer’s disease. J Mol Neurosci. 17: 2001; 101 â 118
dc.identifier.citedreferenceC.R. Jack Jr., D.S. Knopman, W.J. Jagust, L.M. Shaw, P.S. Aisen, M.W. Weiner, et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol. 9: 2010; 119 â 128
dc.identifier.citedreferenceR.J. Bateman, C. Xiong, T.L. Benzinger, A.M. Fagan, A. Goate, N.C. Fox, et al. Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N Engl J Med. 367: 2012; 795 â 804
dc.identifier.citedreferenceR. La Joie, N. Ayakta, W.W. Seeley, E. Borys, A.L. Boxer, C. DeCarli, et al. Multisite study of the relationships between antemortem [(11)C]PIBâ PET Centiloid values and postmortem measures of Alzheimer’s disease neuropathology. Alzheimers Dement. 15: 2019; 205 â 216
dc.identifier.citedreferenceV.J. Lowe, E.S. Lundt, M.L. Senjem, C.G. Schwarz, H.K. Min, S.A. Przybelski, et al. White matter reference region in PET studies of (11)Câ Pittsburgh compound B uptake: Effects of age and Amyloidâ beta deposition. J Nucl Med. 59: 2018; 1583 â 1589
dc.identifier.citedreferenceM. Veronese, B. Bodini, D. Garciaâ Lorenzo, M. Battaglini, S. Bongarzone, C. Comtat, et al. Quantification of [(11)C]PIB PET for imaging myelin in the human brain: a testâ retest reproducibility study in highâ resolution research tomography. J Cereb Blood Flow Metab. 35: 2015; 1771 â 1782
dc.identifier.citedreferenceB. Bodini, M. Veronese, F. Turkheimer, B. Stankoff. Benzothiazole and stilbene derivatives as promising positron emission tomography myelin radiotracers for multiple sclerosis. Ann Neurol. 80: 2016; 166 â 167
dc.identifier.citedreferenceS.M. Landau, A. Fero, S.L. Baker, R. Koeppe, M. Mintun, K. Chen, et al. Measurement of Longitudinal betaâ Amyloid Change with 18Fâ Florbetapir PET and Standardized Uptake Value Ratios. J Nucl Med. 56: 2015; 567 â 574
dc.identifier.citedreferenceK. Chen, A. Roontiva, P. Thiyyagura, W. Lee, X. Liu, N. Ayutyanont, et al. Improved power for characterizing longitudinal amyloidâ beta PET changes and evaluating amyloidâ modifying treatments with a cerebral white matter reference region. J Nucl Med. 56: 2015; 560 â 566
dc.identifier.citedreferenceS.M. Landau, C. Breault, A.D. Joshi, M. Pontecorvo, C.A. Mathis, W.J. Jagust, et al. Amyloidâ beta Imaging with Pittsburgh Compound B and Florbetapir: Comparing Radiotracers and Quantification Methods. J Nucl Med. 54: 2013; 70 â 77
dc.identifier.citedreferenceC. Xiong, M.S. Jasielec, H. Weng, A.M. Fagan, T.L. Benzinger, D. Head, et al. Longitudinal relationships among biomarkers for Alzheimer disease in the Adult Children Study. Neurology. 86: 2016; 1499 â 1506
dc.identifier.citedreferenceC.R. Jack Jr., H.J. Wiste, S.D. Weigand, T.M. Therneau, V.J. Lowe, D.S. Knopman, et al. Defining imaging biomarker cut points for brain aging and Alzheimer’s disease. Alzheimers Dement. 13: 2017; 205 â 216
dc.identifier.citedreferenceY. Su, S. Flores, R.C. Hornbeck, B. Speidel, A.G. Vlassenko, B.A. Gordon, et al. Utilizing the Centiloid scale in crossâ sectional and longitudinal PiB PET studies. NeuroImage: Clin. 19: 2018; 406 â 416
dc.identifier.citedreferenceB.A. Gordon, T.M. Blazey, Y. Su, A. Hariâ Raj, A. Dincer, S. Flores, et al. Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer’s disease: a longitudinal study. Lancet Neurol. 17: 2018; 241 â 250
dc.identifier.citedreferenceO.G. Rousset, D.L. Collins, A. Rahmim, D.F. Wong. Design and implementation of an automated partial volume correction in PET: application to dopamine receptor quantification in the normal human striatum. J Nucl Med. 49: 2008; 1097 â 1106
dc.identifier.citedreferenceA. Joshi, R.A. Koeppe, J.A. Fessler. Reducing between scanner differences in multiâ center PET studies. Neuroimage. 46: 2009; 154 â 159
dc.identifier.citedreferenceY. Su, G.M. D’Angelo, A.G. Vlassenko, G. Zhou, A.Z. Snyder, D.S. Marcus, et al. Quantitative analysis of PiBâ PET with FreeSurfer ROIs. PLoS One. 8: 2013; e73377
dc.identifier.citedreferenceY. Su, T.M. Blazey, A.Z. Snyder, M.E. Raichle, D.S. Marcus, B.M. Ances, et al. Partial volume correction in quantitative amyloid imaging. Neuroimage. 107: 2015; 55 â 64
dc.identifier.citedreferenceP. Pastor, C.M. Roe, A. Villegas, G. Bedoya, S. Chakraverty, G. Garcia, et al. Apolipoprotein Eepsilon4 modifies Alzheimer’s disease onset in an E280A PS1 kindred. Ann Neurol. 54: 2003; 163 â 169
dc.identifier.citedreferenceM.F. Folstein, S.E. Folstein, P.R. McHugh. â Miniâ mental stateâ . A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 12: 1975; 189 â 198
dc.identifier.citedreferenceC.L. Sutphen, M.S. Jasielec, A.R. Shah, E.M. Macy, C. Xiong, A.G. Vlassenko, et al. Longitudinal Cerebrospinal Fluid Biomarker Changes in Preclinical Alzheimer Disease During Middle Age. JAMA Neurol. 72: 2015; 1029 â 1042
dc.identifier.citedreferenceA.G. Vlassenko, L. McCue, M.S. Jasielec, Y. Su, B.A. Gordon, C. Xiong, et al. Imaging and cerebrospinal fluid biomarkers in early preclinical alzheimer disease. Ann Neurol. 80: 2016; 379 â 387
dc.identifier.citedreferenceJ.C. Morris. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology. 43: 1993; 2412 â 2414
dc.identifier.citedreferenceS.M. Mills, J. Mallmann, A.M. Santacruz, A. Fuqua, M. Carril, P.S. Aisen, et al. Preclinical trials in autosomal dominant AD: implementation of the DIANâ TU trial. Rev Neurol. 169: 2013; 737 â 743
dc.identifier.citedreferenceM. Navitsky, A.D. Joshi, I. Kennedy, W.E. Klunk, C.C. Rowe, D.F. Wong, et al. Standardization of amyloid quantitation with florbetapir standardized uptake value ratios to the Centiloid scale. Alzheimers Dement. 14: 2018; 1565 â 1571
dc.identifier.citedreferenceC.C. Rowe, V. Dore, G. Jones, D. Baxendale, R.S. Mulligan, S. Bullich, et al. (18)Fâ Florbetaben PET betaâ amyloid binding expressed in Centiloids. Eur J Nucl Med Mol Imaging. 44: 2017; 2053 â 2059
dc.identifier.citedreferenceC.C. Rowe, G. Jones, V. Dore, S. Pejoska, L. Margison, R.S. Mulligan, et al. Standardized Expression of 18Fâ NAV4694 and 11Câ PiB betaâ Amyloid PET Results with the Centiloid Scale. J Nucl Med. 57: 2016; 1233 â 1237
dc.identifier.citedreferenceW.E. Klunk, R.A. Koeppe, J.C. Price, T.L. Benzinger, M.D. Devous Sr., et al. The Centiloid Project: standardizing quantitative amyloid plaque estimation by PET. Alzheimers Dement. 11: 2015; 1 â 15, e1â e4
dc.identifier.citedreferenceZ. Cselenyi, M.E. Jonhagen, A. Forsberg, C. Halldin, P. Julin, M. Schou, et al. Clinical validation of 18Fâ AZD4694, an amyloidâ betaâ specific PET radioligand. J Nucl Med. 53: 2012; 415 â 424
dc.identifier.citedreferenceR. Vandenberghe, K. Van Laere, A. Ivanoiu, E. Salmon, C. Bastin, E. Triau, et al. 18Fâ flutemetamol amyloid imaging in Alzheimer disease and mild cognitive impairment: a phase 2 trial. Ann Neurol. 68: 2010; 319 â 329
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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