Show simple item record

Utility of perfusion PET measures to assess neuronal injury in Alzheimer’s disease

dc.contributor.authorJoseph‐mathurin, Nelly
dc.contributor.authorSu, Yi
dc.contributor.authorBlazey, Tyler M.
dc.contributor.authorJasielec, Mateusz
dc.contributor.authorVlassenko, Andrei
dc.contributor.authorFriedrichsen, Karl
dc.contributor.authorGordon, Brian A.
dc.contributor.authorHornbeck, Russ C.
dc.contributor.authorCash, Lisa
dc.contributor.authorAnces, Beau M.
dc.contributor.authorVeale, Thomas
dc.contributor.authorCash, David M.
dc.contributor.authorBrickman, Adam M.
dc.contributor.authorBuckles, Virginia
dc.contributor.authorCairns, Nigel J.
dc.contributor.authorCruchaga, Carlos
dc.contributor.authorGoate, Alison
dc.contributor.authorJack, Clifford R.
dc.contributor.authorKarch, Celeste
dc.contributor.authorKlunk, William
dc.contributor.authorKoeppe, Robert A.
dc.contributor.authorMarcus, Daniel S.
dc.contributor.authorMayeux, Richard
dc.contributor.authorMcDade, Eric
dc.contributor.authorNoble, James M.
dc.contributor.authorRingman, John
dc.contributor.authorSaykin, Andrew J.
dc.contributor.authorThompson, Paul M.
dc.contributor.authorXiong, Chengjie
dc.contributor.authorMorris, John C.
dc.contributor.authorBateman, Randall J.
dc.contributor.authorBenzinger, Tammie L.S.
dc.date.accessioned2020-01-13T15:21:49Z
dc.date.available2020-01-13T15:21:49Z
dc.date.issued2018
dc.identifier.citationJoseph‐mathurin, Nelly ; Su, Yi; Blazey, Tyler M.; Jasielec, Mateusz; Vlassenko, Andrei; Friedrichsen, Karl; Gordon, Brian A.; Hornbeck, Russ C.; Cash, Lisa; Ances, Beau M.; Veale, Thomas; Cash, David M.; Brickman, Adam M.; Buckles, Virginia; Cairns, Nigel J.; Cruchaga, Carlos; Goate, Alison; Jack, Clifford R.; Karch, Celeste; Klunk, William; Koeppe, Robert A.; Marcus, Daniel S.; Mayeux, Richard; McDade, Eric; Noble, James M.; Ringman, John; Saykin, Andrew J.; Thompson, Paul M.; Xiong, Chengjie; Morris, John C.; Bateman, Randall J.; Benzinger, Tammie L.S. (2018). "Utility of perfusion PET measures to assess neuronal injury in Alzheimer’s disease." Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring 10(C): 669-677.
dc.identifier.issn2352-8729
dc.identifier.issn2352-8729
dc.identifier.urihttps://hdl.handle.net/2027.42/153272
dc.description.abstractIntroduction18Fâ fluorodeoxyglucose (FDG) positron emission tomography (PET) is commonly used to estimate neuronal injury in Alzheimer’s disease (AD). Here, we evaluate the utility of dynamic PET measures of perfusion using 11Câ Pittsburgh compound B (PiB) to estimate neuronal injury in comparison to FDG PET.MethodsFDG, early frames of PiB images, and relative PiB delivery rate constants (PiBâ R1) were obtained from 110 participants from the Dominantly Inherited Alzheimer Network. Voxelwise, regional crossâ sectional, and longitudinal analyses were done to evaluate the correlation between images and estimate the relationship of the imaging biomarkers with estimated time to disease progression based on family history.ResultsMetabolism and perfusion images were spatially correlated. Regional PiBâ R1 values and FDG, but not early frames of PiB images, significantly decreased in the mutation carriers with estimated year to onset and with increasing dementia severity.DiscussionHypometabolism estimated by PiBâ R1 may provide a measure of brain perfusion without increasing radiation exposure.
dc.publisherWiley Periodicals, Inc.
dc.subject.otherPiB
dc.subject.otherNeuronal injury
dc.subject.otherAlzheimer’s disease
dc.subject.otherFDG
dc.subject.otherPerfusion
dc.titleUtility of perfusion PET measures to assess neuronal injury in Alzheimer’s disease
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/2027.42/153272/1/dad2jdadm201808012.pdf
dc.identifier.doi10.1016/j.dadm.2018.08.012
dc.identifier.sourceAlzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring
dc.identifier.citedreferenceR.S. Frackowiak, G.L. Lenzi, T. Jones, J.D. Heather. Quantitative measurement of regional cerebral blood flow and oxygen metabolism in man using 15O and positron emission tomography: Theory, procedure, and normal values. J Comput Assist Tomogr. 4: 1980; 727 â 736
dc.identifier.citedreferenceJ.C. Morris, P.S. Aisen, R.J. Bateman, T.L. Benzinger, N.J. Cairns, A.M. Fagan, et al. Developing an international network for Alzheimer research: The Dominantly Inherited Alzheimer Network. Clin Investig. 2: 2012; 975 â 984
dc.identifier.citedreferenceK.J. Lin, I.T. Hsiao, J.L. Hsu, C.C. Huang, K.L. Huang, C.J. Hsieh, et al. Imaging characteristic of dualâ phase (18)Fâ florbetapir (AVâ 45/Amyvid) PET for the concomitant detection of perfusion deficits and betaâ amyloid deposition in Alzheimer’s disease and mild cognitive impairment. Eur J Nucl Med Mol Imaging. 43: 2016; 1304 â 1314
dc.identifier.citedreferenceC.R. Jack Jr., D.S. Knopman, W.J. Jagust, R.C. Petersen, M.W. Weiner, P.S. Aisen, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 12: 2013; 207 â 216
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.citedreferenceA.M. Fagan, D.M. Holtzman. Cerebrospinal fluid biomarkers of Alzheimer’s disease. Biomark Med. 4: 2010; 51 â 63
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.citedreferenceC.C. Rowe, S. Ng, U. Ackermann, S.J. Gong, K. Pike, G. Savage, et al. Imaging betaâ amyloid burden in aging and dementia. Neurology. 68: 2007; 1718 â 1725
dc.identifier.citedreferenceL. Mosconi, V. Berti, L. Glodzik, A. Pupi, S. De Santi, M.J. de Leon. Preâ clinical detection of Alzheimer’s disease using FDGâ PET, with or without amyloid imaging. J Alzheimers Dis. 20: 2010; 843 â 854
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.citedreferenceA. Forsberg, H. Engler, G. Blomquist, B. Langstrom, A. Nordberg. The use of PIBâ PET as a dual pathological and functional biomarker in AD. Biochim Biophys Acta. 1822: 2012; 380 â 385
dc.identifier.citedreferenceP.T. Meyer, S. Hellwig, F. Amtage, C. Rottenburger, U. Sahm, P. Reuland, et al. Dualâ biomarker imaging of regional cerebral amyloid load and neuronal activity in dementia with PET and 11Câ labeled Pittsburgh compound B. J Nucl Med. 52: 2011; 393 â 400
dc.identifier.citedreferenceA.H. Rostomian, C. Madison, G.D. Rabinovici, W.J. Jagust. Early 11Câ PIB frames and 18Fâ FDG PET measures are comparable: A study validated in a cohort of AD and FTLD patients. J Nucl Med. 52: 2011; 173 â 179
dc.identifier.citedreferenceS. Tiepolt, S. Hesse, M. Patt, J. Luthardt, M.L. Schroeter, K.T. Hoffmann, et al. Early [(18)F]florbetaben and [(11)C]PiB PET images are a surrogate biomarker of neuronal injury in Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 43: 2016; 1700 â 1709
dc.identifier.citedreferenceL. Fu, L. Liu, J. Zhang, B. Xu, Y. Fan, J. Tian. Comparison of dualâ biomarker PIBâ PET and dualâ tracer PET in AD diagnosis. Eur Radiol. 24: 2014; 2800 â 2809
dc.identifier.citedreferenceM.E. Raichle, W.R. Martin, P. Herscovitch, M.A. Mintun, J. Markham. Brain blood flow measured with intravenous H2(15)O. II. Implementation and validation. J Nucl Med. 24: 1983; 790 â 798
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.citedreferenceY.J. Chen, B.L. Rosario, W. Mowrey, C.M. Laymon, X. Lu, O.L. Lopez, et al. Relative 11Câ PiB Delivery as a Proxy of Relative CBF: Quantitative Evaluation Using Singleâ Session 15Oâ Water and 11Câ PiB PET. J Nucl Med. 56: 2015; 1199 â 1205
dc.identifier.citedreferenceG. Blomquist, H. Engler, A. Nordberg, A. Ringheim, A. Wall, A. Forsberg, et al. Unidirectional Influx and Net Accumulation of PIB. Open Neuroimag J. 2: 2008; 114 â 125
dc.identifier.citedreferenceE. Rodriguezâ Vieitez, A. Leuzy, K. Chiotis, L. Saintâ Aubert, A. Wall, A. Nordberg. Comparability of [18F]THK5317 and [11C]PIB blood flow proxy images with [18F]FDG positron emission tomography in Alzheimer’s disease. J Cereb Blood flow Metab. 37: 2016; 740 â 749
dc.identifier.citedreferenceL. Liu, L. Fu, X. Zhang, J. Zhang, X. Zhang, B. Xu, et al. Combination of dynamic (11)Câ PIB PET and structural MRI improves diagnosis of Alzheimer’s disease. Psychiatry Res. 233: 2015; 131 â 140
dc.identifier.citedreferenceK. Farid, Y.T. Hong, F.I. Aigbirhio, T.D. Fryer, D.K. Menon, E.A. Warburton, et al. Earlyâ Phase 11Câ PiB PET in amyloid angiopathyâ related symptomatic cerebral hemorrhage: Potential diagnostic value?. PLoS One. 10: 2015; e0139926
dc.identifier.citedreferenceA.F. Gietl, G. Warnock, F. Riese, A.M. Kalin, A. Saake, E. Gruber, et al. Regional cerebral blood flow estimated by early PiB uptake is reduced in mild cognitive impairment and associated with age in an amyloidâ dependent manner. Neurobiol Aging. 36: 2015; 1619 â 1628
dc.identifier.citedreferenceR.J. Bateman, P.S. Aisen, B. De Strooper, N.C. Fox, C.A. Lemere, J.M. Ringman, et al. Autosomalâ dominant Alzheimer’s disease: A review and proposal for the prevention of Alzheimer’s disease. Alzheimers Res Ther. 3: 2011; 1
dc.identifier.citedreferenceH.C. Kuo, I.T. Hsiao, C.J. Hsieh, C.Y. Huang, K.L. Huang, Y.Y. Wai, et al. Dualâ phase 18Fâ florbetapir positron emission tomography in patients with primary progressive aphasia, Alzheimer’s disease, and healthy controls: A preliminary study. J Formos Med Assoc. 116: 2017; 964 â 972
dc.identifier.citedreferenceS. Daerr, M. Brendel, C. Zach, E. Mille, D. Schilling, M.J. Zacherl, et al. Evaluation of earlyâ phase [18F]â florbetaben PET acquisition in clinical routine cases. NeuroImage Clin. 14: 2017; 77 â 86
dc.identifier.citedreferenceI.T. Hsiao, C.C. Huang, C.J. Hsieh, W.C. Hsu, S.P. Wey, T.C. Yen, et al. Correlation of earlyâ phase 18Fâ florbetapir (AVâ 45/Amyvid) PET images to FDG images: preliminary studies. Eur J Nucl Med Mol Imaging. 39: 2012; 613 â 620
dc.identifier.citedreferenceR.C. Gur, J.D. Ragland, M. Reivich, J.H. Greenberg, A. Alavi, R.E. Gur. Regional differences in the coupling between resting cerebral blood flow and metabolism may indicate action preparedness as a default state. Cereb Cortex. 19: 2009; 375 â 382
dc.identifier.citedreferenceO.B. Paulson, S.G. Hasselbalch, E. Rostrup, G.M. Knudsen, D. Pelligrino. Cerebral blood flow response to functional activation. J Cereb Blood flow Metab. 30: 2010; 2 â 14
dc.identifier.citedreferenceD.N. Greve, D.H. Salat, S.L. Bowen, D. Izquierdoâ Garcia, A.P. Schultz, C. Catana, et al. Different partial volume correction methods lead to different conclusions: An (18)Fâ FDGâ PET study of aging. NeuroImage. 132: 2016; 334 â 343
dc.identifier.citedreferenceB.A. Thomas, K. Erlandsson, M. Modat, L. Thurfjell, R. Vandenberghe, S. Ourselin, et al. The importance of appropriate partial volume correction for PET quantification in Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 38: 2011; 1104 â 1119
dc.identifier.citedreferenceM. Brendel, M. Hogenauer, A. Delker, J. Sauerbeck, P. Bartenstein, J. Seibyl, et al. Improved longitudinal [(18)F]â AV45 amyloid PET by white matter reference and VOIâ based partial volume effect correction. NeuroImage. 108: 2015; 450 â 459
dc.identifier.citedreferenceD.M. Cash, G.R. Ridgway, Y. Liang, N.S. Ryan, K.M. Kinnunen, T. Yeatman, et al. The pattern of atrophy in familial Alzheimer disease: Volumetric MRI results from the DIAN study. Neurology. 81: 2013; 1425 â 1433
dc.identifier.citedreferenceC.C. Meltzer, J.K. Zubieta, J. Brandt, L.E. Tune, H.S. Mayberg, J.J. Frost. Regional hypometabolism in Alzheimer’s disease as measured by positron emission tomography after correction for effects of partial volume averaging. Neurology. 47: 1996; 454 â 461
dc.identifier.citedreferenceV. Ibanez, P. Pietrini, G.E. Alexander, M.L. Furey, D. Teichberg, J.C. Rajapakse, et al. Regional glucose metabolic abnormalities are not the result of atrophy in Alzheimer’s disease. Neurology. 50: 1998; 1585 â 1593
dc.identifier.citedreferenceF.E. Satterthwaite. An approximate distribution of estimates of variance components. Biometrics. 2: 1946; 110 â 114
dc.identifier.citedreferenceD. Rindskopf. An introduction to the bootstrap. Efron B, Tibshirani RJ, eds. J Educ Behav Stat.. 22: 1997; 245
dc.identifier.citedreferenceJ. Ashburner, K.J. Friston. Diffeomorphic registration using geodesic shooting and Gaussâ Newton optimisation. NeuroImage. 55: 2011; 954 â 967
dc.identifier.citedreferenceJ. Ashburner, K.J. Friston. Unified segmentation. NeuroImage. 26: 2005; 839 â 851
dc.identifier.citedreferenceB.J. Lopresti, W.E. Klunk, C.A. Mathis, J.A. Hoge, S.K. Ziolko, X. Lu, et al. Simplified quantification of Pittsburgh Compound B amyloid imaging PET studies: A comparative analysis. J Nucl Med. 46: 2005; 1959 â 1972
dc.identifier.citedreferenceA.A. Lammertsma, S.P. Hume. Simplified reference tissue model for PET receptor studies. NeuroImage. 4: 1996; 153 â 158
dc.identifier.citedreferenceS.N. Vaishnavi, A.G. Vlassenko, M.M. Rundle, A.Z. Snyder, M.A. Mintun, M.E. Raichle. Regional aerobic glycolysis in the human brain. Proc Natl Acad Sci U S A. 107: 2010; 17757 â 17762
dc.identifier.citedreferenceJ.C. Morris, C.M. Roe, C. Xiong, A.M. Fagan, A.M. Goate, D.M. Holtzman, et al. APOE predicts amyloidâ beta but not tau Alzheimer pathology in cognitively normal aging. Ann Neurol. 67: 2010; 122 â 131
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.citedreferenceJ.C. Morris. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology. 43: 1993; 2412 â 2414
dc.identifier.citedreferenceL. Berg, J.P. Miller, M. Storandt, J. Duchek, J.C. Morris, E.H. Rubin, et al. Mild senile dementia of the Alzheimer type: 2. Longitudinal assessment. Ann Neurol. 23: 1988; 477 â 484
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.