Skip to main content

Advertisement

SpringerLink
Log in

Individualized quantification of brain β-amyloid burden: results of a proof of mechanism phase 0 florbetaben PET trial in patients with Alzheimer’s disease and healthy controls

  • Original Article
  • Published:
European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

Complementing clinical findings with those generated by biomarkers—such as β-amyloid-targeted positron emission tomography (PET) imaging—has been proposed as a means of increasing overall accuracy in the diagnosis of Alzheimer’s disease (AD). Florbetaben ([18F]BAY 94-9172) is a novel β-amyloid PET tracer currently in global clinical development. We present the results of a proof of mechanism study in which the diagnostic efficacy, pharmacokinetics, safety and tolerability of florbetaben were assessed. The value of various quantitative parameters derived from the PET scans as potential surrogate markers of cognitive decline was also investigated.

Methods

Ten patients with mild-moderate probable AD (DSM-IV and NINCDS-ADRDA criteria) and ten age-matched (≥ 55 years) healthy controls (HCs) were administered a single dose of 300 MBq florbetaben, which contained a tracer mass dose of < 5 μg. The 70–90 min post-injection brain PET data were visually analysed by three blinded experts. Quantitative assessment was also performed via MRI-based, anatomical sampling of predefined volumes of interest (VOI) and subsequent calculation of standardized uptake value (SUV) ratios (SUVRs, cerebellar cortex as reference region). Furthermore, single-case, voxelwise analysis was used to calculate individual “whole brain β-amyloid load”.

Results

Visual analysis of the PET data revealed nine of the ten AD, but only one of the ten HC brains to be β-amyloid positive (p = 0.001), with high inter-reader agreement (weighted kappa ≥ 0.88). When compared to HCs, the neocortical SUVRs were significantly higher in the ADs (with descending order of effect size) in frontal cortex, lateral temporal cortex, occipital cortex, anterior and posterior cingulate cortices, and parietal cortex (p = 0.003–0.010). Voxel-based group comparison confirmed these differences. Amongst the PET-derived parameters, the Statistical Parametric Mapping-based whole brain β-amyloid load yielded the closest correlation with the Mini-Mental State Examination scores (r = −0.736, p < 0.001), following a nonlinear regression curve. No serious adverse events or other safety concerns were seen.

Conclusion

These results indicate florbetaben to be a safe and efficacious β-amyloid-targeted tracer with favourable brain kinetics. Subjects with AD could be easily differentiated from HCs by both visual and quantitative assessment of the PET data. The operator-independent, voxel-based analysis yielded whole brain β-amyloid load which appeared valuable as a surrogate marker of disease severity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Tarditi A, Caricasole A, Terstappen G. Therapeutic targets for Alzheimer’s disease. Expert Opin Ther Targets 2009;13:551–67.

    Article  PubMed  CAS  Google Scholar 

  2. Bergmans BA, De Strooper B. Gamma-secretases: from cell biology to therapeutic strategies. Lancet Neurol 2010;9:215–26.

    Article  PubMed  CAS  Google Scholar 

  3. Taupin P. Adult neurogenesis, neural stem cells and Alzheimer’s disease: developments, limitations, problems and promises. Curr Alzheimer Res 2009;6:461–70.

    Article  PubMed  CAS  Google Scholar 

  4. Alzheimer’s Disease International. World Alzheimer Report 2009. http://www.alz.co.uk/research/worldreport.

  5. Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 1991;82:239–59.

    Article  PubMed  CAS  Google Scholar 

  6. Gauthier S, Scheltens P. Can we do better in developing new drugs for Alzheimer’s disease? Alzheimers Dement 2009;5:489–91.

    Article  PubMed  Google Scholar 

  7. Pike KE, Savage G. Memory profiling in mild cognitive impairment: can we determine risk for Alzheimer’s disease? J Neuropsychol 2008;2:361–72.

    Article  PubMed  Google Scholar 

  8. Kukull WA, Larson EB, Reifler BV, Lampe TH, Yerby MS, Hughes JP. The validity of 3 clinical diagnostic criteria for Alzheimer’s disease. Neurology 1990;40:1364–9.

    PubMed  CAS  Google Scholar 

  9. Jellinger K, Danielczyk W, Fischer P, Gabriel E. Clinicopathological analysis of dementia disorders in the elderly. J Neurol Sci 1990;95:239–58.

    Article  PubMed  CAS  Google Scholar 

  10. Dubois B, Feldman HH, Jacova C, Dekosky ST, Barberger-Gateau P, Cummings J, et al. Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDS-ADRDA criteria. Lancet Neurol 2007;6:734–46.

    Article  PubMed  Google Scholar 

  11. Jack Jr CR, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol 2010;9:119–28.

    Article  PubMed  CAS  Google Scholar 

  12. Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993;43:2412–4.

    PubMed  CAS  Google Scholar 

  13. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed. Washington, D.C.: American Psychiatric Association; 1994. p. 143–7. DSM-IV.

    Google Scholar 

  14. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34:939–44.

    PubMed  CAS  Google Scholar 

  15. Morris JC, Mohs RC, Rogers H, Fillenbaum G, Heyman A. Consortium to establish a registry for Alzheimer’s disease (CERAD) clinical and neuropsychological assessment of Alzheimer’s disease. Psychopharmacol Bull 1988;24:641–52.

    PubMed  CAS  Google Scholar 

  16. Wolf-Klein GP, Silverstone FA, Levy AP, Brod MS. Screening for Alzheimer’s disease by clock drawing. J Am Geriatr Soc 1989;37:730–4.

    PubMed  CAS  Google Scholar 

  17. Zhang W, Oya S, Kung MP, Hou C, Maier DL, Kung HF. F-18 Polyethyleneglycol stilbenes as PET imaging agents targeting Abeta aggregates in the brain. Nucl Med Biol 2005;32:799–809.

    Article  PubMed  CAS  Google Scholar 

  18. Patt M, Schildan A, Barthel H, Becker G, Schultze-Mosgau MH, Rohde B, et al. Metabolite analysis of [18F]florbetaben (BAY 94-9172) in human subjects: a substudy within a proof of mechanism clinical trial. J Radioanaly Nucl Chem 2010;284:557–62.

    Article  CAS  Google Scholar 

  19. Meyer PM, Strecker K, Kendziorra K, Becker G, Hesse S, Woelpl D, et al. Reduced α4β2*-nicotinic acetylcholine receptor binding and its relationship to mild cognitive and depressive symptoms in Parkinson disease. Arch Gen Psychiatry 2009;66:866–77.

    Article  PubMed  CAS  Google Scholar 

  20. Svedberg MM, Hall H, Hellström-Lindahl E, Estrada S, Guan Z, Nordberg A, et al. [(11)C]PIB-amyloid binding and levels of Abeta40 and Abeta42 in postmortem brain tissue from Alzheimer patients. Neurochem Int 2009;54:347–57.

    Article  PubMed  CAS  Google Scholar 

  21. Rowe CC, Ackerman U, Browne W, Mulligan R, Pike KL, O’Keefe G, et al. Imaging of amyloid beta in Alzheimer’s disease with 18F-BAY94-9172, a novel PET tracer: proof of mechanism. Lancet Neurol 2008;7:129–35.

    Article  PubMed  CAS  Google Scholar 

  22. Talairach J, Tournoux P. Co-planar stereotaxic atlas of the human brain. Stuttgart: Thieme; 1988.

    Google Scholar 

  23. Haylett DG. Textbook of receptor pharmacology. Boca Raton: CRC; 2002.

    Google Scholar 

  24. Cicchetti DV, Allison T. New procedure for assessing reliability of scoring EEG sleep recordings. Am J EEG Technol 1971;11:101–9.

    Google Scholar 

  25. Mosconi L, Rinne JO, Tsui WH, Berti V, Li Y, Wang H, et al. Increased fibrillar amyloid-{beta} burden in normal individuals with a family history of late-onset Alzheimer’s disease. Proc Natl Acad Sci U S A 2010;107:5949–54.

    Article  PubMed  CAS  Google Scholar 

  26. Okello A, Koivunen J, Edison P, Archer HA, Turkheimer FE, Någren K, et al. Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. Neurology 2009;73:754–60.

    Article  PubMed  CAS  Google Scholar 

  27. Klunk WE, Engler H, Nordberg A, Wang Y, Blomqvist G, Holt DP, et al. Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann Neurol 2004;55:306–19.

    Article  PubMed  CAS  Google Scholar 

  28. Rabinovici GD, Furst AJ, O’Neil JP, Racine CA, Mormino EC, Baker SL, et al. 11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration. Neurology 2007;68:1205–12.

    Article  PubMed  CAS  Google Scholar 

  29. Thompson PW, Lockhart A. Monitoring the amyloid beta-peptide in vivo—caveat emptor. Drug Discov Today 2009;14:241–51.

    Article  PubMed  CAS  Google Scholar 

  30. Rinne JO, Brooks DJ, Rossor MN, Fox NC, Bullock R, Klunk WE, et al. 11C-PiB PET assessment of change in fibrillar amyloid-beta load in patients with Alzheimer’s disease treated with bapineuzumab: a phase 2, double-blind, placebo-controlled, ascending-dose study. Lancet Neurol 2010;9:363–72.

    Article  PubMed  CAS  Google Scholar 

  31. O’Keefe GJ, Saunder TH, Ng S, Ackerman U, Tochon-Danguy HJ, Chan JG, et al. Radiation dosimetry of beta-amyloid tracers 11C-PiB and 18F-BAY94-9172. J Nucl Med 2009;50:309–15.

    Article  PubMed  Google Scholar 

  32. Kim J, Basak JM, Holtzman DM. The role of apolipoprotein E in Alzheimer’s disease. Neuron 2009;63:287–303.

    Article  PubMed  CAS  Google Scholar 

  33. Morris CJ, Roe CM, Xiong C, Fagan AM, Goate AM, Holtzman DM, et al. APOE predicts amyloid-beta but not tau Alzheimer pathology in cognitively normal aging. Ann Neurol 2010;67:122–31.

    Article  PubMed  CAS  Google Scholar 

  34. Farrer LA, Cupples LA, Haines JL, Hyman B, Kukull WA, Mayeux R, et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA 1997;278:1349–56.

    Article  PubMed  CAS  Google Scholar 

  35. Saunders AM, Schmader K, Breitner JC, Benson MD, Brown WT, Goldfarb L, et al. Apolipoprotein E epsilon 4 allele distributions in late-onset Alzheimer’s disease and in other amyloid-forming diseases. Lancet 1993;342:710–1.

    Article  PubMed  CAS  Google Scholar 

  36. Drzezga A, Grimmer T, Henriksen G, Mühlau M, Perneczky R, Miederer I, et al. Effect of APOE genotype on amyloid plaque load and gray matter volume in Alzheimer disease. Neurology 2009;72:1487–94.

    Article  PubMed  CAS  Google Scholar 

  37. Stankoff B, Freeman L, Aigrot MS, Chardain A, Dollé F, Williams A, et al. Imaging central nervous system myelin by positron emission tomography in multiple sclerosis using [methyl-(11) C]-2-(4'-methylaminophenyl)-6-hydroxybenzothiazole. Ann Neurol 2010 [Epub ahead of print].

  38. Mintun MA, Larossa GN, Sheline YI, Dence CS, Lee SY, Mach RH, et al. [11C]PIB in a nondemented population: potential antecedent marker of Alzheimer disease. Neurology 2006;67:446–52.

    Article  PubMed  CAS  Google Scholar 

  39. Rowe CC, Ng S, Ackermann U, Gong SJ, Pike K, Savage G, et al. Imaging beta-amyloid burden in aging and dementia. Neurology 2007;68:1718–25.

    Article  PubMed  CAS  Google Scholar 

  40. Aizenstein HJ, Nebes RD, Saxton JA, Price JC, Mathis CA, Tsopelas ND, et al. Frequent amyloid deposition without significant cognitive impairment among the elderly. Arch Neurol 2008;65:1509–17.

    Article  PubMed  Google Scholar 

  41. Price JL, Morris JC. Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease. Ann Neurol 1999;45:358–68.

    Article  PubMed  CAS  Google Scholar 

  42. Scheinin NM, Aalto S, Koikkalainen J, Lötjönen J, Karrasch M, Kemppainen N, et al. Follow-up of [11C]PIB uptake and brain volume in patients with Alzheimer disease and controls. Neurology 2009;73:1186–92.

    Article  PubMed  CAS  Google Scholar 

  43. Pike KE, Savage G, Villemagne VL, Ng S, Moss SA, Maruff P, et al. Beta-amyloid imaging and memory in non-demented individuals: evidence for preclinical Alzheimer’s disease. Brain 2007;130:2837–44.

    Article  PubMed  Google Scholar 

  44. Price JC, Klunk WE, Lopresti BJ, Lu X, Hoge JA, Ziolko SK, et al. Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B. J Cereb Blood Flow Metab 2005;25:1528–47.

    Article  PubMed  CAS  Google Scholar 

  45. Lopresti BJ, Klunk WE, Mathis CA, Hoge JA, Ziolko SK, Lu X, et al. Simplified quantification of Pittsburgh Compound B amyloid imaging PET studies: a comparative analysis. J Nucl Med 2005;46:1959–72.

    PubMed  CAS  Google Scholar 

  46. Furst AJ, Rabinovici GD, Rostomian AH, Steed T, Alkalay A, Racine C, et al. Cognition, glucose metabolism and amyloid burden in Alzheimer’s disease. Neurobiol Aging. doi:10.1016/j.neurobiolaging.2010.03.011.

  47. Harvan JR, Cotter V. An evaluation of dementia screening in the primary care setting. J Am Acad Nurse Pract 2006;18:351–60.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to thank all patients, their caregivers, and the healthy volunteers who participated in this trial. Further, the support of the PET and cyclotron teams of the Department of Nuclear Medicine, University of Leipzig, is greatly acknowledged. This trial was supported by Bayer Healthcare (Berlin, Germany).

Conflicts of interest

HB, BS, and OS receive consultant honoraria from Bayer Healthcare. TZ, JR, BR, and CR are employees of Bayer Healthcare. The other authors declare that they have no conflict of interests.

Author information

Authors and Affiliations

  1. Department of Nuclear Medicine, University of Leipzig, Liebigstr. 18, 04103, Leipzig, Germany

    Henryk Barthel, Julia Luthardt, Georg Becker, Marianne Patt, Bernhard Sattler, Andreas Schildan, Swen Hesse, Philipp M. Meyer & Osama Sabri

  2. Department of Psychiatry, University of Leipzig, Leipzig, Germany

    Eva Hammerstein, Kristin Hartwig, Henrike Wolf & Hermann-Josef Gertz

  3. Arzneimittelforschung Leipzig GmbH, Leipzig, Germany

    Birk Eggers

  4. Department of Psychiatry, University of Zurich, Zurich, Switzerland

    Henrike Wolf

  5. Bayer Healthcare, Berlin, Germany

    Torsten Zimmermann, Joachim Reischl, Beate Rohde & Cornelia Reininger

Authors
  1. Henryk Barthel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Julia Luthardt
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Georg Becker
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marianne Patt
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Eva Hammerstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kristin Hartwig
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Birk Eggers
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Bernhard Sattler
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Andreas Schildan
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Swen Hesse
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Philipp M. Meyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Henrike Wolf
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Torsten Zimmermann
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Joachim Reischl
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Beate Rohde
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Hermann-Josef Gertz
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Cornelia Reininger
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Osama Sabri
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Henryk Barthel.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Barthel, H., Luthardt, J., Becker, G. et al. Individualized quantification of brain β-amyloid burden: results of a proof of mechanism phase 0 florbetaben PET trial in patients with Alzheimer’s disease and healthy controls. Eur J Nucl Med Mol Imaging 38, 1702–1714 (2011). https://doi.org/10.1007/s00259-011-1821-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00259-011-1821-1

Keywords

Search

Navigation