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Imaging characteristic of dual-phase 18F-florbetapir (AV-45/Amyvid) PET for the concomitant detection of perfusion deficits and beta-amyloid deposition in Alzheimer’s disease and mild cognitive impairment

  • Kun-Ju Lin
  • Ing-Tsung Hsiao
  • Jung-Lung Hsu
  • Chin-Chang Huang
  • Kuo-Lun Huang
  • Chia-Ju Hsieh
  • Shiaw-Pyng Wey
  • Tzu-Chen Yen
Original Article

Abstract

Purpose

We investigated dual-phase 18F-florbetapir (AV-45/Amyvid) PET imaging for the concomitant detection of brain perfusion deficits and beta-amyloid deposition in patients with Alzheimer’s disease (AD) and amnestic mild cognitive impairment (MCI), and in cognitively healthy controls (HCs).

Methods

A total of 82 subjects (24 AD patients, 44 MCI patients and 14 HCs) underwent both dual-phase 18F-AV-45 PET and MRI imaging. Dual-phase dynamic PET imaging consisted of (1) five 1-min scans obtained 1 – 6 min after tracer injection (perfusion 18F-AV-45 imaging, pAV-45), and (2) ten 1-min scans obtained 50 – 60 min after tracer injection (amyloid 18F-AV-45 imaging). Amyloid-negative MCI/AD patients were excluded. Volume of interest analysis and statistical parametric mapping of pAV-45 and 18F-AV-45 images were performed to investigate the perfusion deficits and the beta-amyloid burden in the three study groups. The associations between Mini-Mental State Examination (MMSE) scores and global perfusion deficits and amyloid deposition were investigated with linear and segmental linear correlation analyses.

Results

HCs generally had normal pAV-45 findings, whereas perfusion deficits were evident in the hippocampus, and temporal, parietal and middle frontal cortices in both MCI and AD patients. The motor-sensory cortex was relatively preserved. MMSE scores in the entire study cohort were significantly associated with the degree of perfusion impairment as assessed by pAV-45 imaging (r = 0.5156, P < 0.0001). 18F-AV-45 uptake was significantly higher in AD patients than in the two other study groups. However, the correlation between MMSE scores and 18F-AV-45 uptake in MCI patients was more of a binary phenomenon and began in MCI patients with MMSE score 23.14 when 18F-AV-45 uptake was higher and MMSE score lower than in patients with early MCI. Amyloid deposition started in the precuneus and the frontal and temporal regions in early MCI, ultimately reaching the maximum burden in advanced MCI.

Conclusion

Our results indicate that brain perfusion deficits and beta-amyloid deposition in AD follow different trajectories that can be successfully traced using dual-phase 18F-AV-45 PET imaging.

Keywords

Dual-phase scan Perfusion deficits Amyloid 18F-Florbetapir (AV-45/Amyvid) Alzheimer’s disease Dementia Mild cognitive impairment 

Notes

Acknowledgments

We thank Avid Radiopharmaceuticals Inc. (Philadelphia, PA, USA) for providing the precursor for the preparation of 18F-florbetapir.

Compliance with ethical standards

Funding

This study was carried out with financial support from the National Research Program for Biopharmaceuticals, National Science Council, Taiwan (MOST 103-2314-B-182A-009, 104-2314-B-182A-083-MY2, 103-2325-B-182A-009) and grants from the Research Fund of Chang Gung Memorial Hospital (CMRPG390793).

Conflicts of Interest

None.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the principles of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study. In addition, the next of kin or guardians of AD and MCI patients also gave their written informed consent if the patients could not comprehend the study protocol or they could not sign their name clearly.

Supplementary material

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Supplementary Table 1 (DOCX 26 kb)
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Supplementary Table 2 (DOCX 43 kb)
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Supplementary Table 3 (DOCX 63 kb)
259_2016_3359_MOESM4_ESM.docx (32 kb)
Supplementary Table 4 (DOCX 32 kb)
259_2016_3359_MOESM5_ESM.docx (24 kb)
Supplementary Table 5 (DOCX 23 kb)

References

  1. 1.
    McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR, Kawas CH, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7:263–9.CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    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.CrossRefPubMedGoogle Scholar
  3. 3.
    Lin KJ, Hsu WC, Hsiao IT, Wey SP, Jin LW, Skovronsky D, et al. Whole-body biodistribution and brain PET imaging with [18F]AV-45, a novel amyloid imaging agent – a pilot study. Nucl Med Biol. 2010;37:497–508.CrossRefPubMedGoogle Scholar
  4. 4.
    Nelissen N, Van Laere K, Thurfjell L, Owenius R, Vandenbulcke M, Koole M, et al. Phase 1 study of the Pittsburgh compound B derivative 18F-flutemetamol in healthy volunteers and patients with probable Alzheimer disease. J Nucl Med. 2009;50:1251–9.CrossRefPubMedGoogle Scholar
  5. 5.
    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.CrossRefPubMedGoogle Scholar
  6. 6.
    Jagust WJ, Friedland RP, Budinger TF. Positron emission tomography with [18F]fluorodeoxyglucose differentiates normal pressure hydrocephalus from Alzheimer-type dementia. J Neurol Neurosurg Psychiatry. 1985;48:1091–6.CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Smith FW, Besson JA, Gemmell HG, Sharp PF. The use of technetium-99m-HM-PAO in the assessment of patients with dementia and other neuropsychiatric conditions. J Cereb Blood Flow Metab. 1988;8:S116–22.CrossRefPubMedGoogle Scholar
  8. 8.
    Jack 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.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Landau SM, Mintun MA, Joshi AD, Koeppe RA, Petersen RC, Aisen PS, et al. Amyloid deposition, hypometabolism, and longitudinal cognitive decline. Ann Neurol. 2012;72:578–86.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Wu L, Rowley J, Mohades S, Leuzy A, Dauar MT, Shin M, et al. Dissociation between brain amyloid deposition and metabolism in early mild cognitive impairment. PLoS One. 2012;7:e47905.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Hsiao IT, Huang CC, Hsieh CJ, Hsu WC, Wey SP, Yen TC, et al. Correlation of early-phase 18F-florbetapir (AV-45/Amyvid) PET images to FDG images: preliminary studies. Eur J Nucl Med Mol Imaging. 2012;39:613–20.CrossRefPubMedGoogle Scholar
  12. 12.
    Meyer PT, Hellwig S, Amtage F, Rottenburger C, Sahm U, Reuland P, et al. Dual-biomarker imaging of regional cerebral amyloid load and neuronal activity in dementia with PET and 11C-labeled Pittsburgh compound B. J Nucl Med. 2011;52:393–400.CrossRefPubMedGoogle Scholar
  13. 13.
    Koeppe RA, Gilman S, Joshi A, Liu S, Little R, Junck L, et al. 11C-DTBZ and 18F-FDG PET measures in differentiating dementias. J Nucl Med. 2005;46:936–44.PubMedGoogle Scholar
  14. 14.
    Treyer V, Streffer J, Wyss MT, Bettio A, Ametamey SM, Fischer U, et al. Evaluation of the metabotropic glutamate receptor subtype 5 using PET and 11C-ABP688: assessment of methods. J Nucl Med. 2007;48:1207–15.CrossRefPubMedGoogle Scholar
  15. 15.
    Farid K, Hong YT, Aigbirhio FI, Fryer TD, Menon DK, Warburton EA, et al. Early-phase 11C-PiB PET in amyloid angiopathy-related symptomatic cerebral hemorrhage: potential diagnostic value? PLoS One. 2015;10:e0139926.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Gur RC, Ragland JD, Reivich M, Greenberg JH, Alavi A, Gur RE. Regional differences in the coupling between resting cerebral blood flow and metabolism may indicate action preparedness as a default state. Cereb Cortex. 2009;19:375–82.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Murase K, Tanada S, Fujita H, Sakaki S, Hamamoto K. Kinetic behavior of technetium-99m-HMPAO in the human brain and quantification of cerebral blood flow using dynamic SPECT. J Nucl Med. 1992;33:135–43.PubMedGoogle Scholar
  18. 18.
    Wong CY, Thie J, Gaskill M, Ponto R, Hill J, Tian HY, et al. A statistical investigation of normal regional intra-subject heterogeneity of brain metabolism and perfusion by F-18 FDG and O-15 H2O PET imaging. BMC Nucl Med. 2006;6:4.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Chen Y, Wolk D, Reddin J, Korczykowski M, Martinez P, Musiek E, et al. Voxel-level comparison of arterial spin-labeled perfusion MRI and FDG-PET in Alzheimer disease. Neurology. 2011;77:1977–85.CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Musiek ES, Chen Y, Korczykowski M, Saboury B, Martinez PM, Reddin JS, et al. Direct comparison of fluorodeoxyglucose positron emission tomography and arterial spin labeling magnetic resonance imaging in Alzheimer's disease. Alzheimers Dement. 2012;8:51–9.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Rostomian AH, Madison C, Rabinovici GD, Jagust WJ. Early [11C]PIB frames and [18F]FDG PET measures are comparable: a study validated in a cohort of AD and FTLD patients. J Nucl Med. 2011;52:173–9.PubMedPubMedCentralGoogle Scholar
  22. 22.
    Huang KL, Lin KJ, Hsiao IT, Kuo HC, Hsu WC, Chuang WL, et al. Regional amyloid deposition in amnestic mild cognitive impairment and Alzheimer's disease evaluated by [18F]AV-45 positron emission tomography in Chinese population. PLoS One. 2013;8:e58974.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Winblad B, Palmer K, Kivipelto M, Jelic V, Fratiglioni L, Wahlund LO, et al. Mild cognitive impairment – beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. J Intern Med. 2004;256:240–6.CrossRefPubMedGoogle Scholar
  24. 24.
    Petersen RC, Doody R, Kurz A, Mohs RC, Morris JC, Rabins PV, et al. Current concepts in mild cognitive impairment. Arch Neurol. 2001;58:1985–92.CrossRefPubMedGoogle Scholar
  25. 25.
    American Psychiatric Association. Diagnostic and statistical manual of mental disorders, DSM-IV. Washington, DC: American Psychiatric Association.Google Scholar
  26. 26.
    Lin RT, Lai CL, Tai CT, Liu CK, Yen YY, Howng SL. Prevalence and subtypes of dementia in southern Taiwan: impact of age, sex, education, and urbanization. J Neurol Sci. 1998;160:67–75.CrossRefPubMedGoogle Scholar
  27. 27.
    Liu CK, Lin RT, Chen YF, Tai CT, Yen YY, Howng SL. Prevalence of dementia in an urban area in Taiwan. J Formos Med Assoc. 1996;95:762–8.PubMedGoogle Scholar
  28. 28.
    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.CrossRefPubMedGoogle Scholar
  29. 29.
    Yao CH, Lin KJ, Weng CC, Hsiao IT, Ting YS, Yen TC, et al. GMP-compliant automated synthesis of [(18)F]AV-45 (Florbetapir F18) for imaging beta-amyloid plaques in human brain. Appl Radiat Isot. 2010;68:2293–7.CrossRefPubMedGoogle Scholar
  30. 30.
    Xia M, Wang J, He Y. BrainNet Viewer: a network visualization tool for human brain connectomics. PLoS One. 2013;8:e68910.CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Mazziotta JC, Toga AW, Evans A, Fox P, Lancaster J. A probabilistic atlas of the human brain: theory and rationale for its development. The International Consortium for Brain Mapping (ICBM). Neuroimage. 1995;2:89–101.CrossRefPubMedGoogle Scholar
  32. 32.
    Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage. 2002;15:273–89.CrossRefPubMedGoogle Scholar
  33. 33.
    Pagani M, De Carli F, Morbelli S, Öberg J, Chincarini A, Frisoni G, et al. Volume of interest-based [18F]fluorodeoxyglucose PET discriminates MCI converting to Alzheimer's disease from healthy controls. A European Alzheimer's Disease Consortium (EADC) study. NeuroImage Clin. 2015;7:34–42.CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Clark CM, Schneider JA, Bedell BJ, Beach TG, Bilker WB, Mintun MA, et al. Use of florbetapir-PET for imaging β-amyloid pathology. JAMA. 2011;305:275–83.CrossRefPubMedGoogle Scholar
  35. 35.
    Johnson KA, Sperling RA, Gidicsin CM, Carmasin JS, Maye JE, Coleman RE, et al. Florbetapir (F18-AV-45) PET to assess amyloid burden in Alzheimer's disease dementia, mild cognitive impairment, and normal aging. Alzheimers Dement. 2013;9:S72–83.CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. 2002;27:299–309.CrossRefPubMedGoogle Scholar
  37. 37.
    Del Sole A, Clerici F, Chiti A, Lecchi M, Mariani C, Maggiore L, et al. Individual cerebral metabolic deficits in Alzheimer’s disease and amnestic mild cognitive impairment: an FDG PET study. Eur J Nucl Med Mol Imaging. 2008;35:1357–66.CrossRefPubMedGoogle Scholar
  38. 38.
    Silverman DH, Alavi A. PET imaging in the assessment of normal and impaired cognitive function. Radiol Clin North Am. 2005;43:67–77.CrossRefPubMedGoogle Scholar
  39. 39.
    Habeck C, Risacher S, Lee GJ, Glymour MM, Mormino E, Mukherjee S, et al. Relationship between baseline brain metabolism measured using [18F]FDG PET and memory and executive function in prodromal and early Alzheimer’s disease. Brain Imaging Behav. 2012;6:568–83.CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Jagust W, Gitcho A, Sun F, Kuczynski B, Mungas D, Haan M. Brain imaging evidence of preclinical Alzheimer's disease in normal aging. Ann Neurol. 2006;59:673–81.CrossRefPubMedGoogle Scholar
  41. 41.
    Landau SM, Harvey D, Madison CM, Koeppe RA, Reiman EM, Foster NL, et al. Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol Aging. 2011;32:1207–18.CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Shokouhi S, Claassen D, Kang H, Ding Z, Rogers B, Mishra A, et al. Longitudinal progression of cognitive decline correlates with changes in the spatial pattern of brain 18F-FDG PET. J Nucl Med. 2013;54:1564–9.CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Alexopoulos P, Sorg C, Forschler A, Grimmer T, Skokou M, Wohlschlager A, et al. Perfusion abnormalities in mild cognitive impairment and mild dementia in Alzheimer’s disease measured by pulsed arterial spin labeling MRI. Eur Arch Psychiatry Clin Neurosci. 2012;262:69–77.CrossRefPubMedGoogle Scholar
  44. 44.
    Jueptner M, Weiller C. Review: does measurement of regional cerebral blood flow reflect synaptic activity? Implications for PET and fMRI. Neuroimage. 1995;2:148–56.CrossRefPubMedGoogle Scholar
  45. 45.
    Bozzao A, Floris R, Baviera ME, Apruzzese A, Simonetti G. Diffusion and perfusion MR imaging in cases of Alzheimer's disease: correlations with cortical atrophy and lesion load. AJNR Am J Neuroradiol. 2001;22:1030–6.PubMedGoogle Scholar
  46. 46.
    Shimizu S, Zhang Y, Laxamana J, Miller BL, Kramer JH, Weiner MW, et al. Concordance and discordance between brain perfusion and atrophy in frontotemporal dementia. Brain Imaging Behav. 2010;4:46–54.CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Hulette CM, Welsh-Bohmer KA, Murray MG, Saunders AM, Mash DC, McIntyre LM. Neuropathological and neuropsychological changes in “normal” aging: evidence for preclinical Alzheimer disease in cognitively normal individuals. J Neuropathol Exp Neurol. 1998;57:1168–74.CrossRefPubMedGoogle Scholar
  48. 48.
    Pearl GS. Diagnosis of Alzheimer's disease in a community hospital-based brain bank program. South Med J. 1997;90:720–2.CrossRefPubMedGoogle Scholar
  49. 49.
    Petersen RC, Parisi JE, Dickson DW, Johnson KA, Knopman DS, Boeve BF, et al. Neuropathologic features of amnestic mild cognitive impairment. Arch Neurol. 2006;63:665–72.CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Nuclear Medicine and Molecular Imaging CenterLinkou Chang Gung Memorial Hospital and UniversityTaoyuanTaiwan
  2. 2.Department of Medical Imaging and Radiological Sciences and Healthy Aging Research CenterChang Gung UniversityTaoyuanTaiwan
  3. 3.Section of Dementia and Cognitive Impairment, Department of NeurologyLinkou Chang Gung Memorial HospitalTaoyuanTaiwan
  4. 4.Graduate Institute of Humanities in MedicineTaipei Medical UniversityTaipeiTaiwan
  5. 5.Department of NeurologyLinkou Chang Gung Memorial Hospital and UniversityTaoyuanTaiwan

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