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FDG-PET changes in brain glucose metabolism from normal cognition to pathologically verified Alzheimer’s disease

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European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

We report the first clinicopathological series of longitudinal FDG-PET scans in post-mortem (PM) verified cognitively normal elderly (NL) followed to the onset of Alzheimer’s-type dementia (DAT), and in patients with mild DAT with progressive cognitive deterioration.

Methods

Four NL subjects and three patients with mild DAT received longitudinal clinical, neuropsychological and dynamic FDG-PET examinations with arterial input functions. NL subjects were followed for 13 ± 5 years, received FDG-PET examinations over 7 ± 2 years, and autopsy 6 ± 3 years after the last FDG-PET. Two NL declined to mild cognitive impairment (MCI), and two developed probable DAT before death. DAT patients were followed for 9 ± 3 years, received FDG-PET examinations over 3 ± 2 years, and autopsy 7 ± 1 years after the last FDG-PET. Two DAT patients progressed to moderate-to-severe dementia and one developed vascular dementia.

Results

The two NL subjects who declined to DAT received a PM diagnosis of definite AD. Their FDG-PET scans indicated a progression of deficits in the cerebral metabolic rate for glucose (CMRglc) from the hippocampus to the parietotemporal and posterior cingulate cortices. One DAT patient showed AD with diffuse Lewy body disease (LBD) at PM, and her last in vivo PET was indicative of possible LBD for the presence of occipital as well as parietotemporal hypometabolism.

Conclusion

Progressive CMRglc reductions on FDG-PET occur years in advance of clinical DAT symptoms in patients with pathologically verified disease. The FDG-PET profiles in life were consistent with the PM diagnosis.

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References

  1. Mirra SS, Heyman A, McKeel D, et al. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part II. Standardization of the neuropathologic assessment of Alzheimer’s disease. Neurol 1991;41:479–86.

    CAS  Google Scholar 

  2. 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 

  3. 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 

  4. Mosconi L. Brain glucose metabolism in the early and specific diagnosis of Alzheimer’s disease. Eur J Nucl Med 2005;32:486–510.

    Article  CAS  Google Scholar 

  5. Chetelat G, Desgranges B, De La Sayette V, Viader F, Eustache F, Baron JC. Mild cognitive impairment: can FDG-PET predict who is to rapidly convert to Alzheimer’s disease? Neurology 2003;60:1374–7.

    PubMed  CAS  Google Scholar 

  6. Drzezga A, Lautenschlager N, Siebner H, et al. Cerebral metabolic changes accompanying conversion of mild cognitive impairment into Alzheimer’s disease: a PET follow-up study. Eur J Nucl Med Mol Imaging 2003;30:1104–13.

    Article  PubMed  Google Scholar 

  7. Mosconi L, Perani D, Sorbi S, et al. MCI conversion to dementia and the APOE genotype: a prediction study with FDG-PET. Neurology 2004;63:2332–40.

    PubMed  CAS  Google Scholar 

  8. Ball MJ, Hachinski V, Fox A, et al. A new definition of Alzheimer’s disease: a hippocampal dementia. Lancet 1985;1:14–6.

    Article  PubMed  CAS  Google Scholar 

  9. de Leon MJ, Convit A, Wolf OT, et al. Prediction of cognitive decline in normal elderly subjects with 2-[18F]fluoro-2-deoxy-D-glucose/positron-emission tomography (FDG/PET). Proc Natl Acad Sci U S A 2001;98:10966–71.

    Article  PubMed  Google Scholar 

  10. Mosconi L, De Santi S, Li J, et al. Hippocampal hypometabolism predicts cognitive decline from normal aging. Neurobiol Aging 2007;29:676–92.

    Article  PubMed  Google Scholar 

  11. De Santi S, de Leon MJ, Rusinek H, et al. Hippocampal formation glucose metabolism and volume losses in MCI and AD. Neurobiol Aging 2001;22:529–39.

    Article  PubMed  Google Scholar 

  12. Reisberg B, Ferris SH, de Leon MJ, Crook T. The global deterioration scale for assessment of primary degenerative dementia. Am J Psychiatry 1982;139:1136–9.

    PubMed  CAS  Google Scholar 

  13. Hachinski VC, Lassen NA, Marshall J. Multi-infarct dementia, a cause of mental deterioration in the elderly. Lancet 1974;2:207–10.

    Article  PubMed  CAS  Google Scholar 

  14. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed. Washington, D.C.: American Psychiatric Association; 1994.

    Google Scholar 

  15. De Santi S, Pirraglia E, Barr W, Babb J, Williams S, Rogers K, et al. Robust and conventional neuropsychological norms: diagnosis and prediction of age-related cognitive decline. Neuropsychology 2008;22:469–84.

    Article  PubMed  Google Scholar 

  16. Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol 1999;56:303–8.

    Article  PubMed  CAS  Google Scholar 

  17. Wegiel J, Kuchna I, Nowicki K, et al. Intraneuronal Abeta immunoreactivity is not a predictor of brain amyloidosis-beta or neurofibrillary degeneration. Acta Neuropathol 2007;113:389–402.

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  19. The National Institute on Aging, the Reagan Institute Working Group on Diagnostic Criteria for the Neuropathological Assessment of Alzheimer’s disease. Consensus recommendations for the postmortem diagnosis of Alzheimer’s disease. Neurobiol Aging 1997;18:S1–2.

    Article  Google Scholar 

  20. Sokoloff L, Reivich M, Kennedy C, et al. The [14C]deoxyglucose method for the measurement of local cerebral glucose utilization: theory, procedure, and normal values in the conscious and anesthetized albino rat. J Neurochem 1977;28:897–916.

    Article  PubMed  CAS  Google Scholar 

  21. Reivich M, Alavi A, Wolf A, et al. Glucose metabolic rate kinetic model parameter determination in humans: the lumped constants and rate constants for [18F]fluorodeoxyglucose and [11C]deoxyglucose. J Cereb Blood Flow Metab 1985;5:179–92.

    PubMed  CAS  Google Scholar 

  22. George AE, de Leon MJ, Kalnin A, Rosner L, Goodgold A, Chase N. Leukoencephalopathy in normal and pathologic aging: 2. MRI and brain lucencies. AJNR Am J Neuroradiol 1986;7:567–70.

    PubMed  CAS  Google Scholar 

  23. Minoshima S, Giordani B, Berent S, Frey KA, Foster NL, Kuhl DE. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann Neurol 1997;42:85–94.

    Article  PubMed  CAS  Google Scholar 

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

    Google Scholar 

  25. Mosconi L, Tsui WH, Pupi A, et al. (18)F-FDG PET database of longitudinally confirmed healthy elderly individuals improves detection of mild cognitive impairment and Alzheimer’s disease. J Nucl Med 2007;48:1129–34.

    Article  PubMed  Google Scholar 

  26. Mosconi L, Tsui WH, De Santi S, et al. Reduced hippocampal metabolism in mild cognitive impairment and Alzheimer’s disease: automated FDG-PET image analysis. Neurology 2005;64:1860–7.

    Article  PubMed  CAS  Google Scholar 

  27. Li Y, Rinne JO, Mosconi L, Pirraglia E, Rusinek H, Desanti S, et al. Regional analysis of FDG and PIB-PET images in normal aging, mild cognitive impairment and Alzheimer’s disease. Eur J Nucl Med Mol Imaging 2008;35:2169–81.

    Article  PubMed  Google Scholar 

  28. Minoshima S, Foster NL, Sima AA, Frey KA, Albin RL, Kuhl DE. Alzheimer’s disease versus dementia with Lewy bodies: cerebral metabolic distinction with autopsy confirmation. Ann Neurol 2001;50:358–65.

    Article  PubMed  CAS  Google Scholar 

  29. Braak H, Braak E. Development of Alzheimer-related neurofibrillary changes in the neocortex inversely recapitulates cortical myelogenesis. Acta Neuropathol 1996;92:197–201.

    Article  PubMed  CAS  Google Scholar 

  30. Delacourte A, David JP, Sergeant N, et al. The biochemical pathway of neurofibrillary degeneration in aging and Alzheimer’s disease. Neurol 1999;52:1158–65.

    CAS  Google Scholar 

  31. DeCarli C, Atack JR, Ball MJ, et al. Post-mortem regional neurofibrillary tangle densities but not senile plaque densities are related to regional cerebral metabolic rates for glucose life in Alzheimer’s disease patients. Neurodegeneration 1992;1:113–21.

    Google Scholar 

  32. Bradley KM, O’Sullivan VT, Soper ND, et al. Cerebral perfusion SPET correlated with Braak pathological stage in Alzheimer’s disease. Brain 2002;125:1772–81.

    Article  PubMed  CAS  Google Scholar 

  33. Silverman DHS, Small GW, Chang CY, et al. Positron emission tomography in evaluation of dementia: regional brain metabolism and long-term outcome. JAMA 2001;286:2120–7.

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

This work was supported by the NIH-NIA grants AG12101, AG13616, AG08051, AG03051 and AG022374, NIH NCRR and MO1RR0096, and the Alzheimer’s Association. We thank Joanna Fowler, David Schlyer and Gene-Jack Wang at BNL for their support of the PET studies, and Miroslaw Brys for his contribution to the paper.

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Authors and Affiliations

  1. Department of Psychiatry, New York University School of Medicine, New York, USA

    Lisa Mosconi, Rachel Mistur, Remigiusz Switalski, Wai Hon Tsui, Lidia Glodzik, Yi Li, Elizabeth Pirraglia, Susan De Santi, Barry Reisberg, Thomas Wisniewski & Mony J. de Leon

  2. Department of Neurology, New York University School of Medicine, New York, USA

    Thomas Wisniewski

  3. Department of Pathology, New York University School of Medicine, New York, USA

    Thomas Wisniewski

  4. Nathan Kline Institute, Orangeburg, NY, USA

    Wai Hon Tsui & Mony J. de Leon

  5. Center for Brain Health, MHL 400, New York University School of Medicine, 560 First Avenue, New York, NY, 10016, USA

    Lisa Mosconi

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  1. Lisa Mosconi
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Correspondence to Lisa Mosconi.

Electronic supplementary material

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Supplementary File 1

Diagram illustrating the first and last clinical examination, all PET scans, time of clinical change, and post-mortem examinations for every patient over time (years 1979–2004) (DOC 149 KB).

Supplementary File 2

FDG-PET scans showing medial temporal lobe (MTL) hypometabolism for each subject at the last PET scan, as compared to a healthy control with normal MTL CMRglc. The scans are reformatted to a plane parallel to the plane of the temporal lobe, a plane that runs approximately parallel to the long axis of the hippocampus at an infraorbital angulation of 20° to 25° negative to the canthomeatal plane. This axial orientation enables examination of the full anterior–posterior extent of the hippocampal region and most of the parahippocampal gyrus (Mosconi et al; Eur J Nucl Med Mol Imaging 2006; 33:210–21). CMRglc values are represented on a color-coded scale ranging from 0 to 50 μmol/100 g per minute (DOC 551 KB).

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Mosconi, L., Mistur, R., Switalski, R. et al. FDG-PET changes in brain glucose metabolism from normal cognition to pathologically verified Alzheimer’s disease. Eur J Nucl Med Mol Imaging 36, 811–822 (2009). https://doi.org/10.1007/s00259-008-1039-z

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  • DOI: https://doi.org/10.1007/s00259-008-1039-z

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