Vol. 28, No. 3, 2009
Issue release date: October 2009
Free Access
Dement Geriatr Cogn Disord 2009;28:259–266
(DOI:10.1159/000241879)
Original Research Article
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Performance of FDG PET for Detection of Alzheimer’s Disease in Two Independent Multicentre Samples (NEST-DD and ADNI)

Haense C.a, b · Herholz K.b · Jagust W.J.c · Heiss W.D.a
aMax Planck Institute for Neurological Research, Cologne, Germany; bWolfson Molecular Imaging Centre, University of Manchester, Manchester, UK; cSchool of Public Health and Helen Wills Neuroscience Institute, University of California, Berkeley, Calif., USA
email Corresponding Author


 goto top of outline Key Words

  • Alzheimer’s disease
  • Healthy control
  • 18F-FDG PET
  • Automated analysis
  • Discrimination analysis
  • Biomarker
  • NEST-DD
  • ADNI

 goto top of outline Abstract

Aim: We investigated the performance of FDG PET using an automated procedure for discrimination between Alzheimer’s disease (AD) and controls, and studied the influence of demographic and technical factors. Methods: FDG PET data were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) [102 controls (76.0 ± 4.9 years) and 89 AD patients (75.7 ± 7.6 years, MMSE 23.5 ± 2.1) and the Network for Standardisation of Dementia Diagnosis (NEST-DD) [36 controls (62.2 ± 5.0 years) and 237 AD patients (70.8 ± 8.3 years, MMSE 20.9 ± 4.4). The procedure created t-maps of abnormal voxels. The sum of t-values in predefined areas that are typically affected by AD (AD t-sum) provided a measure of scan abnormality associated with a preset threshold for discrimination between patients and controls. Results: AD patients had much higher AD t-sum scores compared to controls (p < 0.01), which were significantly related to dementia severity (ADNI: r = –0.62, p < 0.01; NEST-DD: r = –0.59, p < 0.01). Early-onset AD patients had significantly higher AD t-sum scores than late-onset AD patients (p < 0.01). Differences between databases were mainly due to different age distributions. The predefined AD t-sum threshold yielded a sensitivity and specificity of 83 and 78% in ADNI and 78 and 94% in NEST-DD, respectively. Conclusion: The automated FDG PET analysis procedure provided good discrimination power, and was most accurate for early-onset AD.

Copyright © 2009 S. Karger AG, Basel


 goto top of outline References
  1. American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders: DSM-IV. Washington, APA, 1994.
  2. Dubois B, Feldman HH, Jacova C, DeKosky ST, Barberger-Gateau P, Cummings J, Delacourte A, Galasko D, Gauthier S, Jicha G, Meguro K, O’Brien J, Pasquier F, Robert P, Rossor M, Salloway S, Stern Y, Visser PJ, Scheltens P: Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDS-ADRDA criteria. Lancet Neurol 2007;6:734–746.
  3. Herholz K: PET studies in dementia. Ann Nucl Med 2003;17:79–89.
  4. Alexander GE, Chen K, Pietrini P, Rapoport SI, Reiman EM: Longitudinal PET evaluation of cerebral metabolic decline in dementia: a potential outcome measure in Alzheimer’s disease treatment studies. Am J Psychiatry 2002;159:738–745.
  5. Foster NL, Chase TN, Mansi L, Brooks R, Fedio P, Patronas NJ, Di Chiro G: Cortical abnormalities in Alzheimer’s disease. Ann Neurol 1984;16:649–654.
  6. 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.
  7. 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;60:1374–1377.
  8. Drzezga A, Grimmer T, Riemenschneider M, Lautenschlager N, Siebner H, Alexopoulus P, Minoshima S, Schwaiger M, Kurz A: Prediction of individual clinical outcome in MCI by means of genetic assessment and (18)F-FDG PET. J Nucl Med 2005;46:1625–1632.
  9. Anchisi D, Borroni B, Franceschi M, Kerrouche N, Kalbe E, Beuthien-Beumann B, Cappa S, Lenz O, Ludecke S, Marcone A, Mielke R, Ortelli P, Padovani A, Pelati O, Pupi A, Scarpini E, Weisenbach S, Herholz K, Salmon E, Holthoff V, Sorbi S, Fazio F, Perani D: Heterogeneity of brain glucose metabolism in mild cognitive impairment and clinical progression to Alzheimer disease. Arch Neurol 2005;62:1728–1733.
  10. Hoffman JM, Welsh-Bohmer KA, Hanson M, Crain B, Hulette C, Earl N, Coleman RE: FDG PET imaging in patients with pathologically verified dementia. J Nucl Med 2000;41:1920–1928.
  11. Silverman DH, Small GW, Chang CY, Lu CS, Kung De Aburto MA, Chen W, Czernin J, Rapoport SI, Pietrini P, Alexander GE, Schapiro MB, Jagust WJ, Hoffman JM, Welsh-Bohmer KA, Alavi A, Clark CM, Salmon E, de Leon MJ, Mielke R, Cummings JL, Kowell AP, Gambhir SS, Hoh CK, Phelps ME: Positron emission tomography in evaluation of dementia: regional brain metabolism and long-term outcome. JAMA 2001;286:2120–2127.
  12. Silverman DHS, Cummings JL, Small GW, Gambhir SS, Chen W, Czernin J, Phelps ME: Added clinical benefit of incorporating 2-deoxy-2-[18F]fluoro-D-glucose with positron emission tomography into the clinical evaluation of patients with cognitive impairment. Mol Imaging Biol 2002;4:283–293.
  13. Herholz K, Salmon E, Perani D, Baron JC, Holthoff V, Frolich L, Schonknecht P, Ito K, Mielke R, Kalbe E, Zundorf G, Delbeuck X, Pelati O, Anchisi D, Fazio F, Kerrouche N, Desgranges B, Eustache F, Beuthien-Baumann B, Menzel C, Schroder J, Kato T, Arahata Y, Henze M, Heiss WD: Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. Neuroimage 2002;17:302–316.
  14. Minoshima S, Frey KA, Koeppe RA, Foster NL, Kuhl DE: A diagnostic approach in Alzheimer’s disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med 1995;36:1238–1248.
  15. 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;34:939–944.
  16. Folstein MF, Folstein SE, McHugh PR: ‘Mini-Mental State’: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189–198.
  17. Friston KJ, Ashburner J, Poline JB, Frith CD, Heather JD, Frachowiak RSJ: Spatial registration and normalisation of images. Hum Brain Mapp 1995;2:165–189.

    External Resources

  18. Herholz K, Carter SF, Jones M: Positron emission tomography imaging in dementia. Br J Radiol 2007;80:S160–S167.
  19. Ishii K, Kono AK, Sasaki H, Miyamoto N, Fukuda T, Sakamoto S, Mori E: Fully automatic diagnostic system for early- and late-onset mild Alzheimer’s disease using FDG PET and 3D-SSP. Eur J Nucl Med Mol Imaging 2006;33:575–583.
  20. DeCarli C, Murphy DG, Tranh M, Grady CL, Haxby JV, Gillette JA, Salerno JA, Gonzales-Aviles A, Horwitz B, Rapoport SI, Shapiro MB: The effect of white matter hyperintensity volume on brain structure, cognitive performance, and cerebral metabolism of glucose in 51 healthy adults. Neurology 1995;45:2077–2084.
  21. Mielke R, Herholz K, Grond M, Kessler J, Heiss WD: Severity of vascular dementia is related to volume of metabolically impaired tissue. Arch Neurol 1992;49:909–913.
  22. Lawlor BA, Ryan TM, Schmeidler J, Mohs RC, Davis KL: Clinical symptoms associated with age at onset in Alzheimer’s disease. Am J Psychiatry 1994;151:1646–1649.
  23. Kim EJ, Cho SS, Jeong Y, Park KC, Kang SJ, Kang E, Kim SE, Lee KH, Na DL: Glucose metabolism in early onset versus late onset Alzheimer’s disease: an SPM analysis of 120 patients. Brain 2005;128:1790–1801.
  24. Sakamoto S, Ishii K, Sasaki M, Hosaka K, Mori T, Matsui M, Hirono N, Mori E: Differences in cerebral metabolic impairment between early and late onset types of Alzheimer’s disease. J Neurol Sci 2002;200:27–32.
  25. Berg L, McKeel DW Jr, Miller JP, Storandt M, Rubin EH, Morris JC, Baty J, Coats M, Norton J, Goate AM, Price JL, Gearing M, Mirra SS, Saunders AM: Clinicopathologic studies in cognitively healthy aging and Alzheimer’s disease: relation of histologic markers to dementia severity, age, sex, and apolipoprotein E genotype. Arch Neurol 1998;55:326–335.
  26. Kemp PM, Holmes C, Hoffmann SM, Bolt L, Holmes R, Rowden J, Fleming JS: Alzheimer’s disease: Differences in technetium-99m HMPAO SPECT scan findings between early onset and late onset dementia. J Neurol Neurosurg Psychiatry 2003;74:715–719.
  27. Sullivan EV, Shear PK, Mathalon DH, Lim KO, Yesavage JA, Tinklenberg JR, Pfefferbaum A: Greater abnormalities of brain cerebrospinal fluid volumes in younger than in older patients with Alzheimer’s disease. Arch Neurol 1993;50:359–373.
  28. Herholz K, Salmon E, Perani D, Baron JC, Holthoff V, Frolich L, Ito K, Mielke R, Kalbe E, Zundorf G, Delbeuck X, Pelati O, Anchisi D, Fazio F, Kerrouche N, Calautti C, Beuthien-Baumann B, Menzel C, Schroder J, Kato T, Arahata Y, Henze M, Heiss WD: Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. Neuroimage 2002;17:302–316.
  29. Mosconi L, Tsui WH, Pupi A, De Santi S, Drzezga A, Minoshima S, de Leon MJ: 18F-FDG PET database of longitudinally confirmed healthy elderly individuals improves detection of mild cognitive impairment and Alzheimer’s disease. J Nucl Med 2007;48:1129–1134.
  30. Mintun MA, Larossa GN, Sheline YI, Dence CS, Lee SY, Mach RH, Klunk WE, Mathis CA, DeKosky ST, Morris JC: [11C]PIB in a nondemented population: potential antecedent marker of Alzheimer disease. Neurology 2006;67:446–452.
  31. Savva GM, Wharton SB, Ince PG, Forster G, Matthews FE, Brayne C: Age, neuropathology, and dementia. New Engl J Med 2009;360:2302–2309.
  32. de Leon MJ, Convit A, Wolf OT, Tarshish CY, DeSanti S, Rusinek H, Tsui W, Kandil E, Scherer AJ, Roche A, Imossi A, Thorn E, Bobinski M, Caraos C, Lesbre P, Schlyer D, Poirier J, Reisberg B, Fowler J: Prediction of cognitive decline in normal elderly subjects with 2-[(18)F]fluoro-2-deoxy-D-glucose/positron-emission tomography (FDG/PET). Proc Natl Acad Sci USA 2001;98:10966–10971.
  33. Mosconi L, De Santi S, Li J, Tsui WH, Li Y, Boppana M, Laska E, Rusinek H, de Leon MJ: Hippocampal hypometabolism predicts cognitive decline from normal aging. Neurobiol Aging 2008;29:676–692.
  34. Foster NL, Heidebrink JL, Clark CM, Jagust WJ, Arnold SE, Barbas NR, DeCarli CS, Turner RS, Koeppe RA, Higdon R, Minoshima S: FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer’s disease. Brain 2007;130:2616–2635.
  35. Mosconi L, Tsui WH, Herholz K, Pupi A, Drzezga A, Lucignani G, Reiman EM, Holthoff V, Kalbe E, Sorbi S, Diehl-Schmid J, Perneczky R, Clerici F, Caselli R, Beuthien-Baumann B, Kurz A, Minoshima S, de Leon MJ: Multicenter standardized 18F-FDG PET diagnosis of mild cognitive impairment, Alzheimer’s disease, and other dementias. J Nucl Med 2008;49:390–398.
  36. Habeck C, Foster NL, Perneczky R, Kurz A, Alexopoulos P, Koeppe RA, Drzezga A, Stern Y: Multivariate and univariate neuroimaging biomarkers of Alzheimer’s disease. Neuroimage 2008;40:1503–1515.
  37. Markiewicz PJ, Matthews JC, Declerck J, Herholz K: Robustness of multivariate image analysis assessed by resampling techniques and applied to FDG-PET scans of patients with Alzheimer’s disease. Neuroimage 2009;46:472–485.
  38. Salmon E, Kerrouche N, Perani D, Lekeu F, Holthoff V, Beuthien-Baumann B, Sorbi S, Lemaire C, Collette F, Herholz K: On the multivariate nature of brain metabolic impairment in Alzheimer’s disease. Neurobiol Aging 2009;30:186–197.
  39. Thal LJ, Kantarci K, Reiman EM, Klunk WE, Weiner MW, Zetterberg H, Galasko D, Pratico D, Griffin S, Schenk D, Siemers E: The role of biomarkers in clinical trials for Alzheimer disease. Alzheimer Dis Assoc Disord 2006;20:6–15.

 goto top of outline Author Contacts

Prof. Karl Herholz
University of Manchester, Wolfson Molecular Imaging Centre
27 Palatine Road
Manchester M20 3LJ (UK)
Tel. +44 161 275 0000, Fax +44 161 275 0003, E-Mail karl.herholz@manchester.ac.uk


 goto top of outline Article Information

Data used in the preparation of this article were obtained from the Network for Standardisation of Dementia Diagnosis (NEST-DD) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (www.loni.ucla.edu/ADNI). As such, the investigators within NEST-DD and ADNI contributed to the design and implementation of those studies and/or provided data, but did not participate in the analysis or writing of this report, except K.H. and W.J.J. (complete list of ADNI investigators available at: www.loni.ucla.edu/ADNI/About/About_InvestigatorsTable.shtml; NEST-DD principal investigators were D. Perani, Milan, S. Sorbi, Florence, E. Salmon, Liege, V. Holthoff, Dresden, and J.C. Baron, Caen).

Accepted: July 29, 2009
Published online: September 25, 2009
Number of Print Pages : 8
Number of Figures : 2, Number of Tables : 2, Number of References : 39
Additional supplementary material is available online - Number of Parts : 1


 goto top of outline Publication Details

Dementia and Geriatric Cognitive Disorders

Vol. 28, No. 3, Year 2009 (Cover Date: October 2009)

Journal Editor: Chan-Palay V. (New York, N.Y.)
ISSN: 1420-8008 (Print), eISSN: 1421-9824 (Online)

For additional information: http://www.karger.com/DEM


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