4.7 Article

Amyloid vs FDG-PET in the differential diagnosis of AD and FTLD

Journal

NEUROLOGY
Volume 77, Issue 23, Pages 2034-2042

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1212/WNL.0b013e31823b9c5e

Keywords

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Funding

  1. National Institute on Aging [K23-AG031861, R01-AG027859, P01-AG1972403, P50-AG023501]
  2. State of California Department of Health Services Alzheimer's Disease Research Center of California [04-33516]
  3. Alzheimer's Association [NIRG-07-59422, ZEN-08-87090]
  4. John Douglas French Alzheimer's Foundation
  5. Consortium for Frontotemporal Dementia Research
  6. NIH/NIA
  7. Alzheimer's Association
  8. Emotional Brain (Oxford University Press)
  9. NIH (NIA, NINDS, DHS/ADP/ARCC)
  10. Larry L. Hillblom Foundation
  11. UCSF Pilot Research Award for Junior Investigators
  12. NIH (NCRR, NIA, NINDS, NCI)
  13. US Department of Defense
  14. National Multiple Sclerosis Society
  15. Genzyme Corporation
  16. US Department of Energy
  17. US Army Medical Research & Materiel Command
  18. NIH
  19. Takeda Pharmaceutical Company Ltd.
  20. Marian S. Ware Alzheimer Program
  21. NIH (NINDS, NIA)
  22. McBean Family Foundation
  23. James S. McDonnell Foundation
  24. John Douglas French Alzheimer's Disease Foundation
  25. publication of Behavioral Neurology of Dementia (Cambridge)
  26. Handbook of Neurology (Elsevier)
  27. Human Frontal Lobes (Guilford)
  28. Novartis
  29. State of California Alzheimer's Center

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Objective: To compare the diagnostic performance of PET with the amyloid ligand Pittsburgh compound B (PiB-PET) to fluorodeoxyglucose (FDG-PET) in discriminating between Alzheimer disease (AD) and frontotemporal lobar degeneration (FTLD). Methods: Patients meeting clinical criteria for AD (n = 62) and FTLD (n = 45) underwent PiB and FDG-PET. PiB scans were classified as positive or negative by 2 visual raters blinded to clinical diagnosis, and using a quantitative threshold derived from controls (n = 25). FDG scans were visually rated as consistent with AD or FTLD, and quantitatively classified based on the region of lowest metabolism relative to controls. Results: PiB visual reads had a higher sensitivity for AD (89.5% average between raters) than FDG visual reads (77.5%) with similar specificity (PiB 83%, FDG 84%). When scans were classified quantitatively, PiB had higher sensitivity (89% vs 73%) while FDG had higher specificity (83% vs 98%). On receiver operating characteristic analysis, areas under the curve for PiB (0.888) and FDG (0.910) were similar. Interrater agreement was higher for PiB (kappa = 0.96) than FDG (kappa = 0.72), as was agreement between visual and quantitative classification (PiB kappa = 0.88-0.92; FDG kappa = 0.64-0.68). In patients with known histopathology, overall classification accuracy (2 visual and 1 quantitative classification per patient) was 97% for PiB (n = 12 patients) and 87% for FDG (n = 10). Conclusions: PiB and FDG showed similar accuracy in discriminating AD and FTLD. PiB was more sensitive when interpreted qualitatively or quantitatively. FDG was more specific, but only when scans were classified quantitatively. PiB slightly outperformed FDG in patients with known histopathology. Neurology (R) 2011;77:2034-2042

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