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 (κ = 0.96) than FDG (κ = 0.72), as was agreement between visual and quantitative classification (PiB κ = 0.88-0.92; FDG κ = 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.
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 (κ = 0.96) than FDG (κ = 0.72), as was agreement between visual and quantitative classification (PiB κ = 0.88-0.92; FDG κ = 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.
Authors: E D Roberson; J H Hesse; K D Rose; H Slama; J K Johnson; K Yaffe; M S Forman; C A Miller; J Q Trojanowski; J H Kramer; B L Miller Journal: Neurology Date: 2005-09-13 Impact factor: 9.910
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Authors: Adam L Boxer; Michael Gold; Edward Huey; William T Hu; Howard Rosen; Joel Kramer; Fen-Biao Gao; Edward A Burton; Tiffany Chow; Aimee Kao; Blair R Leavitt; Bruce Lamb; Megan Grether; David Knopman; Nigel J Cairns; Ian R Mackenzie; Laura Mitic; Erik D Roberson; Daniel Van Kammen; Marc Cantillon; Kathleen Zahs; George Jackson; Stephen Salloway; John Morris; Gary Tong; Howard Feldman; Howard Fillit; Susan Dickinson; Zaven S Khachaturian; Margaret Sutherland; Susan Abushakra; Joseph Lewcock; Robert Farese; Robert O Kenet; Frank Laferla; Steve Perrin; Steve Whitaker; Lawrence Honig; Marsel M Mesulam; Brad Boeve; Murray Grossman; Bruce L Miller; Jeffrey L Cummings Journal: Alzheimers Dement Date: 2012-10-10 Impact factor: 21.566