BACKGROUND AND PURPOSE: Frontotemporal lobar degeneration (FTLD) is a primary neurodegenerative disease comprising 3 clinical subtypes: frontotemporal dementia (FTD), semantic dementia (SD), and progressive nonfluent aphasia (PNFA). The subdivision is primarily based on the characteristic clinical symptoms displayed by each subtype. We hypothesized that these symptoms would be correlated to characteristic patterns of brain atrophy, which could be indentified and used for subclassification of subjects with FTLD. MATERIALS AND METHODS: Volumes of 9 cortical regions were manually parcellated and measured on both hemispheres on 27 controls, 12 patients with FTD, 9 patients with PNFA, and 13 patients with SD. The volumetric data were analyzed by traditional t tests and by a multivariate discriminant analysis (partial least squares discriminant analysis). RESULTS: The ensemble or pattern of atrophy was a good discriminator in pair-wise comparison between the subtypes: FTD compared with SD (sensitivity 100% [12/12], specificity 100% [13/13]); FTD compared with PNFA (sensitivity 92% [11/12], specificity 89% [8/9]); and SD compared with PNFA (sensitivity 86% [11/13], specificity 100% [9/9]). Temporal-versus-frontal atrophy was the most important pattern for discriminating SD from the other 2 subtypes. Right-sided versus left-sided atrophy was the most important pattern for discriminating between subjects with FTD and PNFA. CONCLUSIONS: FTLD subtypes generally display a characteristic pattern of atrophy, which may be considered in diagnosing patients with FTLD.
BACKGROUND AND PURPOSE: Frontotemporal lobar degeneration (FTLD) is a primary neurodegenerative disease comprising 3 clinical subtypes: frontotemporal dementia (FTD), semantic dementia (SD), and progressive nonfluent aphasia (PNFA). The subdivision is primarily based on the characteristic clinical symptoms displayed by each subtype. We hypothesized that these symptoms would be correlated to characteristic patterns of brain atrophy, which could be indentified and used for subclassification of subjects with FTLD. MATERIALS AND METHODS: Volumes of 9 cortical regions were manually parcellated and measured on both hemispheres on 27 controls, 12 patients with FTD, 9 patients with PNFA, and 13 patients with SD. The volumetric data were analyzed by traditional t tests and by a multivariate discriminant analysis (partial least squares discriminant analysis). RESULTS: The ensemble or pattern of atrophy was a good discriminator in pair-wise comparison between the subtypes: FTD compared with SD (sensitivity 100% [12/12], specificity 100% [13/13]); FTD compared with PNFA (sensitivity 92% [11/12], specificity 89% [8/9]); and SD compared with PNFA (sensitivity 86% [11/13], specificity 100% [9/9]). Temporal-versus-frontal atrophy was the most important pattern for discriminating SD from the other 2 subtypes. Right-sided versus left-sided atrophy was the most important pattern for discriminating between subjects with FTD and PNFA. CONCLUSIONS:FTLD subtypes generally display a characteristic pattern of atrophy, which may be considered in diagnosing patients with FTLD.
Authors: Olof Lindberg; Mark Walterfang; Jeffrey C L Looi; Nikolai Malykhin; Per Ostberg; Bram Zandbelt; Martin Styner; Beatriz Paniagua; Dennis Velakoulis; Eva Orndahl; Lars-Olof Wahlund Journal: J Alzheimers Dis Date: 2012 Impact factor: 4.472
Authors: J C L Looi; L Svensson; O Lindberg; B B Zandbelt; P Ostberg; E Orndahl; L-O Wahlund Journal: AJNR Am J Neuroradiol Date: 2009-06-04 Impact factor: 3.825
Authors: Mark Walterfang; Eileen Luders; Jeffrey C L Looi; Priya Rajagopalan; Dennis Velakoulis; Paul M Thompson; Olof Lindberg; Per Ostberg; Love E Nordin; Leif Svensson; Lars-Olof Wahlund Journal: J Alzheimers Dis Date: 2014 Impact factor: 4.472
Authors: Jonathan D Rohrer; Matthew J Clarkson; Raivo Kittus; Martin N Rossor; Sebastien Ourselin; Jason D Warren; Nick C Fox Journal: J Alzheimers Dis Date: 2012 Impact factor: 4.472
Authors: Katya Rascovsky; John R Hodges; David Knopman; Mario F Mendez; Joel H Kramer; John Neuhaus; John C van Swieten; Harro Seelaar; Elise G P Dopper; Chiadi U Onyike; Argye E Hillis; Keith A Josephs; Bradley F Boeve; Andrew Kertesz; William W Seeley; Katherine P Rankin; Julene K Johnson; Maria-Luisa Gorno-Tempini; Howard Rosen; Caroline E Prioleau-Latham; Albert Lee; Christopher M Kipps; Patricia Lillo; Olivier Piguet; Jonathan D Rohrer; Martin N Rossor; Jason D Warren; Nick C Fox; Douglas Galasko; David P Salmon; Sandra E Black; Marsel Mesulam; Sandra Weintraub; Brad C Dickerson; Janine Diehl-Schmid; Florence Pasquier; Vincent Deramecourt; Florence Lebert; Yolande Pijnenburg; Tiffany W Chow; Facundo Manes; Jordan Grafman; Stefano F Cappa; Morris Freedman; Murray Grossman; Bruce L Miller Journal: Brain Date: 2011-08-02 Impact factor: 13.501