Neural networks in frontotemporal dementia—A meta-analysis
Introduction
Recent studies suggest that frontotemporal lobar degeneration is the second most common diagnosis of dementia in individuals younger than 65 years (Johnson et al., 2005). However, several factors have limited research into this disease. The size of cohorts is modest at any one center. Furthermore, until recently, diagnostic accuracy was low. Recent establishment of consensus criteria for frontotemporal lobar degeneration (The Lund and Manchester Groups, 1994; Neary et al., 1998) represents an opportunity to begin large-scale studies. Criteria suggested previously divide frontotemporal lobar degeneration into three major subgroups: frontotemporal dementia (FTD), semantic dementia, and progressive non-fluent aphasia (Neary et al., 1998). FTD, the most common subtype, is characterized by alterations in behavior and personality, namely decline in social interpersonal conduct, impairment in regulation of personal conduct, emotional blunting, and loss of insight (‘diagnostic core features’ (Neary et al., 1998)). Moreover, FTD patients are impaired in social cognition (Gregory et al., 2002, Lough et al., 2006). Both other subtypes lack in their early stages behavioral impairments, rather language domain is mainly affected (Neary et al., 1998, Snowden et al., 1996).
Although FTD is clinically well characterized (Neary et al., 1998), and several hints for specific cognitive deficits were recently published, there is still controversy with regard to the neural basis of disease. Some authors proposed in their brain imaging criteria that FTD is characterized by bilateral impairment in (pre-)frontal and anterior temporal brain regions, whereas others related FTD specifically to frontal lobes and, hence called it frontal variant of frontotemporal lobar degeneration (Perry and Hodges, 2000). Accordingly, one aim of our study was to focus neural impairments in FTD to specific brain regions. Moreover, we wanted to place FTD in a framework of cognitive neuropsychiatry by relating the neural deficits to clinical and cognitive impairments (Halligan and David, 2001). Because patients with FTD show particularly alterations in behavior, personality, and social cognition (Gregory et al., 2002, Lough et al., 2006, Neary et al., 1998), we hypothesized impairments in anterior medial frontal neural networks (Gallagher and Frith, 2003).
As size of cohorts is modest in recently published studies we conducted a systematic function/location meta-analysis including morphometric studies with magnetic resonance imaging (MRI) and functional imaging studies applying (18F) fluorodeoxyglucose positron emission tomography (FDG-PET) (Fox et al., 1998). We chose the method developed by Turkeltaub et al. (2002) as it enables a quantitative meta-analytic approach.
Section snippets
General study selection criteria
MedLine and Current Contents search engines were used to identify studies on morphometry and glucose utilization in FTD. The following search strategy was applied: ((frontotemporal AND dementia) OR Pick) AND (PET OR MRT OR MRI). Studies were included if they fulfilled the following criteria: (1) published between 1980 and 2005, (2) peer-reviewed, (3) patients diagnosed according to internationally recognized diagnostic criteria (The Lund and Manchester Groups, 1994; Neary et al., 1998, Perry
Results
Fig. 1 shows maxima of studies, which were included in the meta-analysis. Note that several maxima are superimposed, and that shifting maxima on the z-axis to the respective slices for illustration purposes may have led to virtual localization outside the brain. Coordinates of maxima are described in detail in Appendix A. Results of the quantitative meta-analysis are summarized in Table 2 and illustrated in Fig. 2, if studies applying FDG-PET and MRI are pooled. Seven significant
Discussion
Our study supports previous notions classifying FTD as frontal variant of frontotemporal lobar degeneration (Perry and Hodges, 2000). More specifically, data confirm our hypothesis that FTD affects mainly frontomedian structures that are relatively spared in normal aging (Grieve et al., 2005, Raz et al., 2004, Salat et al., 2004). In the following, we want to place anatomical impairments in a framework of cognitive neuropsychiatry by relating neural networks to cognitive functions (Halligan and
Acknowledgments
The authors thank Evelyn Ferstl and Kirsten Volz for discussing the manuscript, and Stephan Liebig for help in preparing the figures.
Disclosure statement: There are no actual or potential conflicts of interest for any of the authors.
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