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. 2022 Jun;16(3):1113-1122.
doi: 10.1007/s11682-021-00560-2. Epub 2021 Nov 10.

Altered structural brain networks in linguistic variants of frontotemporal dementia

Affiliations

Altered structural brain networks in linguistic variants of frontotemporal dementia

Salvatore Nigro et al. Brain Imaging Behav. 2022 Jun.

Abstract

Semantic (svPPA) and nonfluent (nfvPPA) variants of primary progressive aphasia (PPA) have recently been associated with distinct patterns of white matter and functional network alterations in left frontoinsular and anterior temporal regions, respectively. Little information exists, however, about the topological characteristics of gray matter covariance networks in these two PPA variants. In the present study, we used a graph theory approach to describe the structural covariance network organization in 34 patients with svPPA, 34 patients with nfvPPA and 110 healthy controls. All participants underwent a 3 T structural MRI. Next, we used cortical thickness values and subcortical volumes to define subject-specific connectivity networks. Patients with svPPA and nfvPPA were characterized by higher values of normalized characteristic path length compared with controls. Moreover, svPPA patients had lower values of normalized clustering coefficient relative to healthy controls. At a regional level, patients with svPPA showed a reduced connectivity and impaired information processing in temporal and limbic brain areas relative to controls and nfvPPA patients. By contrast, local network changes in patients with nfvPPA were focused on frontal brain regions such as the pars opercularis and the middle frontal cortex. Of note, a predominance of local metric changes was observed in the left hemisphere in both nfvPPA and svPPA brain networks. Taken together, these findings provide new evidences of a suboptimal topological organization of the structural covariance networks in svPPA and nfvPPA patients. Moreover, we further confirm that distinct patterns of structural network alterations are related to neurodegenerative mechanisms underlying each PPA variant.

Keywords: Brain networks; Graph analysis; Gray matter structural covariance networks; Nonfluent variant of primary progressive aphasia; Semantic variant of primary progressive aphasia.

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Conflict of interest statement

The authors have no conflict of interest to disclose.

Figures

Fig. 1
Fig. 1
Left panel: cortical and subcortical brain regions showing reduced local properties between patients with semantic variant of primary progressive aphasia (svPPA) and controls (p < 0.05, Bonferroni corrected); Right panel:cortical and subcortical brain regions showing reduced local properties between patients with nonfluent variant of primary progressive aphasia (nfvPPA) and controls (p < 0.05, Bonferroni corrected). Node size is proportional to the effect size of the difference between patients and controls in local graph meausure
Fig. 2
Fig. 2
Cortical and subcortical brain regions showing local properties changes between patients with nonfluent variant of primary progressive aphasia (nfvPPA) and patients with semantic variant of primary progressive aphasia (svPPA)(p < 0.05, Bonferroni corrected). Node size is proportional to the effect size of the difference between patient groups
Fig. 3
Fig. 3
Top 20 ranked brain regions according to local brain measures in controls, patients with semantic variant of primary progressive aphasia (svPPA) and patients with nonfluent variant of primary progressive aphasia (nfvPPA)

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