Altered structural brain networks in linguistic variants of frontotemporal dementia

Nigro, S. Ló; Tafuri, Benedetta; Urso, Daniele; Blasi, Roberto De; Cedola, Alessia; Gigli, Giuseppe; Logroscino, Giancarlo

doi:10.1007/s11682-021-00560-2

Cited by 12 publications

(15 citation statements)

References 55 publications

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“…The global brain network organization of patients with svPPA was characterized by a decreased global efficiency and clustering coefficient, and a higher characteristic path length ( 15 , 22 ), which could reflect lower segregation and integration in the overall network organization. This finding was also confirmed by a recent study showing a reduced small-worldness index in the structural brain network of patients ( 28 ). At a local level, a reduced nodal efficiency, degree, and clustering coefficient have been observed in several brain regions, including the left middle and superior temporal gyri, entorhinal cortex, amygdala, fusiform, hippocampus, and insula ( 15 , 28 ).…”

Section: Network Alterations In Patients With Ftdsupporting

confidence: 85%

“…This finding was also confirmed by a recent study showing a reduced small-worldness index in the structural brain network of patients ( 28 ). At a local level, a reduced nodal efficiency, degree, and clustering coefficient have been observed in several brain regions, including the left middle and superior temporal gyri, entorhinal cortex, amygdala, fusiform, hippocampus, and insula ( 15 , 28 ). Moreover, a loss of hubs was observed in left-hemisphere regions ( 15 ).…”

Section: Network Alterations In Patients With Ftdsupporting

confidence: 85%

“…When FTD subtypes were directly compared, a lower global efficiency was observed in patients with nfvPPA relative to bvFTD but not to svPPA ( 22 ). Moreover, patients with nfvPPA presented a less small-worldness index than patients with svPPA ( 28 ). At local level, significant differences were observed only between PPA subtypes.…”

Section: Network Alterations In Patients With Ftdmentioning

confidence: 99%

“…More recently, several studies have applied advanced MRI acquisitions and analyses to obtain an in-depth characterization of brain alterations with respect to the simple gray matter atrophy. Particularly, an increasing number of studies have assessed brain connectivity through graph-theoretical methods, highlighting that this approach shows unique potentialities in FTD (14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29).…”

Section: Introductionmentioning

confidence: 99%

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The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia

et al. 2022

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Frontotemporal dementia (FTD) is a spectrum of clinical syndromes that affects personality, behavior, language, and cognition. The current diagnostic criteria recognize three main clinical subtypes: the behavioral variant of FTD (bvFTD), the semantic variant of primary progressive aphasia (svPPA), and the non-fluent/agrammatic variant of PPA (nfvPPA). Patients with FTD display heterogeneous clinical and neuropsychological features that highly overlap with those presented by psychiatric syndromes and other types of dementia. Moreover, up to now there are no reliable disease biomarkers, which makes the diagnosis of FTD particularly challenging. To overcome this issue, different studies have adopted metrics derived from magnetic resonance imaging (MRI) to characterize structural and functional brain abnormalities. Within this field, a growing body of scientific literature has shown that graph theory analysis applied to MRI data displays unique potentialities in unveiling brain network abnormalities of FTD subtypes. Here, we provide a critical overview of studies that adopted graph theory to examine the topological changes of large-scale brain networks in FTD. Moreover, we also discuss the possible role of information arising from brain network organization in the diagnostic algorithm of FTD-spectrum disorders and in investigating the neural correlates of clinical symptoms and cognitive deficits experienced by patients.

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Section: Network Alterations In Patients With Ftdsupporting

confidence: 85%

Section: Network Alterations In Patients With Ftdsupporting

confidence: 85%

Section: Network Alterations In Patients With Ftdmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia

et al. 2022

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“…Consistent with these studies, our study showed a prominent involvement of the caudal middle frontal gyrus, pars opercularis regions and caudate for PNFA vs. the controls classification model. Similarly, predominant involvement of temporal brain regions, i.e., temporal pole, hippocampus, and amygdala, was also observed for the classification between svPPA and control ( Gorno-Tempini et al, 2004 ; Rohrer et al, 2009b ; Bocchetta et al, 2019 ; Nigro et al, 2021a ).…”

Section: Discussionmentioning

confidence: 54%

Radiomics Model for Frontotemporal Dementia Diagnosis Using T1-Weighted MRI

et al. 2022

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Radiomics has been proposed as a useful approach to extrapolate novel morphological and textural information from brain Magnetic resonance images (MRI). Radiomics analysis has shown unique potential in the diagnostic work-up and in the follow-up of patients suffering from neurodegenerative diseases. However, the potentiality of this technique in distinguishing frontotemporal dementia (FTD) subtypes has so far not been investigated. In this study, we explored the usefulness of radiomic features in differentiating FTD subtypes, namely, the behavioral variant of FTD (bvFTD), the non-fluent and/or agrammatic (PNFA) and semantic (svPPA) variants of a primary progressive aphasia (PPA). Classification analyses were performed on 3 Tesla T1-weighted images obtained from the Frontotemporal Lobar Degeneration Neuroimaging Initiative. We included 49 patients with bvFTD, 25 patients with PNFA, 34 patients with svPPA, and 60 healthy controls. Texture analyses were conducted to define the first-order statistic and textural features in cortical and subcortical brain regions. Recursive feature elimination was used to select the radiomics signature for each pairwise comparison followed by a classification framework based on a support vector machine. Finally, 10-fold cross-validation was used to assess classification performances. The radiomics-based approach successfully identified the brain regions typically involved in each FTD subtype, achieving a mean accuracy of more than 80% in distinguishing between patient groups. Note mentioning is that radiomics features extracted in the left temporal regions allowed achieving an accuracy of 91 and 94% in distinguishing patients with svPPA from those with PNFA and bvFTD, respectively. Radiomics features show excellent classification performances in distinguishing FTD subtypes, supporting the clinical usefulness of this approach in the diagnostic work-up of FTD.

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Functional and structural network changes related with cognition in semantic dementia longitudinally

Lin

Cui

Chen

et al. 2023

Human Brain Mapping

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Longitudinal changes in the white matter/functional brain networks of semantic dementia (SD), as well as their relations with cognition remain unclear. Using a graph‐theoretic method, we examined the neuroimaging (T1, diffusion tensor imaging, functional MRI) network properties and cognitive performance in processing semantic knowledge of general and six modalities (i.e., object form, color, motion, sound, manipulation and function) from 31 patients (at two time points with an interval of 2 years) and 20 controls (only at baseline). Partial correlation analyses were carried out to explore the relationships between the network changes and the declines of semantic performance. SD exhibited aberrant general and modality‐specific semantic impairment, and gradually worsened over time. Overall, the brain networks showed a decreased global and local efficiency in the functional network organization but a preserved structural network organization with a 2‐year follow‐up. With disease progression, both structural and functional alterations were found to be extended to the temporal and frontal lobes. The regional topological alteration in the left inferior temporal gyrus (ITG.L) was significantly correlated with general semantic processing. Meanwhile, the right superior temporal gyrus and right supplementary motor area were identified to be associated with color and motor‐related semantic attributes. SD manifested disrupted structural and functional network pattern longitudinally. We proposed a hub region (i.e., ITG.L) of semantic network and distributed modality‐specific semantic‐related regions. These findings support the hub‐and‐spoke semantic theory and provide targets for future therapy.

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Altered structural brain networks in linguistic variants of frontotemporal dementia

Cited by 12 publications

References 55 publications

The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia

The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia

Radiomics Model for Frontotemporal Dementia Diagnosis Using T1-Weighted MRI

Functional and structural network changes related with cognition in semantic dementia longitudinally

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