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• W4367302725 abstract "<h3>Objective:</h3> To investigate structural alterations in brain network of patients within the frontotemporal lobar degeneration (FTLD) spectrum using connectome analysis with advanced diffusion-weighted MRI metrics. <h3>Background:</h3> MRI connectomics is a promising tool to describe network-based degeneration in neurodegenerative diseases. Neurite orientation dispersion and density imaging (NODDI) has shown to provide novel insights on structural connectivity alterations. <h3>Design/Methods:</h3> Thirty-four behavioral-variant frontotemporal dementia (bvFTD), 11 semantic variant primary progressive aphasia (svPPA), 11 nonfluent (nfvPPA) patients and 48 healthy controls underwent multi-shell diffusion MRI. Fractional anisotropy (FA) maps were computed. Intra-cellular Volume Fraction (ICVF) maps were also estimated using NODDI, providing a direct quantification of neurite integrity. Graph analysis and connectomics assessed global and local structural topological network properties and regional structural connectivity. <h3>Results:</h3> Overall, widespread structural changes were observed in bvFTD patients relative to healthy controls and svPPA patients in terms of FA-derived network properties. nfvPPA patients also showed altered FA topological properties at global level compared to healthy controls. Sum of node weights (SN) in the sensorimotor lobe revealed that nfvPPA patients showed an altered connection strength compared to svPPA. Moreover, nfvPPA patients showed a significant decreased FA in the left hemispheric fronto-temporal-insular regions relative to controls. Considering ICVF, more severe alterations compared to FA maps allowed to find differences also between svPPA and nfvPPA patients. ICVF graph analysis measures also showed that svPPA had a lower degree centrality and SN in the temporal lobe compared to controls. <h3>Conclusions:</h3> These findings suggest that conventional diffusion-tensor measures might be sensitive enough to highlight vulnerable connections in the FTLD spectrum. However, ICVF demonstrated to be a more specific biomarker to differentiate FTLD syndromes. Specifically, the benefits emerged in the differentiation between svPPA patients and other groups. <b>Disclosure:</b> Federica Agosta has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Philips. Federica Agosta has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Elsevier INC. Silvia Basaia has nothing to disclose. Dr. Facente has nothing to disclose. Ms. Cividini has nothing to disclose. Dr. Spinelli has nothing to disclose. The institution of Elisa Canu has received research support from Italian Ministry of Health . Dr. Castelnovo has nothing to disclose. Giuseppe Magnani has nothing to disclose. Dr. Caso has nothing to disclose. Paola Caroppo has nothing to disclose. Sara Prioni has nothing to disclose. Miss Villa has nothing to disclose. Lucio Tremolizzo has nothing to disclose. Dr. Appollonio has nothing to disclose. Dr. Silani has nothing to disclose. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Bayer, Biogen Idec, Merck-Serono, Novartis, Roche, Sanofi Genzyme, Takeda, and Teva Pharmaceutical Industries. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving on a Speakers Bureau for Bayer, Biogen Idec, Merck-Serono, Novartis, Roche, Sanofi Genzyme, Takeda, and Teva Pharmaceutical Industries. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Springer Nature. The institution of Dr. Filippi has received research support from Biogen Idec, Merck-Serono, Novartis, Roche, Teva Pharmaceutical Industries, Italian Ministry of Health, Fondazione Italiana Sclerosi Multipla, and ARiSLA (Fondazione Italiana di Ricerca per la SLA)." @default.
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• W4367302725 date "2023-04-25" @default.
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• W4367302725 title "Characterization of FTLD spectrum through advanced diffusion-weighted MRI metrics: a connectome approach (P11-6.003)" @default.
• W4367302725 doi "https://doi.org/10.1212/wnl.0000000000203682" @default.
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