: The ability to predict the pathology spreading in patients with frontotemporal dementia (FTD) is crucial for early diagnosis and targeted interventions. This study examined the relationship between network vulnerability and longitudinal atrophy progression in FTD patients, using Network Diffusion Model (NDM) of pathology spread. Thirty behavioural-variant FTD (bvFTD), 13 semantic-variant primary progressive aphasia (svPPA), 14 nonfluent-variant PPA (nfvPPA) and 12 semantic behavioral variant FTD (sbvFTD) patients underwent longitudinal T1-weighted MRI. Fifty young controls (YC) (20-31 years) underwent multi-shell diffusion MRI scan. NDM was developed to model FTD pathology progression as a spreading process from a seed through the healthy structural connectome, using connectivity measures from fractional anisotropy (FA) and intra-cellular volume fraction (ICVF) in YC. Four disease epicenters were initially identified from the peaks of atrophy of each FTD variant: left insula (bvFTD), left temporal pole (svPPA), right temporal pole (sbvFTD) and left supplementary motor area (nfvPPA). Pearson's correlations were calculated between NDM-predicted atrophy in YC and the observed longitudinal atrophy in FTD patients over a follow-up of 24 months. The NDM was then run for all the 220 brain seeds to verify whether the four epicenters were among those that yielded the highest correlation. Using NDM, predictive maps in YC showed pathology progression from the peaks of atrophy in svPPA, nfvPPA, and sbvFTD over 24-months. svPPA exhibited early involvement of left temporal and occipital lobes, progressing to extensive left hemisphere impairment. nfvPPA and sbvFTD similarly spread bilaterally to frontal, sensorimotor, and temporal regions, with sbvFTD additionally affecting the right hemisphere. Moreover, the NDM-predicted atrophy of each region was positively correlated to longitudinal real atrophy, with a greater effect in svPPA and sbvFTD. In bvFTD, the model starting from the left insula (the peak of atrophy) demonstrated a highly left-lateralized pattern, with pathology spreading to frontal, sensorimotor, temporal, and basal ganglia regions, with minimal extension to the contralateral hemisphere by 24 months. However, unlike the atrophy peaks observed in the other three phenotypes, the left insula did not show the strongest correlation between the estimated and actual atrophy. Instead, the bilateral superior frontal gyrus emerged as optimal seeds for modelling atrophy spread, showing the highest correlation ranking in both hemispheres. Overall, NDM applied on ICVF connectome yielded higher correlations relative to NDM applied on FA maps. The NDM implementation using cross-sectional structural connectome is a valuable tool to predict atrophy patterns and pathology spreading in FTD clinical variants.

Modelling pathological spread through the structural connectome in the frontotemporal dementia clinical spectrum / Agosta, Federica; Basaia, Silvia; Spinelli, Edoardo G; Facente, Federica; Lumaca, Laura; Ghirelli, Alma; Canu, Elisa; Castelnovo, Veronica; Sibilla, Elisa; Tripodi, Chiara; Freri, Fabiola; Cecchetti, Giordano; Magnani, Giuseppe; Caso, Francesca; Verde, Federico; Ticozzi, Nicola; Silani, Vincenzo; Caroppo, Paola; Prioni, Sara; Villa, Cristina; Tremolizzo, Lucio; Appollonio, Ildebrando; Raj, Ashish; Filippi, Massimo. - In: BRAIN. - ISSN 0006-8950. - (In corso di stampa). [Epub ahead of print] [10.1093/brain/awae391]

Modelling pathological spread through the structural connectome in the frontotemporal dementia clinical spectrum

Agosta, Federica
Primo
;
Basaia, Silvia
Secondo
;
Spinelli, Edoardo G;Ghirelli, Alma;Castelnovo, Veronica;Tripodi, Chiara;Cecchetti, Giordano;Filippi, Massimo
Ultimo
In corso di stampa

Abstract

: The ability to predict the pathology spreading in patients with frontotemporal dementia (FTD) is crucial for early diagnosis and targeted interventions. This study examined the relationship between network vulnerability and longitudinal atrophy progression in FTD patients, using Network Diffusion Model (NDM) of pathology spread. Thirty behavioural-variant FTD (bvFTD), 13 semantic-variant primary progressive aphasia (svPPA), 14 nonfluent-variant PPA (nfvPPA) and 12 semantic behavioral variant FTD (sbvFTD) patients underwent longitudinal T1-weighted MRI. Fifty young controls (YC) (20-31 years) underwent multi-shell diffusion MRI scan. NDM was developed to model FTD pathology progression as a spreading process from a seed through the healthy structural connectome, using connectivity measures from fractional anisotropy (FA) and intra-cellular volume fraction (ICVF) in YC. Four disease epicenters were initially identified from the peaks of atrophy of each FTD variant: left insula (bvFTD), left temporal pole (svPPA), right temporal pole (sbvFTD) and left supplementary motor area (nfvPPA). Pearson's correlations were calculated between NDM-predicted atrophy in YC and the observed longitudinal atrophy in FTD patients over a follow-up of 24 months. The NDM was then run for all the 220 brain seeds to verify whether the four epicenters were among those that yielded the highest correlation. Using NDM, predictive maps in YC showed pathology progression from the peaks of atrophy in svPPA, nfvPPA, and sbvFTD over 24-months. svPPA exhibited early involvement of left temporal and occipital lobes, progressing to extensive left hemisphere impairment. nfvPPA and sbvFTD similarly spread bilaterally to frontal, sensorimotor, and temporal regions, with sbvFTD additionally affecting the right hemisphere. Moreover, the NDM-predicted atrophy of each region was positively correlated to longitudinal real atrophy, with a greater effect in svPPA and sbvFTD. In bvFTD, the model starting from the left insula (the peak of atrophy) demonstrated a highly left-lateralized pattern, with pathology spreading to frontal, sensorimotor, temporal, and basal ganglia regions, with minimal extension to the contralateral hemisphere by 24 months. However, unlike the atrophy peaks observed in the other three phenotypes, the left insula did not show the strongest correlation between the estimated and actual atrophy. Instead, the bilateral superior frontal gyrus emerged as optimal seeds for modelling atrophy spread, showing the highest correlation ranking in both hemispheres. Overall, NDM applied on ICVF connectome yielded higher correlations relative to NDM applied on FA maps. The NDM implementation using cross-sectional structural connectome is a valuable tool to predict atrophy patterns and pathology spreading in FTD clinical variants.
In corso di stampa
Connectomics
frontotemporal dementia
network spreading
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/173457
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