Modelling pathological spread through the structural connectome in the frontotemporal dementia clinical spectrum
Authors: 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 
Published: November 2024

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.