Biomarkers represent a critical research area in neurodegeneration disease as they can contribute to studying potential disease-modifying agents, fostering timely therapeutic interventions, and alleviating associated financial costs. Functional connectivity (FC) analysis represents a promising approach to identify early biomarkers in specific diseases. Yet, virtually no study has tested whether potential FC biomarkers prove to be reliable and reproducible across different centers. As such, their implementation remains uncertain due to multiple sources of variability across studies: the numerous international centers capable conducting FC research vary in their scanning equipment and their samples' socio-cultural background, and, more troublingly still, no gold-standard method exists to analyze FC. In this unprecedented study, we aim to address both issues by performing the first multicenter FC research in the behavioral-variant frontotemporal dementia (bvFTD), and by assessing multiple FC approaches to propose a gold-standard method for analysis. We enrolled 52 bvFTD patients and 60 controls from three international clinics (with different fMRI recording parameters), and three additional neurological patient groups. To evaluate FC, we focused on seed analysis, inter-regional connectivity, and several graph-theory approaches. Only graph-theory analysis, based on weighted-matrices, yielded consistent differences between bvFTD and controls across centers. Also, graph metrics robustly discriminated bvFTD from the other neurological conditions. The consistency of our findings across heterogeneous contexts highlights graph-theory as a potential gold-standard approach for brain network analysis in bvFTD.
- Frontotemporal dementia
- Functional connectivity
- Graph-theory and neurodegenerative diseases