To determine MRI whole-brain connectometry differences in patients with no cognitive impairment, mild cognitive impairment (MCI), and dementia. All patients were scanned on a 3T MRI scanner and diffusion images were acquired using DTI sequences. Connectometry analysis was performed and FreeSurferDKT was used as the brain parcellation, and the connectivity matrix was calculated by using the count of the connecting tracks. The connectivity matrix and graph theoretical analysis was conducted using DSI Studio (available at http://dsi-studio.labsolver.org).
All patients underwent Montreal Cognitive Assessment (MoCA) and were divided into 3 groups - no cognitive impairment, mild cognitive impairment, and dementia.
Whole-brain network measures that were compared between groups were - density, clustering coefficient, transitivity, path length, small worldness, global efficiency, the diameter of the graph, the radius of a graph, assortativity coefficient, and rich club (with k values 5, 10, 15, 20, and 25). Patients with no cognitive impairment had higher connectome density, shorter path lengths, higher small worldness, better global efficiency, and higher rich club concentration compared with MCI patients and patients with dementia.
On the contrary patients with cognitive impairment had higher values of clustering coefficient and transitivity. MRI connectometry analysis could be used to aid in the diagnosis of MCI and dementia as well as to differentiate patients with no cognitive impairment, MCI, and dementia.
- 3.4. Other publications in conference proceedings (including local)