Abstract

PURPOSE: The present study aimed to explore the functional connectivity differences in Resting State Networks (RSNs) induced by cancer and chemotherapy in Lung Cancer (LC) patients using an Independent Component Analysis (ICA).
METHODS: Three matched groups of 15 LC following Chemotherapy (C+), 15 LC before Chemotherapy (C-) and 15 Healthy Controls (HC) were included. Analysis was performed using ICA and a multivariate pattern analysis (MVPA) was used to classify groups based on profiles of functional connectivity.
RESULTS: We found significant differences in four of the RSN identified: Default Mode Network (DMN), Predominantly Left and Right Anterior Temporal Network, and Cerebellum Network. Whereas DMN showed decreased connectivity, the other RSNs exhibited increased connectivity in both LC compared to HC and in C+ in comparison to C-. MVPA discriminated significantly and accurately between all groups.
CONCLUSIONS: Our study showed that disrupted functional connectivity associated with cancer and chemotherapy-induced cognitive deficits is not only related to DMN decreased connectivity abnormalities but also to an increased connectivity of other RSNs, suggesting a potential compensatory mechanism.