RESTING STATE EXECUTIVE CONTROL AND SALIENCE NETWORK CONNECTIVITY IN CLINICALLY STABLE LOWER GRADE GLIOMA COVARIES WITH COGNITIVE PERFORMANCE

Abstract BACKGROUND Survival outcomes for patients with lower grade gliomas (LrGG) are improving. However, injury from tumor growth and consequences of treatment often leads to impaired cognition, particularly in cognitive domains reliant on distributed functional networks and intact white-matter tracts. Resting state functional MRI (rsfMRI) is a method of investigating the integrity of these functional networks. METHODS This study investigated rsfMRI connectivity in 21 patients with clinically stable LrGG compared to age- and gender-matched healthy controls, and associated imaging measures with cognitive outcomes. Data were acquired for 12 cognitive tests administered within one week of imaging. RsfMRI and T1-weighted images for 21 research controls were acquired from OpenNeuro datasets. RsfMRI data were processed and analyzed using the CONN toolbox using CONN’s standard regions of interest (ROI) for the 8 canonical networks as seeds, and cognitive test scores as covariates, with a threshold for T tests of p< .001 uncorrected. RESULTS Median age was 48 years old (range 27-67). There were 6 astrocytomas, IDHmut; 3 astrocytomas IDH-wt, 8 oligodendrogliomas, and 4 NOS. Thirteen had left hemisphere tumors (8 frontal, 3 parietal, 2 temporal), and 6 right (5 frontal, 1 temporal). Fourteen had previously recieved radiotherapy. There was significantly lower connectivity in frontoparietal executive control and the salience networks in LrGG patients versus controls. Within patients, lower executive control network connectivity covaried with worse performance on executive measures (FAS, Tower of London, Trails-A, Animal Naming, FrSBe), and attention and working memory measures (Digit Symbol, HVLT). Lower salience network connectivity covaried with poorer performance on executive measures (FrSBe, FAS) and attention and working memory measures (Digit Span, HVLT, WAIS-WM). CONCLUSION In clinically stable LrGG, rsfMRI measures of network connectivity are potentially useful markers to monitor and track, given the concordance with cognition, and could help guide cognitive assessment and rehabilitation.