2026 Proffered Presentations
S067: DIFFERENTIAL DISRUPTION OF FUNCTIONAL NETWORKS IN PATIENTS WITH VESTIBULAR SCHWANNOMA
Vratko Himic, MD; Richa Dahake, BS; Alan Ho, BS; Roxanne Mayrand, BS; Jay Chandhar, MD; Aparna Govindan, MD; Olivia Kalmanson, MD; Amy Wang, MD; Dagoberto Estevez-Ordonez, MD, PhD; Christine Dinh, MD; Ashish Shah, MD; Ricardo Komotar, MD; Carolina Benjamin, MD; Michael E Ivan, MD, MBS; University of Miami
Introduction: Functional connectomic analysis has been previously used to analyze the effects of intraparenchymal lesions on cortical networks. The impact of vestibular schwannomas (VS) is less well characterized. Given their location, and consequently their relatively large distance away from cortical networks, it would be interesting to qualify and quantify the extent to which networks are disrupted in patients with VS. Networks have been previously analyzed through tractographic and correlation analyses. However, the extent to which a network is adversely affected is less clear. This study aims to quantify the extent of network disruption across a case series of VS patients.
Objective: To describe a novel quantitative approach to analyze pre-operative network disruption in the functional connectome in patients with VS across eight networks: central executive, dorsal attention, default mode, language, salience, limbic/paralimbic, sensorimotor, and visual.
Methods: The functional connectome was derived from a combination of diffusion tensor imaging (DTI) and resting-state function magnetic resonance imaging (rs-fMRI). Pre-operative functional matrices were generated from the pre-operative functional MRI of four patients with VS using the Quicktome™ platform. Each patient generated two pre-operative datasets per network (one for each cerebral hemisphere), totaling eight matrices for each of the eight networks. Across 64 matrices, 44,752 different parcel-parcel connections were analyzed for anomalous connectivity; these were marked as anomalous if their connectivity was above or below a reference cohort of 2000 healthy patients; values exceeding ±2SD from the reference mean were flagged as anomalous. At a more granular level, these were categorized into extremely hypoconnected or hyperconnected based on their relation to the 2SD cut-off. We quantified the extent of network disruption by the percentage of each network’s total possible connections that were marked as anomalous. The Friedman test was used to assess differences between networks in the percentage of network disruption (%ND), and post-hoc analysis with Dunn-Bonferroni testing was used to discern pairwise differences.
Results: Across four VS patients, there was a statistically significant difference in the extent of pre-operative %ND (Friedman: χ2(7) = 17.23, p=0.0160) with no significant difference in post-hoc Dunn-Bonferroni testing. The most disrupted network was the central executive network (median %ND:1.87%, [IQR: 1.49-2.30%]) and the least disrupted was the limbic/paralimbic network (median %ND:0%, [IQR: 0-0.38%]). Hyperconnected anomalies did not differ significantly across networks. However, when assessing the contribution of hypoconnected anomalies to network disruption, there was both a difference between networks (Friedman: χ2(7) = 23.43, p=0.0014), with multiple comparison testing showing that the limbic network is significantly less disrupted compared to the dorsal attention (p=0.0012) and visual (p=0.0055) networks. Indeed, the limbic/paralimbic network had no hypoconnected anomalies.
Conclusion: The baseline pre-operative functional connectome in VS patients differs across cortical networks. Hypoconnected anomalies (those parcel-parcel connections that demonstrate extremes of connectivity at least 2SD less than the mean of a healthy population) contribute the most to this difference. Of these, the limbic/paralimbic network is the least disrupted and is the driver of the statistically significant differences across our cohort.
