Functional connectivity networks for preoperative brain mapping in neurosurgery

Area of Science:

• Neuroimaging
• Neurosurgery
• Systems Neuroscience

Background:

• Brain lesion resection aims to maximize tumor removal while preserving function.
• Resting-state functional MRI (fMRI) enables assessment of whole-brain connectivity networks without specific tasks.
• This shift allows for rapid, minimally engaging functional mapping.

Purpose of the Study:

• To assess the feasibility of fMRI-based mapping of functional connectivity networks in neurosurgical patients.
• To evaluate the benefits of resting-state connectivity mapping for surgical planning.
• To identify network alterations in patients with focal brain lesions.

Main Methods:

• Acquired resting-state fMRI using a 3-T scanner and multiecho echo-planar imaging.
• Applied independent component analysis and seed-based functional connectivity analysis (InstaCorr).
• Focused on 7 established networks and a language network centered on Broca's area in 5 glioblastoma patients.

Main Results:

• Successfully identified all 8 functional connectivity networks in every participant.
• Observed default mode network topological changes in all patients due to the tumor.
• Detected individual network abnormalities, including displacement, component loss, and region recruitment.

Conclusions:

• Resting-state fMRI reliably detects functional networks and alterations in glioblastoma patients.
• This mapping technique shows sensitivity for identifying network changes.
• Offers potential for investigating executive control, attention, and salience networks, aiding rehabilitation insights.