Intraoperative Evaluation of Semiautomatic Localization of the Facial Nerve Using Diffusion Tensor Imaging in Patients with Large Vestibular Schwannomas: A Pilot Study.

Abstract

Background: Facial nerve damage remains a significant risk during vestibular schwannoma (VS) resection, with reported incidences varying widely (3-46%). Damage risk increases with tumor size. Digital tractography enables nerve reconstruction but typically involves manual procedures, resulting in subjective evaluations that limit reproducibility and validation. We introduce a robust, semi-automatic tractography methodology with reproducible region-of-interest (ROI) generation and present an initial validation using a novel quantitative three-dimensional comparison approach in patients with a large VS.

Objective: To assess the accuracy of facial nerve reconstruction employing a semi-automatic ROI selection method in patients with VSs.

Materials and methods: We included six patients with an average tumor size of 28 mm (95% CI: 17-40, 100% left) who underwent translabyrinthine VS surgery. Each VS patient was scanned with the regular neuronavigation magnetic resonance imaging (MRI) protocol and a custom diffusion-MRI protocol before surgery. The facial nerve trajectory was reconstructed with a diffusion tensor imaging-based tractography software package using semi-automatic ROI generation. We validated our reconstructions with the Brainlab neuronavigation system for intraoperative point annotation along the course of the facial nerve.

Results: Tracts could be reconstructed in all included patients. The median distance and angle between the points and closest reconstruction were 5.1 mm (IQR: 3.5-7.6) and 38.5 degrees (IQR: 2.7-79.8), respectively.

Conclusion: We present a promising methodology for facial nerve reconstruction in patients with VSs. However, further optimization of the methodology is warranted before a proper clinical validation study can be performed.