The current grading of facial nerve function is based on subjective impression with the established assessment scale of House and Brackmann (HB). Especially for research a more objective method is needed to lower the interobserver variability to a minimum. We developed a semi-automated grading system based on (facial) surface EMG-data measuring the facial nerve function of 28 patients with vestibular schwannoma surgery. The sEMG was recorded preoperatively, postoperatively and after 3-12 months. In addition, the HB grade was determined. After manual selection and preprocessing, the data were subjected to machine learning classificators (Logistic regression, SVM and KNN). Lateralization indices were calculated and multivariant machine learning analysis was performed according to three scenarios [differentiation of normal (1) and slight (2) vs. impaired facial nerve function and classification of HB 1-3 (3)]. The calculated AUC for each scenario showed overall good differentiation capability with a median AUC of 0.72 for scenario 1, 0.91 for scenario 2 and multiclass AUC of 0.74 for scenario 3. This study approach using sEMG and machine learning shows feasibility regarding facial nerve grading in perioperative VS-surgery setting. sEMG may be a viable alternative to House Brackmann regarding objective evaluation of facial function especially for research purposes.

Facial nerve damage in vestibular schwannoma surgery is associated with A-train patterns in free-running EMG, correlating with the degree of postoperative facial palsy. However, anatomy, preoperative functional status, tumor size and occurrence of A-trains clusters, i.e., sudden A-trains in most channels may further contribute. In the presented study, we examine neural networks to estimate postoperative facial function based on such features.

Nimodipine is well characterized for the management of SAH (subarachnoid hemorrhage) and has been shown to promote a better outcome and less DIND (delayed ischemic neurological deficits). In rat experiments, enhanced axonal sprouting and higher survival of motoneurons was demonstrated after cutting or crushing the facial nerve by nimodipine. These results were confirmed in clinical trials following vestibular Schwannoma surgery. The mechanism of the protective competence of nimodipine is unknown. Therefore, in this study, we established an in vitro model to examine the survival of Neuro2a cells after different stress stimuli occurring during surgery with or without nimodipine. Nimodipine significantly decreased ethanol-induced cell death of cells up to approximately 9% in all tested concentrations. Heat-induced cell death was diminished by approximately 2.5% by nimodipine. Cell death induced by mechanical treatment was reduced up to 15% by nimodipine. Our findings indicate that nimodipine rescues Neuro2a cells faintly, but significantly, from ethanol-, heat- and mechanically-induced cell death to different extents in a dosage-dependent manner. This model seems suitable for further investigation of the molecular mechanisms involved in the neuroprotective signal pathways influenced by nimodipine.