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Accessing the stapedius muscle via novel surgical retrofacial approach during cochlear implantation surgery: Intraoperative results on feasibility and safety.

Orlando Guntinas-LichiusDirk ArnoldGerd Fabian VolkDaniela KorthRene AschenbachJohann-Martin HempelFritz SchneiderThore Schade-MannPhilipp GamerdingerAnke TropitzschHubert Löwenheim
Published in: PloS one (2022)
Human stapedius muscle (SM) can be directly and safely accessed via retrofacial approach, opening new approaches to directly measure the electrically evoked stapedius reflex threshold (eSRT). The measurement of the SM activity via direct surgical access represents a potential tool for objective eSRT fitting of cochlear implants (CI), increasing the benefit experienced by the CI users and leading to new perspectives in the development of smart implantable neurostimulators. 3D middle-ear reconstructions created after manual segmentation and related SM accessibility metrics were evaluated before the CI surgery for 16 candidates with assessed stapedius reflex. Retrofacial approach to access the SM was performed after facial recess exposure. In cases of poor exposition of SM, the access was performed anteriorly to the FN via drilling of the pyramidal eminence (PE). The total access rate of the SM via both the retrofacial and anterior approach of the FN was 100%. In 81.2% of cases (13/16), the retrofacial approach allowed to access the SM on previously categorized well exposed (8/8), partially exposed (4/5), and wholly concealed (1/3) SM with respect to FN. Following intraoperative evaluation in the remaining 18.8% (3/16), the SM was accessed anteriorly via drilling of the PE. Exposure of SM with respect to the FN and the sigmoid sinus's prominence was a predictor for the suitable surgical approach. The retrofacial approach offers feasible and reproducible access to the SM belly, opening direct access to electromyographic sensing of the eSRT. Surgical planner tools can quantitatively assist pre-surgical assessment.
Keyphrases
  • minimally invasive
  • endothelial cells
  • patients undergoing
  • machine learning
  • computed tomography
  • deep learning
  • magnetic resonance imaging
  • human health