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Updated: Mar 7, 2026
Robotic Cochlear Implantation for Direct Cochlear Access
Published on: June 16, 2022
Population Statistics Approach for Safety Assessment in Robotic Cochlear Implantation
Tom Williamson1, Kate Gavaghan, Nicolas Gerber
1*ARTORG Center for Biomedical Engineering Research, University of Bern †Department of Otorhinolaryngology, Head and Neck Surgery ‡Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, Bern, Switzerland.
Hypothesis:
Descriptive statistics with respect to patient anatomy and image guidance accuracy can be used to assess the effectiveness of any system for minimally invasive cochlear implantation, on both an individual patient and wider population level.
Background:
Minimally invasive cochlear implantation involves the drilling of a tunnel from the surface of the mastoid to cochlea, with the trajectory passing through the facial recess. The facial recess anatomy constrains the drilling path and places prohibitive accuracy requirements on the used system. Existing single thresholds are insufficient for assessing the effectiveness of these systems.
Methods:
A statistical model of the anatomical situation encountered during minimally invasive drilling of the mastoid for cochlear implantation was developed. A literature review was performed to determine the statistical distribution of facial recess width; these values were confirmed through facial recess measurements on computed tomography (CT) data. Based on the accuracy of a robotic system developed by the authors, the effect of variation of system accuracy, precision, and tunnel diameter examined with respect to the potential treatable portion of the population.
Results:
A facial recess diameter of 2.54 ± 0.51 mm (n = 74) was determined from a review of existing literature; subsequent measurements on CT data revealed a facial recess diameter of 2.54 ± 0.5 mm (n = 23). The developed model demonstrated the effects of varying accuracy on the treatable portion of the population.
Conclusions:
The presented model allows the assessment of the applicability of a system on a wider population scale beyond examining only the system's ability to reach an arbitrary threshold accuracy.
