Abstract
Abstract
Purpose
Cochlear implantation in congenital inner ear malformations can be technically challenging due to the atypical anatomy which can limit electrode selection, trajectory, and insertion depth. Although high-resolution CT/MRI and planning tools (e.g., OTOPLAN
®
) support preoperative assessment, severe malformations may require additional validation. We evaluated whether robot-assisted insertion improves insertion performance in malformed cochleae using patient-specific 3D models.
Methods
High-resolution CT and/or MRI from 8 paediatric candidates were used to reconstruct and 3D print 16 cochleae (malformed cochleae plus one anatomically normal control with eighth nerve aplasia, as applicable). Four electrode arrays (MED-EL Medium, MED-EL Compressed, MED-EL Flex24, and Cochlear Straight) were inserted by an expert surgeon (P1), a novice surgeon (P2), and a robotic system (RobOtol
®
, R1). Outcomes were insertion completeness (complete/incomplete) and ease (easy/hard). Data were analysed using Firth’s penalized logistic regression and classification tree analysis. Preoperative prediction by P1 alone versus P1 + OTOPLAN
®
was compared using standard classification metrics.
Results
Electrode type and cochlear anatomy were the primary determinants of insertion outcomes. Electrode arrays with shorter active lengths (MED-EL Compressed) demonstrated higher insertion completeness in anatomically restricted malformed cochleae, whereas Flex24 and Cochlear Straight showed reduced completeness in restrictive hypoplastic cochleae. Operator identity, including robotic assistance, had minimal impact; ease was generally high. OTOPLAN
®
assisted planning improved prediction performance and reduced false-negative assessments.
Conclusion
In malformed cochleae, insertion completeness was influenced primarily by cochlear morphology and electrode characteristics within the outcome measures assessed. Patient-specific 3D models provide a useful platform for electrode–anatomy compatibility assessment and preoperative planning; however, clinical validation incorporating tonotopic coverage, audiological outcomes, and objective robotic performance metrics is warranted.