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Reducing structural damage and adverse surgical events during cochlear implantation using an intraoperative sensing system

$1,297,496R44FY2025DCNIH

Advanced Optronics, Inc., Pittsburgh PA

Investigators

Abstract

SUMMARY/ABSTRACT Cochlear implants (CIs) restore hearing via direct electrical stimulation of the auditory nerve. Currently, the surgeon must blindly thread an ultra-thin CI electrode array into the spiral-shaped cochlea, risking structural damage that destroys residual acoustic hearing and impacts speech intelligibility outcomes. This loss of residual hearing occurs in about 50% of operations, is identified by the FDA as an important implant-related risk, and contributes to low CI adoption rates. Currently, only about 5% of eligible CI candidates receive a CI in the US. Measurable characteristics of electrode insertion, including position and force, are linked to surgical outcomes such as speech perception and structural damage, providing a pathway for ameliorating these risks. Presently, these features are sensed manually & qualitatively by the surgeon during CI insertion, with adjustments in technique depending heavily on subjective experience and surgeon dexterity. To address this significant clinical gap, Advanced Optronics, Inc. (AO) is developing the “Sixth Sense” Surgical Guidance System, which uses a sensor-enabled CI electrode to generate quantitative data for surgeons to utilize in real-time during electrode insertion. With instantaneous metrics regarding the trajectory of the intracochlear electrode and the forces it endures, the surgeon can make data-driven micro-adjustments that optimize electrode placement, minimize structural damage, and improve the surgical outcomes for patients. The system integrates 3 primary components: (i) a flexible micro-electromechanical systems (MEMS) strain sensor to detect changes in the CI electrode, (ii) ML models to transform the raw strain into clinically relevant metrics, and (iii) hardware to collect and process the data and display information to surgeons in real-time. This Phase II proposal builds on our successful Phase I SBIR effort, which developed a benchtop prototype system, completed component-level optimization, and demonstrated feasibility. The next major steps to allow system validation and successful product introduction to the end-user (surgeon) are (1) Refinement & optimization of the CI sensor system and validation of performance; (2) ML Sim2Real transfer for electrode state detection and clinical event detection; and (3) a Powered cadaver study for validation and data collection with the integrated CI system. Aims 1 and 2 are parallel, yet synergistic: ML models will identify critical features of insertion; sensor design iterations will detect these features; and the process will be repeated and re-evaluated. This will result in an optimized hardware platform of a sensor-enabled CI electrode, featuring an optimized sensor design to provide detailed real-time information on the electrode state paired with optimized ML models to interpret the raw strain data and generate clinically relevant features. The final outcome of the validation study will be the demonstration of reduced intracochlear trauma via histological analysis using the 5-point Eshraghi scale. The successful outcome of this Phase II effort will result in the design freeze of the CI system and end user validation, producing a translation-ready device in preparation for out-licensing and adoption by CI companies for real-world use.

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