Combining Intraoperative Electrocochleography with Robotics-Assisted Electrode Array Insertion

OBJECTIVE

To describe the use of robotics-assisted electrode array (EA) insertion combined with intraoperative electrocochleography (ECochG) in hearing preservation cochlear implant surgery.

STUDY DESIGN

Prospective, single-arm, open-label study.

SETTING

All procedures and data collection were performed at a single tertiary referral center.

PATIENTS

Twenty-one postlingually deaf adult subjects meeting Food and Drug Administration indication criteria for cochlear implantation with residual acoustic hearing defined as thresholds no worse than 65 dB at 125, 250, and 500 Hz.

INTERVENTION

All patients underwent standard-of-care unilateral cochlear implant surgery using a single-use robotics-assisted EA insertion device and concurrent intraoperative ECochG.

MAIN OUTCOME MEASURES

Postoperative pure-tone average over 125, 250, and 500 Hz measured at initial activation and subsequent intervals up to 1 year afterward.

RESULTS

Twenty-two EAs were implanted with a single-use robotics-assisted insertion device and simultaneous intraoperative ECochG. Fine control over robotic insertion kinetics could be applied in response to changes in ECochG signal. Patients had stable pure-tone averages after activation with normal impedance and neural telemetry responses.

CONCLUSIONS

Combining robotics-assisted EA insertion with intraoperative ECochG is a feasible technique when performing hearing preservation implant surgery. This combined approach may provide the surgeon a means to overcome the limitations of manual insertion and respond to cochlear feedback in real-time.

Robotic assistance during cochlear implantation: the rationale for consistent, controlled speed of electrode array insertion

Cochlear implants (CI) have revolutionized the treatment of patients with severe to profound sensory hearing loss by providing a method of bypassing normal hearing to directly stimulate the auditory nerve. A further advance in the field has been the introduction of "hearing preservation" surgery, whereby the CI electrode array (EA) is carefully inserted to spare damage to the delicate anatomy and function of the cochlea. Preserving residual function of the inner ear allows patients to receive maximal benefit from the CI and to combine CI electric stimulation with acoustic hearing, offering improved postoperative speech, hearing, and quality of life outcomes. However, under the current paradigm of implant surgery, where EAs are inserted by hand, the cochlea cannot be reliably spared from damage. Robotics-assisted EA insertion is an emerging technology that may overcome fundamental human kinetic limitations that prevent consistency in achieving steady and slow EA insertion. This review begins by describing the relationship between EA insertion speed and generation of intracochlear forces and pressures. The various mechanisms by which these intracochlear forces can damage the cochlea and lead to worsened postoperative outcomes are discussed. The constraints of manual insertion technique are compared to robotics-assisted methods, followed by an overview of the current and future state of robotics-assisted EA insertion.

Middle Cranial Fossa Approach for Sporadic Vestibular Schwannoma

The middle fossa approach is an excellent technique for removing appropriate vestibular schwannomas in patients with serviceable hearing. Knowledge of the intricate middle fossa anatomy is essential for optimal outcomes. Gross total removal can be achieved with preservation of hearing and facial nerve function, both in the immediate and long-term periods. This article provides an overview of the background and indications for the procedure, a description of the operative protocol, and a summary of the literature on postoperative hearing outcomes.

Shortwave infrared otoscopy for diagnosis of middle ear effusions: a machine-learning-based approach

Otitis media, a common disease marked by the presence of fluid within the middle ear space, imparts a significant global health and economic burden. Identifying an effusion through the tympanic membrane is critical to diagnostic success but remains challenging due to the inherent limitations of visible light otoscopy and user interpretation. Here we describe a powerful diagnostic approach to otitis media utilizing advancements in otoscopy and machine learning. We developed an otoscope that visualizes middle ear structures and fluid in the shortwave infrared region, holding several advantages over traditional approaches. Images were captured in vivo and then processed by a novel machine learning based algorithm. The model predicts the presence of effusions with greater accuracy than current techniques, offering specificity and sensitivity over 90%. This platform has the potential to reduce costs and resources associated with otitis media, especially as improvements are made in shortwave imaging and machine learning.