Harris, Michael S

ABSTRACT Objective To evaluate intracochlear electrocochleography (ECochG) amplitude parameters during cochlear implantation (CI) using a novel multi‐frequency ECochG algorithm. Methods A multi‐institutional, prospective cohort study was performed at 18 high‐volume CI centers. The inclusion criteria were adults with sensorineural hearing loss and audiometric thresholds of ≤ 90 dB hearing level at 500 Hz undergoing CI with Advanced Bionics (Valencia, CA) Ultra 3D devices between 2024 and 2025. ECochG recordings were performed with simultaneous multi‐frequency stimulation of four frequencies between 125 and 4000 Hz during cochlear implant insertion. Concurrent multi‐frequency recording allowed extraction of amplitude and phase of each frequency individually. Post hoc analysis was performed to determine the difference in the number of drop alarms between single‐ and multi‐frequency ECochG. An ECochG amplitude drop of 6 dB was defined as a drop alarm. Insertion track patterns were compared between single‐ and multi‐frequency ECochG. Results One hundred ninety‐five ears were included. Mean number of drop alarms for the single‐frequency algorithm was 1.72 (95% CI: 1.52, 1.92; median 1) compared to 0.42 (95% CI: 0.31, 0.53; median 0) for multi‐frequency; p < 0.001. The number of Type C patterns (rise in amplitude during insertion followed by a drop) decreased with the multi‐frequency ECochG algorithm compared to the single‐frequency ECochG algorithm. The number of Type D patterns (no‐response) decreased, indicating that multi‐frequency ECochG generated more responses across the cochlea than single‐frequency ECochG. Conclusions A novel multi‐frequency ECochG algorithm during CI is associated with fewer drop alarms and altered insertion track patterns, which may provide a more accurate assessment of the cochlear microenvironment. Level of Evidence 3.

AbstractObjectiveThis study investigated the comparative performance of ear, nose, and throat (ENT) physicians in correctly detecting ear abnormalities when reviewing digital otoscopy imaging using 3 different visualization methods, including computer‐assisted composite images called “SelectStitch,” single video frame “Still” images, and video clips. The study also explored clinicians' diagnostic confidence levels and the time to make a diagnosis.Study DesignClinician diagnostic reader study.SettingOnline diagnostic survey of ENT physicians.MethodsNine ENT physicians reviewed digital otoscopy examinations from 86 ears with various diagnoses (normal, perforation, retraction, middle ear effusion, tympanosclerosis). Otoscopy examinations used artificial‐intelligence (AI)‐based computer‐aided composite image generation from a video clip (SelectStitch), manually selected best still frame from a video clip (Still), or the entire video clip. Statistical analyses included comparisons of ability to detect correct diagnosis, confidence levels, and diagnosis times.ResultsThe ENT physicians' ability to detect ear abnormalities (33.2%‐68.7%) varied depending on the pathologies. SelectStitch and Still images were not statistically different in detecting abnormalities (P > .50), but both were different from Video (P < .01). However, the performance improvement observed with Videos came at the cost of significantly longer time to determining the diagnosis. The level of confidence in the diagnosis was positively associated with correct diagnoses, but varied by particular pathology.ConclusionThis study explores the potential of computer‐assisted techniques like SelectStitch in enhancing otoscopic diagnoses and time‐saving, which could benefit telemedicine settings. Comparable performance between computer‐generated and manually selected images suggests the potential of AI algorithms for otoscopy applications.

Objective Examine cochlear implant (CI) users' ability to identify safety‐relevant environmental sounds, imperative for safety, independence, and personal well‐being. Methods Twenty‐one experienced adult CI users completed an Environmental Sound Identification (ESI) test consisting of 42 common environmental sounds, 28 of which were relevant to personal safety, along with 14 control sounds. Prior to sound identification, participants were shown sound names and asked to rate the familiarity and, separately, relevance to safety of each corresponding sound on a 1–5 scale. Results Overall ESI accuracy was 57% correct for the safety‐relevant sounds and 55% correct for control sounds. Participants rated safety‐relevant sounds as more important to safety and more familiar than the non‐safety sounds. ESI accuracy significantly correlated with familiarity ratings. Conclusion The present findings suggest mediocre ESI accuracy in postlingual adult CI users for safety‐relevant and other environmental sounds. Deficits in the identification of these sounds may put CI listeners at increased risk of accidents or injuries and may require a specific rehabilitation program to improve CI outcomes. Level of Evidence 4 Laryngoscope , 133:2388–2393, 2023

ObjectivesExisting cochlear implant (CI) outcomes research demonstrates a high degree of variability in device effectiveness among experienced CI users. Increasing evidence suggests that verbal learning and memory (VL&M) may have an influence on speech recognition with CIs. This study examined the relations in CI users between visual measures of VL&M and speech recognition in a series of models that also incorporated spectro‐temporal discrimination. Predictions were that (1) speech recognition would be associated with VL&M abilities and (2) VL&M would contribute to speech recognition outcomes above and beyond spectro‐temporal discrimination in multivariable models of speech recognition.MethodsThis cross‐sectional study included 30 adult postlingually deaf experienced CI users who completed a nonauditory visual version of the California Verbal Learning Test‐Second Edition (v‐CVLT‐II) to assess VL&M, and the Spectral‐Temporally Modulated Ripple Test (SMRT), an auditory measure of spectro‐temporal processing. Participants also completed a battery of word and sentence recognition tasks.ResultsCI users showed significant correlations between some v‐CVLT‐II measures (short‐delay free‐ and cued‐recall, retroactive interference, and “subjective” organizational recall strategies) and speech recognition measures. Performance on the SMRT was correlated with all speech recognition measures. Hierarchical multivariable linear regression analyses showed that SMRT performance accounted for a significant degree of speech recognition outcome variance. Moreover, for all speech recognition measures, VL&M scores contributed independently in addition to SMRT.ConclusionMeasures of spectro‐temporal discrimination and VL&M were associated with speech recognition in CI users. After accounting for spectro‐temporal discrimination, VL&M contributed independently to performance on measures of speech recognition for words and sentences produced by single and multiple talkers.Level of Evidence3 Laryngoscope, 133:661–669, 2023

Abstract Objective The main purpose of this article is to determine if vestibular schwannoma consistency as determined by tissue intensity on T2-weighted magnetic resonance imagings (MRIs) is predictive of intraoperative experience and postoperative clinical outcomes. Study Design Retrospective chart review. Setting Tertiary referral center. Patients Seventy-seven patients diagnosed with vestibular schwannomas who were treated with microsurgical resection. Intervention Diagnostic. Main Outcome Measures Intraoperative measures include totality of resection, surgical time and cranial nerve VII stimulation and postoperative measures include House–Brackmann grade and perioperative complications. Results Tumor consistency determined via tissue intensity on MRI was only found to correlate with surgical time, with a softer tumor being associated with a longer surgical time (p < 0.0001). However, this was primarily driven by tumor volume with larger tumors being associated with longer surgical time based on multivariate analysis. None of the other intraoperative or postoperative measures considered were found to correlate with tumor consistency. Conclusions Tumor consistency determined by MRI is not predictive of intraoperative experience or postoperative outcomes in vestibular schwannomas. Tumor volume is the strongest driver of these outcome measures as opposed to tumor consistency.