Synchrotron‐Based Trauma Assessment of Robotic Electrode Insertions in Cochlear Implantation
Bibliographic record
Abstract
OBJECTIVES: Minimizing intraoperative trauma during cochlear implant electrode insertion is crucial for preserving residual hearing. Manual insertions are subject to variability due to surgeon experience and anatomical differences, often leading to inconsistent outcomes. Robotic-assisted systems have been developed to improve insertion precision and reduce trauma. This study evaluates the safety and efficacy of the OTODRIVE system for cochlear implant electrode insertion. METHODS: Fifteen cadaveric human temporal bones were implanted with a variety of electrodes (FLEX26, FLEX28, FLEXSOFT, FLEX34) and an inner ear catheter (INCAT). The OTODRIVE system was used to maintain a constant insertion speed of 0.1 mm/s. The samples were subsequently imaged using synchrotron radiation phase-contrast imaging (SR-PCI) to assess intracochlear trauma. Parameters such as linear and angular insertion depths and cochlear coverage were measured. The presence of trauma was analyzed using a trauma evaluation plot. RESULTS: The average linear insertion depth was 24.8 ± 3.5 mm, and the average angular insertion depth was 527° ± 81°. Cochlear coverage was 74% ± 7%. Only one case of partial scala media translocation and two cases of basilar membrane elevation were observed, with no instances of severe trauma such as tip fold-over, scala vestibuli translocation, or osseous spiral lamina fracture. CONCLUSION: The findings indicate that the OTODRIVE system enables consistent and controlled electrode placement while minimizing trauma to cochlear structures, suggesting its potential to enhance hearing and structural preservation outcomes. Further clinical studies are required to establish the long-term benefits of robotic-assisted techniques over manual insertions in routine cochlear implantation. LEVEL OF EVIDENCE: N/A.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".