Development of a Novel Algorithm for Tip Fold-Over Detection in Cochlear Implants and Evaluation on Bench and Multiple Clinical Data Bases.

Objectives: Tip fold-over (TFO) is a rare but critical occurrence in cochlear implant procedures where the electrode array folds back on itself within the cochlea, compromising programming and device performance. Timely intraoperative detection is essential for immediate correction and optimal placement. Electric field imaging (EFI) has shown promise for identifying TFO both intra- and post-operatively. This study evaluates the performance of a TFO detection algorithm implemented in Target CI (Version 1.6) using Advanced Bionics' cochlear implant systems, validated through bench and patient datasets. Methods: Sample data included (1) bench testing with a plastic cochlea and human temporal bones with and without induced TFOs, confirmed visually or radiographically; (2) intraoperative EFI measurements recorded using the AIM™ system, with electrode placement confirmed through imaging; and (3) historical EFI recordings from the Target CI DataLake, which lacks imaging and programming metadata. The TFO algorithm's performance was evaluated by assessing its sensitivity and specificity using these datasets. Results: The TFO algorithm achieved 100% sensitivity and specificity in bench models and intraoperative EFI with imaging-confirmed placements. Among 226 intra-op cases, four TFOs were confirmed by imaging, and all were correctly identified by the algorithm. In the large set of DataLake cases (14,734 implants), 0.80% were flagged as potential TFOs. TFO prevalence was higher with pre-curved arrays (1.22%) than straight lateral wall arrays (0.32%). Conclusions: The TFO algorithm showed high reliability with 100% sensitivity and specificity using routine clinical EFI data. While not a replacement for imaging, the TFO algorithm serves as a fast, accessible tool to alert clinicians to potential TFOs.