Objectives/hypothesis This study aimed to compare the predicted anatomy‐based frequency allocation of cochlear implant electrodes with the default standard frequencies. Study Design Retrospective study. Methods A retrospective analysis was performed using computed tomography (CT) images of patients who received cochlear implants at a tertiary referral center. Patients were excluded if they had any congenital or acquired cochlear anatomical anomalies. The CT images of the patients were uploaded to the surgical planning software. Two independent reviewers allocated the anatomical parameters of the cochlea. The software then used these parameters to calculate the frequency allocation for each electrode according to the type of electrode and the length of the organ of Corti (OC) in each patient. These anatomy‐based frequency allocations were compared with the default frequency settings. Main Outcome Measure Frequency‐to‐place mismatch in semitones. Results A total of 169 implanted ears in 102 patients were included in this study. The readings of the two reviewers were homogenous, with a Cronbach's alpha of 0.98. The mean anatomy‐based frequency allocation was 487.3 ± 202.9 Hz in electrode 1; 9,298.6 ± 490.6 Hz in electrode 12. The anatomy‐based frequency allocations were found to be significantly higher than the frequencies of the default frequencies for each corresponding electrode (one‐sample t‐test, P < .001). The frequency‐to‐place mismatch was negatively correlated with cochlear coverage and positively correlated with the cochlear duct length (Pearson correlation > 0.65, P < .003). Conclusions The anatomy‐based frequency allocation of each electrode is significantly different from the default frequency setting. This frequency‐to‐place mismatch was affected mainly by the cochlear coverage. Level of Evidence 3 Laryngoscope, 132:2224–2231, 2022

Objectives To study the changes in the coiled configuration of electrode excess lead in the mastoid cavity in the cochlear implant recipients over time. Methods Post-operative CT scans at two different appointments of fourteen patients with cochlear implants (CI) were retrospectively analyzed using a DICOM viewer software (3D-slicer). Mastoid thickness (MT) was measured in the oblique coronal plane from the round window (RW) entrance to the mastoid edge and inter-cochlear distance (ICD) was measured in the axial plane at the fundus level between two ears. 3D segmentation of the entire inner ear of both sides and coiled electrode excess lead was performed to visually compare the changes in coiled configuration between the two CT scan time points. Result MT and ICD increased logarithmically with the patient’s age, as has been measured from both the 1st and the 2nd CT scans and a weak linear correlation between MT and ICD was observed. Growth in MT and ICT measured between the time of 1st and 2nd CT scans showed a strong linear correlation. In eight cases, changes in the electrode excess lead have been observed in the 2nd CT scan, either a change in the coiling configuration of electrode excess lead or shifted laterally toward the mastoid edge. The ICD growth between the 1st and the 2nd CT scans was >2 mm in only seven cases and all of them were children. All other six cases had no observed changes in the coiled electrode lead. In addition, the mastoid growth between the 1st and the 2nd CT scan was >2.5 mm in only 4 cases. Conclusion Coiled configuration of electrode excess lead could change when the MT and ICD increased over time.

The mathematical equations to estimate cochlear duct length (CDL) using cochlear parameters such as basal turn diameter (A-value) and width (B-value) are currently applied for cochleae with two and a half turns of normal development. Most of the inner ear malformation (IEM) types have either  less than two and a half cochlear turns or have a cystic apex, making the current available CDL equations unsuitable for cochleae with abnormal anatomies. Therefore, this study aimed to estimate the basal turn length (BTL) from the cochlear parameters of different anatomical types, including normal anatomy; enlarged vestibular aqueduct; incomplete partition types I, II, and III; and cochlear hypoplasia. The lateral wall was manually tracked for 360° of the angular depth, along with the A and B values in the oblique coronal view for all anatomical types. A strong positive linear correlation was observed between BTL and the A- (r2 = 0.74) and B-values (r2 = 0.84). The multiple linear regression model to predict the BTL from the A-and B-values resulted in the following equation (estimated BTL = [A × 1.04] + [B × 1.89] − 0.92). The manually measured and estimated BTL differed by 1.12%. The proposed equation could be beneficial in adequately selecting an electrode that covers the basal turn in deformed cochleae.

This study aimed to validate the role of 3D segmentation in measuring the volume of the vestibular aqueduct (VAD), and the inner ear, and to study the correlation between VAD volume and VAD linear measurements at the midpoint and operculum. The correlation with other cochlear metrics was also studied. We retrospectively recruited 21 children (42 ears) diagnosed with Mondini dysplasia (MD) plus enlarged vestibular aqueduct (EVA) from 2009 to 2021 and who underwent cochlear implantation (CI). Patients’ sociodemographic data were collected, and linear cochlear metrics were measured using Otoplan. Vestibular aqueduct width and vestibular aqueduct and inner ear volumes were measured by two independent neuro-otologists using 3D segmentation software (version 4.11.20210226) and high-resolution CT. We also conducted a regression analysis to determine the association between these variables and CT VAD and inner ear volumes. Among the 33 cochlear implanted ears, 13 ears had a gusher (39.4%). Regarding CT inner ear volume, we found that gender, age, A-value, and VAD at the operculum were statistically significant (p-Value = 0.003, <0.001, 0.031, and 0.027, respectively) by regression analysis. Moreover, we found that Age, H value, VAD at the midpoint, and VAD at the operculum were significant predictors of CT VAD volume (p-Value < 0.04). Finally, gender (OR: 0.092; 95%CI: 0.009–0.982; p-Value = 0.048) and VAD at the midpoint (OR: 0.106; 95%CI: 0.015–0.735; p-Value = 0.023) were significant predictors of gusher risk. Patients’ gusher risk was significantly differentiated by gender and VAD width at the midpoint.