Objective: In the field of cochlear implantation, the current trend toward patient‐specific electrode selection and the achievement of optimal audiologic outcomes has resulted in implant manufacturers developing a large portfolio of electrodes. The aim of this study was to bridge the gap between the known variability of cochlea length and this electrode portfolio.Design: Retrospective analysis on cochlear length and shape in micro–computed tomography and cone beam computed tomography data.Setting: Tertiary care medical center.Subjects and Methods: A simple 2‐step approach was developed to accurately estimate the individual cochlear length as well as the projected length of an electrode array inside the cochlea. The method is capable of predicting the length of the cochlea and the inserted electrode length at any specific angle. Validation of the approach was performed with 20 scans of human temporal bones (micro–computed tomography) and 47 pre‐ and postoperative clinical scans (cone beam computed tomography).Results: Mean ± SD absolute errors in cochlear length estimations were 0.12 ± 0.10 mm, 0.38 ± 0.26 mm, and 0.71 ± 0.43 mm for 1, 1.5, and 2 cochlea turns, respectively. Predicted insertion angles based on clinical cone beam computed tomography data showed absolute deviations of 27° ± 18° to the corresponding postoperative measurements.Conclusion: With accuracy improvements of 80% to 90% in comparison with previously proposed approaches, the method is well suited for the use in individualized cochlear implantation.

Objective: Within the field of cochlear implantation (CIs), the role of utilizing patient-specific cochlear anatomy for choosing the optimal implant electrode is becoming increasingly important. Unfortunately, performing detailed anatomical measurements of a cochlea using clinical imaging data is rather time consuming and hence difficult to implement into the clinical routine. In order to accelerate clinical cochlear anatomy evaluations, previously developed mathematical models can be adjusted to the patient-specific anatomy by measuring just a few overall cochlear dimensions. However, the accuracy of model-based cochlear anatomy estimations is unclear, and incorrect evaluations may lead to false conclusions regarding the suitability of specific implant electrodes. Methods: Based on 10 cochleae, an error evaluation of various commonly used curve fitting approaches for cochlear shape and duct length approximation was conducted. Spline tracings of the cochlear contours were used as reference values for the various approximations. Results: Parameterized average cochlear helix models and two of five analytical approaches were found to be suitable for reconstructing the cochlear helical shape and estimating its length. Discussion: Spline curve reconstructions are the most accurate and reliable method for assessing patient-specific cochlear geometry, especially in the case of anatomical irregularities. The most accurate results within the group of model-based evaluations still resulted in mean overall cochlear length deviations of approximately 5%. Conclusion: Spline curve reconstructions appear to be the best option for anatomical diagnostics in clinical practice. Retrospective studies can be performed to further evaluate model-based evaluations.

In cochlear implantation, current preoperative planning procedures allow for estimating how far a specific implant will reach into the inner ear of the patient, which is important to optimize hearing preservation and speech perception outcomes. Here we report on the development of a methodology that goes beyond current planning approaches: the proposed model does not only estimate specific outcome parameters but allows for entire, three-dimensional virtual implantations of patient-specific cochlear anatomies with different types of electrode arrays. The model was trained based on imaging datasets of 186 human cochleae, which contained 171 clinical computer tomographies (CTs) of actual cochlear implant patients as well as 15 high-resolution micro-CTs of cadaver cochleae to also reconstruct the refined intracochlear structures not visible in clinical imaging. The model was validated on an independent dataset of 141 preoperative and postoperative clinical CTs of cochlear implant recipients and outperformed all currently available planning approaches, not only in terms of accuracy but also regarding the amount of information that is available prior to the actual implantation.

Objectives: (1) To assess variations of the human intracochlear anatomy and quantify factors which might be relevant for cochlear implantation (CI) regarding surgical technique and electrode design. (2) Search for correlations of these factors with clinically assessable measurements. Design: Human temporal bone study with micro computed tomography (μCT) data and analysis of intracochlear geometrical variations: μCT data of 15 fresh human temporal bones was generated, and the intracochlear lumina scala tympani (ST) and scala vestibuli were manually segmented using custom software specifically designed for accurate cochlear segmentation. The corresponding datasets were processed yielding 15 detailed, three-dimensional cochlear models which were investigated in terms of the scalae height, cross-sectional size, and rotation as well as the interrelation of these factors and correlations to others. Results: The greatest anatomical variability was observed within the round window region of the cochlea (basal 45°), especially regarding the cross-sectional size of the ST and its orientation relative to the scala vestibuli, which were found to be correlated (p < 0.001). The cross-sectional height of the ST changes substantially for both increasing cochlear angles and lateral wall distances. Even small cochleae were found to contain enough space for all commercially available CI arrays. Significant correlations of individual intracochlear parameters to clinically assessable ones were found despite the small sample size. Conclusion: While there is generally enough space within the ST for CI, strong intracochlear anatomical variations could be observed highlighting the relevance of both soft surgical technique as well as a highly flexible and self-adapting cochlear implant electrode array design. Cochlear dimensions (especially at the round window) could potentially be used to indicate surgically challenging anatomies.

Purpose: A cochlea modeling approach is presented allowing for a user defined degree of geometry simplification which automatically adjusts to the patient specific anatomy. Model generation can be performed in a straightforward manner due to error estimation prior to the actual generation, thus minimizing modeling time. Therefore, the presented technique is well suited for a wide range of applications including finite element analyses where geometrical simplifications are often inevitable. Methods: The method is presented for n=5 cochleae which were segmented using a custom software for increased accuracy. The linear basilar membrane cross sections are expanded to areas while the scalae contours are reconstructed by a predefined number of arc segments. Prior to model generation, geometrical errors are evaluated locally for each cross section as well as globally for the resulting models and their basal turn profiles. The final combination of all reconditioned features to a 3D volume is performed in Autodesk Inventor using the loft feature. Results: Due to the volume generation based on cubic splines, low errors could be achieved even for low numbers of arc segments and provided cross sections, both of which correspond to a strong degree of model simplification. Model generation could be performed in a time efficient manner. Conclusion: The proposed simplification method was proven to be well suited for the helical cochlea geometry. The generated output data can be imported into commercial software tools for various analyses representing a time efficient way to create cochlea models optimally suited for the desired task.