CC BY-NC-ND 4.0 · Laryngorhinootologie 2018; 97(S 02): S36
DOI: 10.1055/s-0038-1639840
Abstracts
Bildgebende Verfahren/Ultraschall: Imaging/Sonography

Distance A-measurement is a reliable predictor of cochlea length: correlation with 3D-reconstruction

T Sengebusch
1   HNO-Universitätsklinik Evangelisches Krankenhaus Oldenburg, Oldenburg
,
L Geven
1   HNO-Universitätsklinik Evangelisches Krankenhaus Oldenburg, Oldenburg
,
A Radeloff
1   HNO-Universitätsklinik Evangelisches Krankenhaus Oldenburg, Oldenburg
,
M Müller
2   Klinik für Hals-Nasen-Ohren-Heilkunde, Universitätsklinikum Tübingen, Tübingen
,
H Löwenheim
2   Klinik für Hals-Nasen-Ohren-Heilkunde, Universitätsklinikum Tübingen, Tübingen
› Author Affiliations
 

Choosing the optimal electrode array is an important factor for the postoperative hearing rehabilitation after cochlear implantation. Given the large variability of the cochlear length, a precise preoperative assessment is necessary to find the correct electrode array. This can be achieved by different means, e.g. a calculation on the basis of a distance A-measurement according to Escudé et al. (2006) or by multiplanar reconstruction that is time-consuming, but more precise.

Here we retrospectively analyzed CT-scans of 131 patients. The cochlear length was determined by 3D-reconstruction or calculated using the distance A and results were compared.

Distance A averaged 9,09 mm (SD:± 0,39; Range 8,10 – 10,10 mm). According to Escudé et al. the average cochlear length was 37,41 mm (SD:± 1,92; range 31,26 – 42,23 mm). The cochlear length determined by 3D reconstruction was 37,68 mm (SD:± 2,28; range 31,60 – 44,40 mm). The difference between the average of 3D reconstruction and the calculated length according to Escudé was not statistically significant.

In summary, the distance A correlates well with the cochlear length and is suitable for choosing the electrode array before cochlear implantation in the clinical setting, due to its fast and easy determinability.



Publication History

Publication Date:
18 April 2018 (online)

© 2018. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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