Back

Evaluation of intracochlear pressure and distribution during fluid application in cochlea models and human petrous bone

Kim, R.; Riemann, C.; Kilgue, A.; Schleyer, S.; Pfeiffer, C. J.; Scholtz, L.-U.; Schuermann, M.; Todt, I.

2024-03-28 biophysics
10.1101/2024.03.25.586533 bioRxiv
Show abstract

IntroductionThe important factor during the application of substances for an inner ear therapy is the atraumatic execution as well as a homogeneous distribution over the cochlea in a reasonable time frame. Since faster delivery can be obtained with higher pressure but, higher pressure will lead to traumatic execution, there are certain constrains for the delivery process. Because of this, an optimized procedure for intracochlear delivery is needed, which enables reduction of intracochlear pressure during perfusion in reasonable time. Hence, the aim of this study was to compare different techniques of substance application and their effects on intracochlear pressure in different models. Material and MethodsIntracochlear pressure was measured by fiberoptic pressure sensors in artificial cochlea models and in a human temporal bone. The pressure sensor was introduced into the inner ear models via an additional channel or the lateral arcade of the temporal bone. In all models the substance was applied by means of an inner ear catheter (MED-EL, Innsbruck, Austria) via the round window with methylene blue with or without second access to the cochlea (helicotrema/oval window). ResultsThe application of substances showed significant differences in intracochlear pressure and substance distribution at the same velocity between the models with and without second access. ConclusionUsing a second-hole technique leads to a faster homogeneous distribution, as well as a lower intracochlear pressure, which can be assumed to be an essential factor for hearing preservation during substance application.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.