Constructing a three‐dimensional electrical model of a living cochlear implant user's cochlea

Malherbe, Tiaan Krynauw; Hanekom, Tania; Hanekom, Johan J.

doi:10.1002/cnm.2751

Cited by 40 publications

(60 citation statements)

References 36 publications

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“…The SD of the 3 dB bandwidth in the voltage distribution at the nerve positions across the 12 PSMs was 3.0 mm. These values are in the range of values reported by Malherbe et al (2015a,b). The SD in 3 dB bandwidth for the NPSM2 model for different values of R (from 9.16 to 71.5) was 8.1 mm, which is much larger than the variability observed across PSMs.…”

Section: Resultssupporting

confidence: 85%

“…For example, the model of Malherbe et al (2015a,b) is constructed using greater detail including the height of the ducts, the width of the bony canal in which the cochlear nerve lies, the inclusion of a head model, and the consideration of the reference electrode. The simpler and less accurate geometry used in this study can be adapted to clinical CT scans using the electrode positions and just six parameters to characterize the cochlea.…”

Section: Discussionmentioning

confidence: 99%

“…Malherbe et al (2015a,b) modeled potential distributions and neural excitation profiles (threshold amplitudes, center frequencies, and bandwidths) for different user-specific cochlear morphologies and electrode placements within the cochlea. In general, they showed that the variability of threshold, characteristic frequency, and bandwidth values observed as a result of morphology are almost as large as variations observed as a result of electrode placement, suggesting that user-specific morphology is an important determinant of CI performance.…”

Section: Discussionmentioning

confidence: 99%

“…Other models (Suesserman and Spelman, 1993; Hanekom, 2001; Briaire, 2008) are very sophisticated trying to model many details of the cochlea; however, their adaptation to each CI user seems to be time consuming. Recently, geometrical models have been developed such that they can be adapted to each CI user (Dang et al, 2015; Malherbe et al, 2015b; Mangado et al, 2016). In Dang et al (2015), a detailed anatomical model of the cochlea was parameterized and used to predict the voltage distribution (using FEM) created by CI electrical stimulation in a temporal bone.…”

Section: Introductionmentioning

confidence: 99%

“…In Dang et al (2015), a detailed anatomical model of the cochlea was parameterized and used to predict the voltage distribution (using FEM) created by CI electrical stimulation in a temporal bone. In Malherbe et al (2015a,b), a method to construct user-specific models of the cochlear of living CI users was presented. In their study, the effect of variations in cochlear morphology and electrode location on modeled potential distributions and neural excitations was analyzed.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Validation of a Cochlear Implant Patient-Specific Model of the Voltage Distribution in a Clinical Setting

Nogueira

Schurzig

Büchner

et al. 2016

Front. Bioeng. Biotechnol.

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Cochlear Implants (CIs) are medical implantable devices that can restore the sense of hearing in people with profound hearing loss. Clinical trials assessing speech intelligibility in CI users have found large intersubject variability. One possibility to explain the variability is the individual differences in the interface created between electrodes of the CI and the auditory nerve. In order to understand the variability, models of the voltage distribution of the electrically stimulated cochlea may be useful. With this purpose in mind, we developed a parametric model that can be adapted to each CI user based on landmarks from individual cone beam computed tomography (CBCT) scans of the cochlea before and after implantation. The conductivity values of each cochlea compartment as well as the weighting factors of different grounding modes have also been parameterized. Simulations were performed modeling the cochlea and electrode positions of 12 CI users. Three models were compared with different levels of detail: a homogeneous model (HM), a non-patient-specific model (NPSM), and a patient-specific model (PSM). The model simulations were compared with voltage distribution measurements obtained from the backward telemetry of the 12 CI users. Results show that the PSM produces the lowest error when predicting individual voltage distributions. Given a patient-specific geometry and electrode positions, we show an example on how to optimize the parameters of the model and how to couple it to an auditory nerve model. The model here presented may help to understand speech performance variability and support the development of new sound coding strategies for CIs.

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Section: Resultssupporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Validation of a Cochlear Implant Patient-Specific Model of the Voltage Distribution in a Clinical Setting

Nogueira

Schurzig

Büchner

et al. 2016

Front. Bioeng. Biotechnol.

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A multiobjective optimization procedure for the electrode design of cochlear implants

Ramos‐de‐Miguel

Escobar

Greiner

et al. 2018

Numer Methods Biomed Eng

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This paper presents a new procedure to design optimal electrodes for cochlear implants. The main objective of this study is to find a set of electrode designs that maximize the focalization and minimize the power consumption simultaneously. To achieve that, a criterion to measure the ability of focalization of an electrode is proposed. It is presented a procedure to determine (1) the electrical potential induced by an electrode by solving the Laplace equation through the finite element method; (2) the response of a neuron to an applied field using NEURON, a compartmentalized cell model; (3) the optimization to find the best electrode designs according to power consumption and focalization by 2 evolutionary multiobjective methods based on the non-dominated sorting genetic algorithm II: a straight multiobjective approach and a seeded multiobjective approach. An electrode design formed by 2 conductive rings with a possible difference of potential between them is proposed. It is analyzed that the response of the neuron is determined by the shape and the difference of the potential between the electrode rings. Our procedure successfully achieves a nondominated set of optimum electrode designs improving a standard electrode in both objectives, as designs with better focalization allow to include extra electrodes in the cochlear implant, and designs with lower power consumption extend the length of the battery.

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Auditory Nerve Fiber Health Estimation Using Patient Specific Cochlear Implant Stimulation Models

Liu

Çakır

Noble

2020

Simulation and Synthesis in Medical Imaging

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Cochlear implants (CIs) restore hearing using an array of electrodes implanted in the cochlea to directly stimulate auditory nerve fibers (ANFs). Hearing outcomes with CIs are dependent on the health of the ANFs. In this research, we developed an approach to estimate the health of ANFs using patient-customized, image-based computational models of CI stimulation. Our stimulation models build on a previous model-based solution to estimate the intra-cochlear electric field (EF) created by the CI. Herein, we propose to use the estimated EF to drive ANF models representing 75 nerve bundles along the length of the cochlea. We propose a method to detect the neural health of the ANF models by optimizing neural health parameters to minimize the sum of squared differences between simulated and the physiological measurements available via patients' CIs. The resulting health parameters provide an estimate of the health of ANF bundles. Experiments with 8 subjects show promising model prediction accuracy, with excellent agreement between neural stimulation responses that are clinically measured and those that are predicted by our parameter optimized models. These results suggest our modeling approach may provide an accurate estimation of ANF health for CI users.

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Constructing a three‐dimensional electrical model of a living cochlear implant user's cochlea

Abstract: This work suggests that the use of user-specific models is indicated when more detailed analysis is required than what is available from generic models. Copyright © 2015 John Wiley & Sons, Ltd.

Cited by 40 publications

References 36 publications

Validation of a Cochlear Implant Patient-Specific Model of the Voltage Distribution in a Clinical Setting

Validation of a Cochlear Implant Patient-Specific Model of the Voltage Distribution in a Clinical Setting

A multiobjective optimization procedure for the electrode design of cochlear implants

Auditory Nerve Fiber Health Estimation Using Patient Specific Cochlear Implant Stimulation Models

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