Computational Evaluation of Cochlear Implant Surgery Outcomes Accounting for Uncertainty and Parameter Variability Article Swipe
Nerea Mangado
,
Jordi Pons‐Prats
,
Martí Coma
,
Pavel Mistrík
,
Gemma Piella
,
Mario Ceresa
,
Miguel Á. González Ballester
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.3389/fphys.2018.00498
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.3389/fphys.2018.00498
Cochlear implantation (CI) is a complex surgical procedure that restores hearing in patients with severe deafness. The successful outcome of the implanted device relies on a group of factors, some of them unpredictable or difficult to control. Uncertainties on the electrode array position and the electrical properties of the bone make it difficult to accurately compute the current propagation delivered by the implant and the resulting neural activation. In this context, we use uncertainty quantification methods to explore how these uncertainties propagate through all the stages of CI computational simulations. To this end, we employ an automatic framework, encompassing from the finite element generation of CI models to the assessment of the neural response induced by the implant stimulation. To estimate the confidence intervals of the simulated neural response, we propose two approaches. First, we encode the variability of the cochlear morphology among the population through a statistical shape model. This allows us to generate a population of virtual patients using Monte Carlo sampling and to assign to each of them a set of parameter values according to a statistical distribution. The framework is implemented and parallelized in a High Throughput Computing environment that enables to maximize the available computing resources. Secondly, we perform a patient-specific study to evaluate the computed neural response to seek the optimal post-implantation stimulus levels. Considering a single cochlear morphology, the uncertainty in tissue electrical resistivity and surgical insertion parameters is propagated using the Probabilistic Collocation method, which reduces the number of samples to evaluate. Results show that bone resistivity has the highest influence on CI outcomes. In conjunction with the variability of the cochlear length, worst outcomes are obtained for small cochleae with high resistivity values. However, the effect of the surgical insertion length on the CI outcomes could not be clearly observed, since its impact may be concealed by the other considered parameters. Whereas the Monte Carlo approach implies a high computational cost, Probabilistic Collocation presents a suitable trade-off between precision and computational time. Results suggest that the proposed framework has a great potential to help in both surgical planning decisions and in the audiological setting process.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fphys.2018.00498
- https://www.frontiersin.org/articles/10.3389/fphys.2018.00498/pdf
- OA Status
- gold
- Cited By
- 13
- References
- 54
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2800004337
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2800004337Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/fphys.2018.00498Digital Object Identifier
- Title
-
Computational Evaluation of Cochlear Implant Surgery Outcomes Accounting for Uncertainty and Parameter VariabilityWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-05-23Full publication date if available
- Authors
-
Nerea Mangado, Jordi Pons‐Prats, Martí Coma, Pavel Mistrík, Gemma Piella, Mario Ceresa, Miguel Á. González BallesterList of authors in order
- Landing page
-
https://doi.org/10.3389/fphys.2018.00498Publisher landing page
- PDF URL
-
https://www.frontiersin.org/articles/10.3389/fphys.2018.00498/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.frontiersin.org/articles/10.3389/fphys.2018.00498/pdfDirect OA link when available
- Concepts
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Computer science, Probabilistic logic, Cochlear implant, Population, Monte Carlo method, Context (archaeology), Algorithm, Artificial intelligence, Statistics, Medicine, Mathematics, Audiology, Environmental health, Biology, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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13Total citation count in OpenAlex
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-
2025: 2, 2024: 3, 2022: 4, 2021: 1, 2020: 2Per-year citation counts (last 5 years)
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54Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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