ArticleJournal of materials science. Materials in medicine2020
A data-driven polynomial approach to reproduce the scar tissue outgrowth around neural implants.
Article in Journal of materials science. Materials in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Biomimicry ofBiomimetics (Basel, Switzerland) · 2025Article
- Some Mechanical Constraints to the Biomimicry with Peripheral Nerves.Biomimetics (Basel, Switzerland) · 2023Article
- Translational bioengineering strategies for peripheral nerve regeneration: opportunities, challenges, and novel concepts.Neural regeneration research · 2023Review
- Biomedical and Tissue Engineering Strategies to Control Foreign Body Reaction to Invasive Neural Electrodes.Frontiers in bioengineering and biotechnology · 2021Review
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Authors and funding
5 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the huge complexity of the foreign body reaction, a quantitative assessment over time of the scar tissue thickness around implanted materials is needed to figure out the evolution of neural implants for long times. A data-driven approach, based on phenomenological polynomial functions, is able to reproduce experimental data. Nevertheless, a misuse of this strategy may lead to unsatisfactory results, even if standard indexes are optimized. In this work, an effective in silico procedure was presented to reproduce the scar tissue dynamics around implanted synthetic devices and to predict the capsule thickness for times before and after experimental detections.
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Registered trials
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