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3D printed biomimetic cochleae and machine learning co-modelling provides clinical informatics for cochlear implant patients

Author

Listed:
  • Iek Man Lei

    (University of Cambridge
    University of Cambridge)

  • Chen Jiang

    (University of Cambridge
    University of Cambridge
    Tsinghua University)

  • Chon Lok Lei

    (University of Macau
    University of Oxford)

  • Simone Rosalie de Rijk

    (University of Cambridge)

  • Yu Chuen Tam

    (Addenbrookes Hospital)

  • Chloe Swords

    (Development and Neurosciences)

  • Michael P. F. Sutcliffe

    (University of Cambridge)

  • George G. Malliaras

    (University of Cambridge)

  • Manohar Bance

    (University of Cambridge)

  • Yan Yan Shery Huang

    (University of Cambridge
    University of Cambridge)

Abstract

Cochlear implants restore hearing in patients with severe to profound deafness by delivering electrical stimuli inside the cochlea. Understanding stimulus current spread, and how it correlates to patient-dependent factors, is hampered by the poor accessibility of the inner ear and by the lack of clinically-relevant in vitro, in vivo or in silico models. Here, we present 3D printing-neural network co-modelling for interpreting electric field imaging profiles of cochlear implant patients. With tuneable electro-anatomy, the 3D printed cochleae can replicate clinical scenarios of electric field imaging profiles at the off-stimuli positions. The co-modelling framework demonstrated autonomous and robust predictions of patient profiles or cochlear geometry, unfolded the electro-anatomical factors causing current spread, assisted on-demand printing for implant testing, and inferred patients’ in vivo cochlear tissue resistivity (estimated mean = 6.6 kΩcm). We anticipate our framework will facilitate physical modelling and digital twin innovations for neuromodulation implants.

Suggested Citation

  • Iek Man Lei & Chen Jiang & Chon Lok Lei & Simone Rosalie de Rijk & Yu Chuen Tam & Chloe Swords & Michael P. F. Sutcliffe & George G. Malliaras & Manohar Bance & Yan Yan Shery Huang, 2021. "3D printed biomimetic cochleae and machine learning co-modelling provides clinical informatics for cochlear implant patients," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26491-6
    DOI: 10.1038/s41467-021-26491-6
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    References listed on IDEAS

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    1. Kristoffer Famm & Brian Litt & Kevin J. Tracey & Edward S. Boyden & Moncef Slaoui, 2013. "A jump-start for electroceuticals," Nature, Nature, vol. 496(7444), pages 159-161, April.
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