NeuroPrint - hybrid printing technology for personalized soft neuromuscular interfaces

We utilized the capacity of a hybrid printing platform for integration of soft materials and composites into bioelectronic devices well-adapted to various anatomical structures and experimental models, in order to investigate, enable and recover functions of the neuromuscular system. 

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Neural interfaces establish communication between biological systems and electronic devices. This technology can enable clinical applications for restoring physiological functions lost in injury or disease (1). A key aspect of biointegration of neural implants is their mechanical and anatomical adaptation to the neuronal environment. Recently, matching the elasticity of the implant to surrounding tissues of the nervous system has been recognized as crucial for long-term stability and biointegration (2, 3). This can be facilitated by the incorporation of elastic materials, mechanically adaptive thin films, foils and fibers into the implant, to allow close communication with the target tissues (4, 5).

Despite improvements in materials, current technologies do not support rapid customization of implants. This makes adapting implants (to the varied anatomy of neural niches and the anthropometry of patients with different age, size, and specific therapeutic targets) impractical, costly and slow. Personalized medicine requires fast (on-demand) production of well-adjusted devices that enable physicians to design the optimal treatment strategy. Printing of medical devices has already been explored for various clinical applications, such as patient-specific artificial limb sockets, bone regeneration scaffolds and models for surgical planning (6,7)

Although additive manufacturing has been applied for development of flexible and elastic bioelectronic devices for in vitro applications and external skins, rapid prototyping technologies for neural implants have not been applied (8). Here, we utilize the capacity of a hybrid printing platform for integration of soft materials and composites into bioelectronic devices well-adapted to various anatomical structures and experimental models, in order to investigate, enable and recover functions of the neuromuscular system.

Hybrid printing platform

We present a hybrid printing technology to produce interfaces for monitoring and enabling functional states of the nervous system. Due to adapted geometry and unique mechanical properties, the NeuroPrint interfaces can be applied to various neural structures, model species and tasks. Using arrays of platinum-silicone composite electrodes, we stimulated and recorded biopotentials from the brain, spinal cord, peripheral nerve, as well as striated and smooth muscles.  The monolithic infrastructure of the implant ensured resilience to mechanical deformation and efficient charge exchange with neural structures under chronic implantation.

Electromechanical properties of the implants enabled their high biointegration in long-term in vivo experiments, suggesting their potential applications in different fields of translational and clinical neuroscience, including neuroprosthetics and electroceuticals. As a meso-scale fabrication technology, NeuroPrint is well suited to the circuits-level interfacing that is desired for neuroelectronic medicine.  Personalized treatment requires on-demand and flexible fabrication technologies that may be utilized in clinical practice, empowered by the development of control electronics and power supply for complete implantable systems. By establishing highly functional and durable interfacing with sensitive neural tissue, NeuroPrint electrodes emerge as a crucial component of such systems.

NeuroPrint electrodes applications

References:

  1. F. B. Wagner et al., Targeted neurotechnology restores walking in humans with spinal cord injury. Nature 563, 65-71 (2018).
  2. Y. Liu et al., Soft and elastic hydrogel-based microelectronics for localized low-voltage neuromodulation. Nature Biomedical Engineering 3, 58-68 (2019).
  3. I. R. Minev et al., Electronic dura mater for long-term multimodal neural interfaces. Science 347, 159-163 (2015).
  4. T.-M. Fu, G. Hong, R. D. Viveros, T. Zhou, C. M. Lieber, Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology. Proceedings of the National Academy of Sciences 114, E10046-E10055 (2017).
  5. C. M. Boutry et al., A stretchable and biodegradable strain and pressure sensor for orthopaedic application. Nature Electronics 1, 314-321 (2018).
  6. D. M. Sengeh, H. Herr, A variable-impedance prosthetic socket for a transtibial amputee designed from magnetic resonance imaging data. JPO: Journal of Prosthetics and Orthotics 25, 129-137 (2013).
  7. C. C. Ploch, C. S. Mansi, J. Jayamohan, E. Kuhl, Using 3D printing to create personalized brain models for neurosurgical training and preoperative planning. World neurosurgery 90, 668-674 (2016).
  8. A. D. Valentine et al., Hybrid 3D Printing of Soft Electronics. Advanced Materials 29, 1703817-n/a (2017).

 

 

Pavel Musienko

Professor, Institute of translational biomedicine, St Petersburg State University

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