3D Printed Anatomical Nerve Regeneration Pathways

Abstract

An imaging-coupled 3D printing methodology for the design, optimization, and fabrication of a customized nerve repair technology for complex injuries is presented. The custom scaffolds are deterministically fabricated via a microextrusion printing principle which enables the simultaneous incorporation of anatomical geometries, biomimetic physical cues, and spatially controlled biochemical gradients in a one-pot 3D manufacturing approach.

Keywords: 3D printing; 3D scanning; nerve regeneration; neural engineering; tissue engineering.

Figure 1

Personalized nerve regeneration pathways enabled by 3D scanning and printing. a) A tissue model of the nerve pathway to be constructed is prepared for subsequent imaging by either incision (in situ approach) or transection (ex situ approach). b) The intact or transected tissue is imaged using structured light scanning (SLS), which results in a high precision 3D model of the nerve pathway. c) The reverse engineered nerve pathway is 3D printed, to realize a device which mimics the original nerve in terms of geometry, physical cues, and path-specific biochemical cues in the form of gradient distributions.

Figure 2

3D printed complex nerve pathways from 3D scanned bifurcating nerves. a) The sciatic nerve provides a bifurcating mixed nerve model which contains branching sensory (derived from the sural nerve; top) and motor nerves (derived from the peroneal and tibial nerves; bottom). b) The complex nerve pathway is transected, providing a tissue template for ex situ scanning measurements. c) Scans are conducted from various perspectives to assemble a 3D model which describes the geometry of the nerve pathway (sural and tibial nerve motor branches). d) The individual scans are aligned to replicate the 3D geometry of the nerve tissue. e) The aligned scans are assembled into a water-tight 3D model, leading to a full reconstruction of the nerve pathway geometry, which provides a template for 3D printing. f) The 3D model is printed into a hollow silicone pathway which is customized to fit the exact geometry of the original tissue.

Figure 3

Mechanical characterization and computational analysis of the pathways. a) Tensile strength measurements on 3D printed materials reveal the influence of the printing orientation (physical cue direction) on the ultimate tensile strength. b) Von Mises stress (σ) distribution in the nerve pathway under a tensile load applied to the distal ends of the nerve (σ_max = 0.41 MPa). c) Von Mises stress (σ) distribution in the nerve pathway under a torsional load applied to the distal ends of the nerve (σ_max = 0.61 MPa).

Figure 4

Characterization and influence of the 3D printed physical cue. a) Scanning electron micrograph of a 3D printed hollow nerve pathway displaying an axially-oriented physical cue on the luminal surface. b) Profilometry measurement performed on the luminal surface of the 3D printed nerve pathway shows a distinct microgroove structure. c) Cultured primary embryonic neurons on the 3D printed horizontally-oriented physical cue (90° reference angle) stained for tau (green). d) Corresponding orientation analysis showing a coincidence of the neurite network alignment with the physical cue. e) Cultured Schwann cells on the horizontally-oriented physical cue (90° reference angle) stained for GFAP (green) and laminin (red). f) Corresponding orientation analysis showing a coincidence of the cytoskeleton and extracellular matrix alignment with the physical cue.

Figure 5

Functionalization of nerve pathways with path-specific biochemical gradients. a) Schematic of the path-specific incorporation of gradient distributions of supporting biochemical cues – nerve growth factor, NGF, and glial cell line-derived neurotrophic factor, GDNF – in the sensory and motor paths, respectively. b) Representative photograph of the 3D printed gradient pattern achieved using a protein-loaded hydrogel. Green and red dyes were added to the hydrogel to enhance the image contrast. c) Results from finite element analysis (FEA) of transient drug release showing the establishment of an axially-oriented concentration gradient which results from the 3D printed luminal hydrogel pattern over time. d) Experimental drug release studies showing the protein release kinetics from the gelatin methacrylate hydrogel system.

Figure 6

In vitro and in vivo characterization of regeneration with 3D printed nerve pathways. a) Effect of the diffusive NGF gradient on the guidance of the sensory neurite network growth (inset scale bar = 1,000 μm; a full size image is provided in Supporting Figure S7). b) Effect of the diffusive GDNF gradient on the migration velocity of Schwann cells (inset scale bar = 100 μm; arrow indicates direction of source and migration direction). c) Schematic of implanted nerve guide showing bifurcation into sensory and motor nerve paths. d) Photograph of an implanted 3D printed nerve guide prior to suturing. e) Histology of regenerated nerve showing cross-sections of regenerated nerves stained for tubulin (green) (scale bar = 50 μm). f) Comparison of the functional return in regenerated rat hind limbs (* indicates p-value < 0.05, ** indicates p-value < 0.01).