3D printing and modelling of customized implants and surgical guides for non-human primates

Xing Chen, Jessy K Possel, Catherine Wacongne, Anne F van Ham, P Christiaan Klink, Pieter R Roelfsema

Research output: Contribution to journal/periodicalArticleScientificpeer-review

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Abstract

BACKGROUND: Primate neurobiologists use chronically implanted devices such as pedestals for head stabilization and chambers to gain access to the brain and study its activity. Such implants are skull-mounted, and made from a hard, durable material, such as titanium.

NEW METHOD: Here, we present a low-cost method of creating customized 3D-printed cranial implants that are tailored to the anatomy of individual animals. We performed pre-surgical computed tomography (CT) and magnetic resonance (MR) scans to generate three-dimensional (3D) models of the skull and brain. We then used 3D modelling software to design implantable head posts, chambers, and a pedestal anchorage base, as well as craniotomy guides to aid us during surgery. Prototypes were made from plastic or resin, while implants were 3D-printed in titanium. The implants underwent post-processing and received a coating of osteocompatible material to promote bone integration.

RESULTS: Their tailored fit greatly facilitated surgical implantation, and eliminated the gap between the implant and the bone. To date, our implants remain robust and well-integrated with the skull.

COMPARISON WITH EXISTING METHOD(S): Commercial-off-the-shelf solutions typically come with a uniform, flat base, preventing them from sitting flush against the curved surface of the skull. This leaves gaps for fluid and tissue ingress, increasing the risk of microbial infection and tissue inflammation, as well as implant loss.

CONCLUSIONS: The use of 3D printing technology enabled us to quickly and affordably create unique, complex designs, avoiding the constraints levied by traditional production methods, thereby boosting experimental success and improving the wellbeing of the animals.

Original languageEnglish
Pages (from-to)38-55
Number of pages18
JournalJournal of Neuroscience Methods
Volume286
DOIs
Publication statusPublished - 2017

Keywords

  • Journal Article

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