Reducing MRI susceptibility artefacts in implants using additively manufactured porous Ti-6Al-4V structures

Magnetic Resonance Imaging (MRI) is critical in diagnosing post-operative complications following implant surgery and imaging anatomy adjacent to implants. Increasing field strengths and use of gradient-echo sequences have highlighted difficulties from susceptibility artefacts in scan data. Artefacts manifest around metal implants, including those made from titanium alloys, making detection of complications (e.g. bleeding, infection) difficult and hindering imaging of surrounding structures such as the brain or inner ear.Existing research focusses on post-processing and unorthodox scan sequences to better capture data around these devices. This study proposes a complementary up-stream design approach using lightweight structures produced via additive manufacturing (AM). Strategic implant mass reduction presents a potential tool in managing artefacts.Uniform specimens of Ti-6Al-4V structures, including lattices, were produced using the AM process, selective laser melting, with various unit cell designs and relative densities (3.1%–96.7%). Samples, submerged in water, were imaged in a 3T MRI system using clinically relevant sequences. Artefacts were quantified by image analysis revealing a strong linear relationship (RR2 = 0.99) between severity and relative sample density. Likewise, distortion due to slice selection errors showed a squared relationship (RR2 = 0.92) with sample density. Unique artefact features were identified surrounding honeycomb samples suggesting a complex relationship exists for larger unit cells.To demonstrate clinical utility, a honeycomb design was applied to a representative cranioplasty. Analysis revealed 10% artefact reduction compared to traditional solid material illustrating the feasibility of this approach.This study provides a basis to strategically design implants to reduce MRI artefacts and improve post-operative diagnosis capability.Statement of SignificanceMRI susceptibility artefacts surrounding metal implants present a clinical challenge for the diagnosis of post-operative complications relating to the implant itself or underlying anatomy. In this study for the first time we demonstrate that additive manufacturing may be exploited to create lattice structures that predictably reduce MRI image artefact severity surrounding titanium alloy implants. Specifically, a direct correlation of artefact severity, both total signal loss and distortion, with the relative material density of these functionalised materials has been demonstrated within clinically relevant MRI sequences. This approach opens the door for strategic implant design, utilising this structurally functionalised material, that may improve post-operative patient outcomes and compliments existing efforts in this area which focus on data acquisition and post-processing methods