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Published on: August 5, 2021
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Semi-automated digital workflow to design and evaluate patient-specific mandibular reconstruction implants
A van Kootwijk1, V Moosabeiki1, M Cruz Saldivar1
1Department of Biomechanical Engineering, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology (TU Delft), Mekelweg 2, 2628 CD, Delft, the Netherlands.
Summary
Patient-specific implants for mandibular reconstruction were designed using a digital workflow. Topology optimization did not significantly alter biomechanical performance, making the lightweight, porous implant preferable for clinical use.
Area of Science:
- Biomaterials Engineering
- Maxillofacial Surgery
- Additive Manufacturing
Background:
- Reconstructing large mandibular defects presents significant aesthetic and functional challenges.
- Patient-specific implants are crucial for optimal outcomes in maxillofacial surgery.
Purpose of the Study:
- To design patient-specific mandibular reconstruction implants using a semi-automated digital workflow.
- To evaluate the impact of topology optimization on implant biomechanical performance.
Main Methods:
- A semi-automated digital workflow was used to design a fully porous implant (LA-implant) and a topology-optimized implant (TO-implant).
- Both implants were additively manufactured from Ti-6Al-4V ELI using selective laser melting.
- Finite element analysis (FEA) and biomechanical testing (quasi-static and cyclic) assessed mechanical performance, with Digital Image Correlation (DIC) for FE model validation.
Main Results:
- FEA predictions closely matched DIC measurements, validating the numerical models.
- No statistically significant differences in stiffness, ultimate load, or displacement were found between LA- and TO-implants.
- Implants withstood loads exceeding average human biting force without failure.
Conclusions:
- The digital workflow enables precise design of patient-specific implants with excellent mechanical properties.
- The lightweight, porous LA-implant, with reduced design time, is preferred for clinical application.
- This approach facilitates cost- and time-effective pre-surgical planning, potentially improving surgical outcomes.
