Experimental validation of 3D printed patient-specific implants using digital image correlation and finite element...

Area of Science:

• Biomedical Engineering
• Materials Science
• Computational Mechanics

Background:

• Patient-specific craniofacial implants are revolutionizing reconstructive surgery.
• Topology optimization offers a novel approach to designing implants that restore mid-face form and function.
• Validating implant performance under physiological loads is crucial for clinical success.

Purpose of the Study:

• To validate a topology-optimized, patient-specific craniofacial implant design using mechanical testing.
• To compare finite element model predictions with experimental strain data obtained via Digital Image Correlation (DIC).
• To demonstrate the efficacy of optimized implant shapes in ensuring adequate load transfer during mastication.

Main Methods:

• Creation of patient-specific finite element models from CT scans.
• 3D printing of a complete skull model with embedded, topology-optimized implants.
• Mechanical testing simulating masticatory forces and measuring strain using Digital Image Correlation (DIC).
• Comparison of principal maximum and minimum strains between computational models and experimental data.

Main Results:

• The study successfully validated the finite element models of patient-specific craniofacial implants.
• Digital Image Correlation (DIC) provided comprehensive full-field strain data for comparison.
• The topology-optimized implant designs demonstrated an adequate load-transfer mechanism during simulated mastication.

Conclusions:

• The computational and experimental approach using topology optimization is a viable technique for designing patient-specific craniofacial implants.
• Validated models enhance the reliability of 3D-printed implants for mid-face reconstruction.
• This method ensures restored form and function with effective physiological load management.