Additive manufacturing (AM, also known as 3D printing) is an advanced manufacturing technique that has enabled progress in the design and fabrication of customised or patient-specific (meta-)biomaterials and biomedical devices (e.g., implants, prosthetics, and orthotics) with complex internal microstructures and tuneable properties. In the past few decades, several design guidelines have been proposed for creating porous lattice structures, particularly for biomedical applications. Meanwhile, the capabilities of AM to fabricate a wide range of biomaterials, including metals and their alloys, polymers, and ceramics, have been exploited, offering unprecedented benefits to medical professionals and patients alike. In this review article, we provide an overview of the design principles that have been developed and used for the AM of biomaterials as well as those dealing with three major categories of biomaterials, i.e., metals (and their alloys), polymers, and ceramics. The design strategies can be categorised as: library-based design, topology optimisation, bio-inspired design, and meta-biomaterials. Recent developments related to the biomedical applications and fabrication methods of AM aimed at enhancing the quality of final 3D-printed biomaterials and improving their physical, mechanical, and biological characteristics are also highlighted. Finally, examples of 3D-printed biomaterials with tuned properties and functionalities are presented.

https://www.mdpi.com/1996-1944/15/15/5457/pdf?version=1660110471

Additive Manufacturing of Biomaterials—Design Principles and Their Implementation

Advanced head and neck cancers involving the mandible often require surgical removal of the diseased parts and replacement with donor bone or prosthesis to recreate the form and function of the premorbid mandible. The degree to which this reconstruction successfully replicates key geometric features of the original bone critically affects the cosmetic and functional outcomes of speaking, chewing, and breathing. With advancements in computational power, biomechanical modeling has emerged as a prevalent tool for predicting the functional outcomes of the masticatory system and evaluating the effectiveness of reconstruction procedures in patients undergoing mandibular reconstruction surgery. These models offer cost-effective and patient-specific treatment tailored to the needs of individuals. To underscore the significance of biomechanical modeling, we conducted a review of 66 studies that utilized computational models in the biomechanical analysis of mandibular reconstruction surgery. The majority of these studies employed finite element method (FEM) in their approach; therefore, a detailed investigation of FEM has also been provided. Additionally, we categorized these studies based on the main components analyzed, including bone flaps, plates/screws, and prostheses, as well as their design and material composition. 

Computational models and their applications in biomechanical analysis of mandibular reconstruction surgery

In recent years, the field of mandibular reconstruction has made great strides in terms of hardware innovations and their clinical applications. There has been considerable interest in using computer-aided design, finite element modelling, and additive manufacturing techniques to build patient-specific surgical implants. Moreover, lattice implants can mimic mandibular bone’s mechanical and structural properties. This article reviews current approaches for mandibular reconstruction, their applications, and their drawbacks. Then, we discuss the potential of mandibular devices with lattice structures, their development and applications, and the challenges for their use in clinical settings.

Titanium Alloy Implants with Lattice Structures for Mandibular Reconstruction

Only a few mandibular bone finite element (FE) models have been validated in literature, making it difficult to assess the credibility of the models. In a comparative study between FE models and biomechanical experiments using a synthetic polyamide 12 (PA12) mandible model, we investigate how material properties and boundary conditions affect the FE model's accuracy using the design of experiments approach. Multiple FE parameters, such as contact definitions and the materials' elastic and plastic deformation characteristics, were systematically analyzed for an intact mandibular model and transferred to the fracture fixation model. In a second step, the contact definitions for the titanium screw and implant (S-I), implant and PA12 mandible (I-M), and interfragmentary (IF) PA12 segments were optimized. Comparing simulated deformations (from 0 to -5 mm) and reaction forces (from 10 to 1'415 N) with experimental results showed a strong sensitivity to FE mechanical properties and contact definitions. The results suggest that using the bonded definition for the screw-implant contact of the fracture plate is ineffective. The contact friction parameter set with the highest agreement was identified: titanium screw and implant μ = 0.2, implant and PA12 mandible μ = 0.2, interfragmentary PA12 mandible μ = 0.1. The simulated reaction force (RMSE = 26.60 N) and surface displacement data (RMSE = 0.19 mm) of the FE analysis showed a strong agreement with the experimental biomechanical data. The results were generated through parameter optimization which means that our findings need to be validated in the event of a new dataset with deviating anatomy. Conclusively, the predictive capability of the FE model can be improved by FE model calibration through experimental testing. Validated preoperative quasi-static FE analysis could allow engineers and surgeons to accurately estimate how the implant's choice and placement suit the patient's biomechanical needs. 

Parameter optimization in a finite element mandibular fracture fixation model using the design of experiments approach.

Abstract Advanced head and neck cancers involving the mandible often require surgical removal of the diseased parts and replacement with donor bone or prosthesis to recreate the form and function of the premorbid mandible. The degree to which this reconstruction successfully replicates key geometric features of the original bone critically affects the cosmetic and functional outcomes of speaking, chewing, and breathing. With advancements in computational power, biomechanical modeling has emerged as a prevalent tool for predicting the functional outcomes of the masticatory system and evaluating the effectiveness of reconstruction procedures in patients undergoing mandibular reconstruction surgery. These models enable surgeons to provide cost-efficient and patient-specific treatment tailored to the needs of individuals. To underscore the significance of biomechanical modeling, we conducted a review of 66 studies that utilized computational models in the biomechanical analysis of mandibular reconstruction surgery. These studies were categorized based on the main components analyzed, including bone flaps, plates/screws, and prostheses, as well as their design and material composition. 

/pdf/computational-models-and-their-applications-in-biomechanical-3cg3tv0r.pdf

Computational Models and Their Applications in Biomechanical Analysis of Mandibular Reconstruction Surgery

Mandibular reconstruction using patient-specific cage implants is a promising alternative to the vascularized free flap reconstruction for nonirradiated patients with adequate soft tissues, or for patients whose clinical condition is not conducive to microsurgical reconstruction. This study aimed to assess the biomechanical performance of 3D printed patient-specific cage implants designed with a semi-automated workflow in a combined cadaveric and retrospective case series study. We designed cage implants for two human cadaveric mandibles using our previously developed design workflow. The biomechanical performance of the implants was assessed with the finite element analysis (FEA) and quasi-static biomechanical testing. Digital image correlation (DIC) was used to measure the full-field strains and validate the FE models by comparing the distribution of maximum principal strains within the bone. The retrospective study of a case series involved three patients, each of whom was treated with a cage implant of similar design. The biomechanical performance of these implants was evaluated using the experimentally validated FEA under the scenarios of both mandibular union and nonunion. No implant or screw failure was observed prior to contralateral bone fracture during the quasi-static testing of both cadaveric mandibles. The FEA and DIC strain contour plots indicated a strong linear correlation (r = 0.92) and a low standard error (SE=29.32με), with computational models yielding higher strain values by a factor of 2.7. The overall stresses acting on the case series’ implants stayed well below the yield strength of additively manufactured (AM) commercially pure titanium, when simulated under highly strenuous chewing conditions. Simulating a full union between the graft and remnant mandible yielded a substantial reduction (72.7±1.5%) in local peak stresses within the implants as compared to a non-bonded graft. This study shows the suitability of the developed semi-automated workflow in designing patient-specific cage implants with satisfactory mechanical functioning under demanding chewing conditions. The proposed workflow can aid clinical engineers in creating reconstruction systems and streamlining pre-surgical planning. Nevertheless, more research is still needed to evaluate the osteogenic potential of bone graft insertions. 

Biomechanical evaluation of additively manufactured patient-specific mandibular cage implants designed with a semi-automated workflow: A cadaveric and retrospective case study.

The reconstruction of large mandibular defects with optimal aesthetic and functional outcomes remains a major challenge for maxillofacial surgeons. The aim of this study was to design patient-specific mandibular reconstruction implants through a semi-automated digital workflow and to assess the effects of topology optimization on the biomechanical performance of the designed implants. By using the proposed workflow, a fully porous implant (LA-implant) and a topology-optimized implant (TO-implant) both made of Ti–6Al–4V ELI were designed and additively manufactured using selective laser melting. The mechanical performance of the implants was predicted by performing finite element analysis (FEA) and was experimentally assessed by conducting quasi-static and cyclic biomechanical tests. Digital image correlation (DIC) was used to validate the FE model by comparing the principal strains predicted by the FEM model with the measured distribution of the same type of strain. The numerical predictions were in good agreement with the DIC measurements and the predicted locations of specimen failure matched the actual ones. No statistically significant differences (p < 0.05) in the mean stiffness, mean ultimate load, or mean ultimate displacement were detected between the LA- and TO-implant groups. No implant failures were observed during quasi-static or cyclic testing under masticatory loads that were substantially higher (>1000 N) than the average maximum biting force of healthy individuals. Given its relatively lower weight (16.5%), higher porosity (17.4%), and much shorter design time (633.3%), the LA-implant is preferred for clinical application. This study clearly demonstrates the capability of the proposed workflow to develop patient-specific implants with high precision and superior mechanical performance, which will greatly facilitate cost- and time-effective pre-surgical planning and is expected to improve the surgical outcome. 

Semi-automated digital workflow to design and evaluate patient-specific mandibular reconstruction implants.

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Biomechanical evaluation of additively manufactured patient-specific mandibular cage implants designed with a semi-automated workflow: A cadaveric and retrospective case study.

Semi-automated digital workflow to design and evaluate patient-specific mandibular reconstruction implants.