Additive manufacturing (AM) provides the opportunity for complex porous designs, without the costs depending on batch size. Therefore patient-specific implants can be rapidly manufactured. In clinical practice, reconstruction of the mandible is needed in case of bone tumors or trauma. Part of the mandible is removed and the shape of the missing part needs to be estimated, before an implant can be designed. Now-a-days the golden standard for mandible reconstruction is autograft surgery using the iliac or fibula bone. However, this comes with extra donor site surgery and asymmetrical face contours. Mandible movements are needed for mastication and speech and the mandible bone accounts largely for the individual’s face appearance. Hence, good estimation is needed for both function and aesthetics
In this study, a statistical shape model (SSM) of the mandible was generated by segmentation of the mandibles from 35 full body CT-scans. The missing shape of the mandible was estimated using an extruded base, the SSM and mirroring of the intact side. Two finite element models (FEM) were made; one of a healthy mandible and one with a 25% total volume defect with a solid Ti-alloy implant created with the SSM. Two loading conditions were simulated separately; incision clenching (INC) and right molar biting (RMB). Topology optimizations were made with a volume constraint of 0.2 and 0.24 together with an objective function to minimalize the strain energy. To investigate more initial conditions, more topology optimizations were completed. These included one in which the initial implant included pores and two in which extreme mandible cases were used, which were retrieved using the b-values for the first mode of the SSM.
Variations in shape of the mandible were seen in the modes of the SSM. Mode 1 described the variations in shape between the intercondylar angle and distance, mode 2 of the gonial angle and symphysis length, mode 3 described the variations in shape and position of the condyle and mode 4 was associated with the coronoid process. Calculations of the maximum and average distances of the point cloud of the original missing bone part to the estimated shapes illustrated that both mirroring of the healthy side and SSM resulted in the closest estimation. No significance was found between the two methods. Limitations of the mirroring method in relation to the locations of the defects, resulted in the use of SSM for the design of the implant. Topology optimization resulted in optimized implant frames that were located at lateral inferior sides of the implants for both volume constraints and biting tasks. Small differences were seen in the exact location of the crossing of the implant frame. FEM results suggested correct maintenance of stress concentrations and displacements, when compared to the healthy intact mandible. It was suggested that the initial implant shape influences the optimized outcome. Different mandibles resulted in unique optimized implant frames, making the outcome patient specific. The workflow created in this study can be used as a proof of concept for the design and optimization of patient-specific implants for mandible reconstruction, which can easily be manufactured using additive manufacturing processes.