CuraBone main results are presented according to the application field and the technologies used. Hence, one of the main orthopaedic applications are joints. Human joints carry a lot of loads and help to buffer many daily impacts during our lifetime. Therefore, they normally suffer damage and degeneration. Elderly patients often experience problems with degenerations of the cartilage, ligaments, meniscus or even the bones. If all these factors occur in the same patient, a total joint arthroplasty might be necessary. A methodology has been created in order to develop personalized musculoskeletal models of the joints: Maria Paz Quilez and David Leandro Dejtiar for the knee (Fig.1); Maria Hilvert and Antoine Vautrin for the mandible and Jonathan Pitocchi for the shoulder. This process has allowed an assessment of the functional outcome after implantation according to patient satisfaction.
To achieve a successful total joint arthroplasty, implants have to be mechanically fixated to the bone, its stability is highly dependent on the interaction between the implant and bone tissue. The long-term fixation of a porous implant is mainly regulated by the relative micro-motion between prosthesis and host bone. Therefore, Jonathan Pitocchi developed a method for automatically generating a finite element model (FEM) of a shoulder implant, which predicts the micro-motion for a custom reverse shoulder implant (Fig.2) [1]. The methodology also incorporates a novel tool that combines scapular bone shape and cortical morphology in a statistical shape model [2]. In addition, a musculoskeletal model was created by means of an automated method for accurately measuring muscle elongations during the preoperative planning of shoulder arthroplasty [3]. This numerical platform can be easily adapted to analyze different bones and prostheses in the future. It may have important applications in the design and planning of custom implants, calculating the results and guaranteeing low computational costs.
Reverse shoulder implants have a 3D-printed customized glenoid component where bone ingrowth is fundamental for the long-term success of the fixation. Gabriele Nasello developed a mechano-driven algorithm implemented in a FEM based approach which was validated using goat in-vivo experiments [4]. This predictive tool will guide future bone regeneration after surgical interventions [5]. Validation of bone regeneration algorithms was achieved through the creation of novel microfluidic-based in-vitro cell cultures where Gabriele Nasello recreated bone formation under controlled conditions [6,7] (Fig.3).
In addition, Antoine Vautrin and Maria Hilvert developed a computer-based methodology for the personalized design of bioresorbable implants for cranio-maxillofacial applications (Fig.4) [8]. Currently, preoperative planning is already used to supply the surgeon with patient-specific plates (non-resorbable). To develop bioresorbable solutions for this application, different materials have been evaluated for the different applications. CMF plates have been computationally evaluated, considering plate degradation and bone healing process.
Finally, one of the main challenges of these bioreasorbable plates was to characterize the dynamics of material degradation under different conditions. Therefore, Simone Russo has designed and fabricated a new bioreactor that provides the possibility to apply different fluid flow conditions and that has been conceived to evaluate material degradation over time (Fig.5).
