Anatomical Image-Based 3D Modeling of Human Tibia and Its Biomechanical Analysis

Over the years, biomechanics has created strategies for injury prevention and treatment. The tibia is one of the many bones that make up the human body and is a key load-bearing structure. Regular activities including walking, running, and kneeling exert a lot of stress on it. It is especially prone to injuries involving fractures, which are caused due to accidents or abnormal mechanical stress. The intricate geometry of human bones, notably the tibia, makes its modeling extremely challenging. Such intricate designs are often challenging for conventional CAD tools to create accurately. This research aims to investigate the structural integrity of a human tibia under usual physiological loading conditions by modeling it using a polygonal modeling approach based on anatomical MRI and CT scans images. The open-source digital graphics software Blender, which is good for creating complex biological structures, was utilized in the modeling process. At least two tibia anatomical images were required to develop an accurate polygonal model. The study used the open-source meshing software Gmsh to preprocess the model and create a high-quality finite element mesh as polygonal models cannot be used directly for finite element analysis (FEA). Following that, ANSYS Workbench was employed to import the meshed tibia model and carry out a thorough finite element analysis under static compressive and bending loads. Significant details about the tibia’s mechanical behavior were found by the bending investigation. It was found that lateral bending produced more stress and deformation than frontal bending, indicating that lateral loading increases the possibility of structural damage. The findings emphasize the importance of considering loading direction when assessing the tibia’s biomechanics. These results contribute to the design of improved fracture plates and tibial implants, offering feasible methods to reduce the risk of injuries and speed up patient recovery.