Multi-objective constraints for path planning in screw fixation of scaphoid fractures

Scaphoid fractures, a common type of clinical fracture, often require screw placement surgery to achieve optimal therapeutic outcomes. Path planning algorithms can avoid more risks and have vital potential for developing precise and automatic surgeries. Despite the success of surgical path planning algorithms, automatic path planning for scaphoid fractures remains challenging owing to the complex bone structure and individual variations.

Thus, we propose a Multi-objective constrained Path planning Algorithm (MPA) for fracture screw placement, which includes the identification of the center of the fracture surface. Further, three constraint conditions were introduced to eliminate infeasible paths, followed by adding three objectives to the remaining paths for more accurate planning. Finally, the Nondominated Sorting Genetic Algorithms (NSGA)-II algorithm was used to optimize the surgical paths.

We defined the vertical compression distance (VCD), a common observation index in clinics. The experiments show that the average VCD of the MPA paths is measured at 23.88 mm, outperforming the clinical planning paths by 21.71 mm. Ablation experiments demonstrated that all three objectives (distance, length, and angle) effectively optimized the path planning. Additionally, we also used finite element analysis to compare and analyze the MPA path and clinical path. The experimental results showed that the MPA path always outperformed the clinical path in terms of scaphoid strain and screw stress.

This study presents a solution for the path planning of scaphoid fractures. Our future research will attempt to enhance the model's performance and extend its application to a broader range of fracture types.