Planning Nonlinear Access Paths for Temporal Bone Surgery
This work addresses the challenge of minimally-invasive surgeries at the otobasis, offering a domain-specific solution that is incremental in improving path planning methods.
The paper tackled the problem of planning nonlinear access paths for temporal bone surgery to improve clinical outcomes by increasing distances to risk structures and optimizing instrument orientations, demonstrating that their new algorithms outperform state-of-the-art methods based on circular arcs or Bezier-Splines on real CT data and synthetic anatomies.
Purpose: Interventions at the otobasis operate in the narrow region of the temporal bone where several highly sensitive organs define obstacles with minimal clearance for surgical instruments. Nonlinear trajectories for potential minimally-invasive interventions can provide larger distances to risk structures and optimized orientations of surgical instruments, thus improving clinical outcomes when compared to existing linear approaches. In this paper, we present fast and accurate planning methods for such nonlinear access paths. Methods: We define a specific motion planning problem in SE(3) = R3 x SO(3) with notable constraints in computation time and goal pose that reflect the requirements of temporal bone surgery.We then present k-RRT-Connect: two suitable motion planners based on bidirectional Rapidly-exploring Random Trees (RRT) to solve this problem efficiently. Results: The benefits of k-RRT-Connect are demonstrated on real CT data of patients. Their general performance is shown on a large set of realistic synthetic anatomies. We also show that these new algorithms outperform state of the art methods based on circular arcs or Bezier-Splines when applied to this specific problem. Conclusion: With this work we demonstrate that pre- and intra-operative planning of nonlinear access paths is possible for minimally-invasive surgeries at the otobasis.