Preoperative path planning for percutaneous renal biopsy using the hybrid sampling rapidly-exploring random tree (HS-RRT*) method.

BACKGROUND AND

OBJECTIVE

Percutaneous renal biopsy is an essential diagnostic procedure for renal diseases. However, puncture trajectory planning still relies heavily on the operator's experience, and standardized quantitative planning methods remain lacking. To improve procedural safety, reproducibility, and standardization, this study proposes a hybrid sampling-based RRT* algorithm (HS-RRT*) based on reverse path planning for efficient and safe trajectory planning in different renal puncture regions.

METHODS

An ex vivo renal puncture phantom was developed using three-dimensional (3D) printing, and the puncture environment was reconstructed from 3D medical images. Building upon the conventional reverse RRT algorithm, HS-RRT* incorporates a sampling-channel strategy, a sampling-angle evaluation mechanism, multi-path selection, and Bézier curve-based trajectory smoothing. The proposed method was systematically compared with representative path-planning algorithms under identical spatial configurations.

RESULTS

Experimental results demonstrate that HS-RRT* outperforms the compared algorithms in terms of path length, search efficiency, and trajectory smoothness. The generated puncture trajectories satisfy clinical safety requirements while effectively reducing the randomness associated with single-path planning. Moreover, the optimized trajectories exhibit improved smoothness, with the maximum bending angle maintained below 4°

CONCLUSIONS

HS-RRT* provides a precise, efficient, and standardized solution for preoperative trajectory planning in percutaneous renal biopsy. By integrating reverse path planning, hybrid sampling, and trajectory optimization, the proposed framework provides a reliable technical basis for intelligent puncture navigation and standardized clinical procedures.