A rapid path planning approach for liver tumor ablation with comprehensive constraints.

Localized thermal ablation is widely recognized as an effective treatment for liver tumors, offering a minimally invasive alternative to surgical resection. However, the accuracy and safety of the procedure heavily depend on preoperative puncture path planning, which must account for anatomical constraints and potential thermal injury to surrounding tissues. This study proposes an improved multi-objective whale optimization algorithm for preoperative planning of liver tumor ablation. The algorithm simultaneously optimizes the needle trajectory while considering multiple clinical constraints, such as avoiding vital structures and minimizing path length and risk zones. The method was evaluated using real clinical data from seven patients. Experimental results show that the proposed approach achieves an average planning time of 22 s per case, significantly enhancing computational efficiency. Furthermore, it generates two optimized paths for each patient with varying thermal damage zones, both of which outperform existing mainstream optimization algorithms in terms of clinical feasibility and safety. Compared to traditional methods, the proposed algorithm provides faster computation and more reliable path options, better supporting clinical decision-making in liver tumor treatment. These results suggest that the method has strong potential for real-world application in improving the precision and efficiency of thermal ablation procedures.