Author(s)

Nan Bao Jingyi Jia, Yueyao Chen,Zhizhou Li, Chongchong Song, Ruotong Zhao

Corresponding Author

Nan Ba

Abstract

CT image-guided lung biopsy surgery is the gold standard for lung tumor diagnosis. The preoperative path planning of the surgery is necessary, which aims to find some optimal needle insertion points on the patient’s skin. The traditional path planning method is that the surgeons estimate the puncture paths by observing the patient’s CT images, which is highly dependent on the experience of surgeons and affects the success rate of the surgery due to improper path selection. In this work, we proposed an intelligent lung biopsy surgery path planning method, which solved a multi-objective optimization problem. We segmented some chest important organs based on CT images, and quantitatively analyzed multiple clinical criteria. The concept of Pareto optimization was introduced to solve the multi-objective optimization problem in the method. Finally, some optimal surgery paths were provided for the surgeons. The retrospective evaluation of clinical data was performed, which was proved that the proposed method could be accepted in lung biopsy surgery.

Keywords

Surgery path planning, Lung biopsy, CT image-guided surgery, Pareto optimization