A lung biopsy path planning algorithm based on the double spherical constraint Pareto and indicators'
Hui Yang1, Yu Zhang1, Yuhang Gong1
1College of Biomedical Engineering, Sichuan University, Chengdu 610065, China.
Summary
This study introduces an automated path planning method to assist doctors in CT-guided percutaneous transthoracic lung biopsy (CT-PTLB). The system offers feasible puncture paths, enhancing diagnostic procedures for lung cancer.
Area of Science:
- Medical Imaging and Intervention
- Computational Pathology
- Surgical Robotics
Background:
- Lung cancer exhibits the highest mortality rate globally.
- CT-guided percutaneous transthoracic lung biopsy (CT-PTLB) is a standard diagnostic tool but demands significant physician expertise.
- The complexity of CT-PTLB necessitates advanced decision support systems.
Purpose of the Study:
- To develop an automated path planning method for CT-PTLB.
- To provide auxiliary guidance for puncture path selection to clinicians.
- To enhance the safety and efficiency of lung biopsy procedures.
Main Methods:
- A three-step approach: preprocessing (organ segmentation), initial path selection (target point selection with down-sampling, entry point selection), and path evaluation (quantified risk/execution indicators, double spherical constraint Pareto scoring).
- Utilized a novel path scoring system incorporating indicator importance and correlation.
- Tested retrospectively on 6 CT images and prospectively on 25 CT images.
Main Results:
- The automated method successfully planned feasible puncture paths for diverse clinical scenarios.
- The proposed path evaluation system effectively assessed comprehensive path performance.
- Experimental validation demonstrated the system's utility as an auxiliary tool.
Conclusions:
- The developed automatic path planning method is effective for CT-PTLB.
- This system can serve as a valuable auxiliary tool for lung biopsy surgeries.
- The approach has the potential to improve clinical decision-making in lung cancer diagnosis.
