A method of lung puncture path planning based on multi-level constraint.
10.7507/1001-5515.202112029
- Author:
Fenghui SUN
1
;
Hongliang PEI
1
;
Yifei YANG
1
;
Qingwen FAN
1
;
Xiao'ou LI
2
Author Information
1. School of Mechanical Engineering, Sichuan University, Chengdu 610065, P. R. China.
2. Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, P. R. China.
- Publication Type:Journal Article
- Keywords:
Fibonacci lattice;
Lung puncture trajectory planning;
Multi-level constraint;
Oriented bounding box tree;
Pareto optimization
- MeSH:
Humans;
Lung/diagnostic imaging*;
Lung Neoplasms/diagnostic imaging*;
Punctures;
Thorax;
Tomography, X-Ray Computed
- From:
Journal of Biomedical Engineering
2022;39(3):462-470
- CountryChina
- Language:Chinese
-
Abstract:
Percutaneous pulmonary puncture guided by computed tomography (CT) is one of the most effective tools for obtaining lung tissue and diagnosing lung cancer. Path planning is an important procedure to avoid puncture complications and reduce patient pain and puncture mortality. In this work, a path planning method for lung puncture is proposed based on multi-level constraints. A digital model of the chest is firstly established using patient's CT image. A Fibonacci lattice sampling is secondly conducted on an ideal sphere centered on the tumor lesion in order to obtain a set of candidate paths. Finally, by considering clinical puncture guidelines, an optimal path can be obtained by a proposed multi-level constraint strategy, which is combined with oriented bounding box tree (OBBTree) algorithm and Pareto optimization algorithm. Results of simulation experiments demonstrated the effectiveness of the proposed method, which has good performance for avoiding physical and physiological barriers. Hence, the method could be used as an aid for physicians to select the puncture path.
