Path planning for percutaneous lung biopsy based on the loose-Pareto and adaptive heptagonal optimization method

Liu, Qi; Zhou, Geyi; Zhong, Jianquan; TANG, Ling; Lu, Yao; Qin, Jing; He, Ling; Zhang, Jing

doi:10.1007/s11517-022-02754-2

Cited by 2 publications

(6 citation statements)

References 27 publications

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“…Among them, the three constraints proposed by Bao et al had a mean constraint strength of 92.97% for the initial puncture path (Nan 2017, Bao et al 2020. Liu et al proposed seven constraints with constraint strength ranging from 86.87% to 97.43% across three datasets (Liu et al 2023). From the content of section 3.4.2, the average constraint strength of the constraints proposed in this paper reaches 95%, which can effectively exclude the puncture paths that do not meet the clinical requirements.…”

Section: Discussionmentioning

confidence: 87%

“…(1) Personalized mass target point modeling The traditional path planning problem for paracentesis identifies the mass target point as the geometric centre of mass or the centre of stratification, which does not consider the mass displacement due to the patient's respiratory movements (Nan 2017, Bao et al 2020, Liu et al 2023 Compared with previous studies, the algorithm proposed in this paper classifies lung masses into two categories based on the length of the long axis of the ellipsoid fitted to the mass. Considering that the patient's respiratory motion causes displacement of the lung mass, this algorithm provides a personalized mass target point selection scheme for each patient based on the mass size.…”

Section: Discussionmentioning

confidence: 99%

“…(3) Optimal path selection algorithm based on fuzzy optimization Puncture surgery path planning problems are multi-objective optimization problems. The traditional optimal path selection schemes include two types of weighting methods (Baegert et al 2007a, 2007b, Ren et al 2014 and Pareto optimization methods (Nan 2017, Zhang et al 2019, Bao et al 2020, Zhong et al 2022, Liu et al 2023. This paper applies fuzzy optimization ideas to the puncture surgery path planning problem for the first time, which provides a new direction of thinking for solving multiobjective optimization problems in medicine.…”

Section: Discussionmentioning

confidence: 99%

“…In the current study, the investigators usually used the stratified centre of mass as the target point on the mass for the puncture procedure (Nan 2017, Bao et al 2020, Liu et al 2023. In this section, comparative experiments conducted using the adaptive fitting 3D sphere proposed in this algorithm and the stratified centre of mass are reported.…”

Section: Comparative Experiments With Related Workmentioning

confidence: 99%

“…They used six sets of chest CT data and six sub-objective functions, as well as the concept of Pareto optimization, to find the optimal puncture path. Liu et al (2023) use the relaxed Pareto and heptagonal adaptive constraint methods for optimal path selection. He et al (2023) combined the clinical preferences of doctors with Pareto thinking, balancing the impact of objective algorithms and doctors' subjective preferences on path planning.…”

Section: Introductionmentioning

confidence: 99%

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Path planning algorithm for percutaneous puncture lung mass biopsy procedure based on the multi-objective constraints and fuzzy optimization

Zhang,

Han

et al. 2024

Phys. Med. Biol.

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Objective. The percutaneous puncture lung mass biopsy procedure, which relies on preoperative CT images, is considered the gold standard for determining the benign or malignant nature of lung masses. However, the traditional lung puncture procedure has several issues, including long operation times, a high probability of complications, and high exposure to CT radiation for the patient, as it relies heavily on the surgeon's clinical experience. Approach. To address these problems, a multi-constrained objective optimization model based on clinical criteria for the percutaneous puncture lung mass biopsy procedure has been proposed. Additionally, based on fuzzy optimization, a multidimensional spatial Pareto front algorithm has been developed for optimal path selection. The algorithm finds optimal paths, which are displayed on 3D images, and provides reference points for clinicians' surgical path planning. Main results. To evaluate the algorithm's performance, 25 data sets collected from the Second People's Hospital of Zigong were used for prospective and retrospective experiments. The results demonstrate that 92% of the optimal paths generated by the algorithm meet the clinicians' surgical needs. Significance. The algorithm proposed in this paper is innovative in the selection of mass target point, the integration of constraints based on clinical standards, and the utilization of multi-objective optimization algorithm. Comparison experiments have validated the better performance of the proposed algorithm. From a clinical standpoint, the algorithm proposed in this paper has a higher clinical feasibility of the proposed pathway than related studies, which reduces the dependency of the physician's expertise and clinical experience on pathway planning during the percutaneous puncture lung mass biopsy procedure.

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Section: Discussionmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 99%