Preoperative path planning algorithm for lung puncture biopsy based on path constraint and multidimensional space distance optimization

He, Ling; Meng, Yuxuan; Zhong, Jianquan; TANG, Ling; Chui, Chee-Kong; Zhang, Jing

doi:10.1016/j.bspc.2022.104304

Cited by 4 publications

(2 citation statements)

References 51 publications

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“…During the procedure, the puncture path should be as far as possible from vital organs in the chest (He et al 2023). In addition to the vital organs described in section 2.2.3., the vascular density around the path should be considered to minimize the risk of tissue bleeding.…”

Section: Distance Conditionsmentioning

confidence: 99%

“…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. However, there are currently few percutaneous puncture procedure path planning systems specifically designed for pulmonary masses.…”

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: Distance Conditionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%