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A practical pretreatment planning method of multiple puncturing for thermal ablation surgery
Biocybernetics and Biomedical Engineering ( IF 6.4 ) Pub Date : 2020-08-30 , DOI: 10.1016/j.bbe.2020.08.004
Jing Li , Yuanqi Xu , Nanyan Shen , Lanyun Feng , Zhuang Ran , Zongqian Deng

Thermal ablation surgery serves as one of the main approaches to treat liver tumors. The pretreatment planning, which highly demands the experience and ability of the physician, plays a vital role in thermal ablation surgery. The planning of multiple puncturing is necessary for avoiding the possible interference, destroying the tumor thoroughly and minimizing the damage to healthy tissue. A GPU-independent pretreatment planning method is proposed based on multi-objective optimization, which takes the most comprehensive constraints into consideration. An adaptive decision method of closing kernel size based on Jenks Natural Breaks is utilized to describe the final feasible region more accurately. It should be noted that the reasonable procedure of solving the feasible region and the use of KD tree based high dimensional search approach are used to enhance the computational efficiency. Seven constraints are handled within 7 s without GPU acceleration. The Pareto front points of nine puncturing tests are obtained in 5 s by using the NSGA-II algorithm. To evaluate the maximum difference and similarity between the planning results and the puncturing points recommended by the physician, Hausdorff distance and overlap rate are respectively developed, the Hausdorff distances are within 30 mm in seven out of nine tests and the average value of overlap rate is 73.0% for all the tests. The puncturing paths of high safety and clinical-practice compliance can be provided by the proposed method, based on which the pretreatment planning software developed can apply to the interns’ training and ability evaluating for thermal ablation surgery.



中文翻译:

实用的热消融术多穿刺术前计划方法

热消融手术是治疗肝肿瘤的主要方法之一。预处理计划非常需要医生的经验和能力,在热消融手术中起着至关重要的作用。为了避免可能的干扰,彻底破坏肿瘤并使对健康组织的损害最小化,必须进行多次穿刺计划。提出了一种基于多目标优化的独立于GPU的预处理规划方法,该方法考虑了最全面的约束条件。利用基于Jenks自然断裂的闭合核尺寸的自适应决策方法,可以更准确地描述最终的可行区域。应该注意的是,使用合理的方法来求解可行区域并使用基于KD树的高维搜索方法来提高计算效率。无需GPU加速即可在7 s内处理七个约束。使用NSGA-II算法在5 s内获得了九次穿刺测试的帕累托前沿。为了评估计划结果与医师推荐的穿刺点之间的最大差异和相似性,分别开发了Hausdorff距离和重叠率,在九次测试中的七次中,Hausdorff距离在30 mm以内,重叠率的平均值为所有测试的73.0%。所提出的方法可以提供高安全性和临床实践依从性的穿刺路径,

更新日期:2020-09-28
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