Multiple objective planning for thermal ablation of liver tumors
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ORIGINAL ARTICLE
Multiple objective planning for thermal ablation of liver tumors Libin Liang1,2 · Derek Cool3 · Nirmal Kakani4 · Guangzhi Wang1
· Hui Ding1 · Aaron Fenster2,3
Received: 21 March 2020 / Accepted: 19 August 2020 © CARS 2020
Abstract Purpose Preoperative treatment planning is key to ensure successful thermal ablation of liver tumors. The planning aims to minimize the number of electrodes required for complete ablation and the damage to the surrounding tissues while satisfying multiple clinical constraints. This is a challenging multiple objective planning problem, in which the trade-off between different objectives must be considered. Methods We propose a novel method to solve the multiple objective planning problem, which combines the set cover-based model and Pareto optimization. The set cover-based model considers multiple clinical constraints and generates several clinically feasible treatment plans, among which the Pareto optimization is performed to find the trade-off between different objectives. Results We evaluated the proposed method on 20 tumors of 11 patients in two different situations used in common thermal ablation approaches: with and without the pull-back technique. Pareto optimal plans were found and verified to be clinically acceptable in all cases, which can find the trade-off between the number of electrodes and the damage to the surrounding tissues. Conclusion The proposed method performs well in the two different situations we considered: with or without the pull-back technique. It can generate Pareto optimal plans satisfying multiple clinical constraints. These plans consider the trade-off between different planning objectives. Keywords Treatment planning · Multiple objectives · Set cover · Pareto optimization
Introduction
This paper is based on the work: “Liang L., Cool D., Kakani N., Wang G., Ding H., Fenster A. (2019) Development of a Multi-objective Optimized Planning Method for Microwave Liver Tumor Ablation. In: Shen D. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science, vol 11768. Springer, Cham.”
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Guangzhi Wang [email protected] Libin Liang [email protected] Derek Cool [email protected] Nirmal Kakani [email protected] Hui Ding [email protected] Aaron Fenster [email protected]
Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver and is also among the leading causes of cancer-related mortality [1]. Image-guided thermal ablation is currently becoming widely accepted for the treatment of HCC by ablation of the tumor using a needle-like electrode to heat or freeze the targeted tissues [2]. The main thermal ablation modalities include radiofrequency ablation (RFA), microwave ablation (MWA), and cryoablation.
1
Department of Biomedical Engineering, School of Medicine, Tsinghua University, Room C249, Beijing 100084, People’s Republic of China
2
Robarts Research Institute, Western University, London, ON, Canada
3
Department o
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