Ding Lujia, Moser Michael, Luo Yigang, Zhang Wenjun, Zhang Bing
School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China.
Department of Surgery, University of Saskatchewan, Saskatoon, SK S7N 0W8, Canada.
J Biomech Eng. 2021 Jan 1;143(1). doi: 10.1115/1.4047551.
Irreversible electroporation (IRE), a relatively new energy-based tumor ablation technology, has shown itself in the last decade to be able to safely ablate tumors with favorable clinical outcomes, yet little work has been done on optimizing the IRE protocol to variously sized tumors. Incomplete tumor ablation has been shown to be the main reason leading to the local recurrence and thus treatment failure. The goal of this study was to develop a general optimization approach to optimize the IRE protocol for cervical tumors in different sizes, while minimizing the damage to normal tissues. This kind of approach can lay a foundation for future personalized treatment of IRE. First, a statistical IRE cervical tumor death model was built using previous data in our group. Then, a multi-objective optimization problem model was built, in which the decision variables are five IRE-setting parameters, namely, the pulse strength (U), the length of active tip (H), the number of pulses delivered in one round between a pair of electrodes (A), the distance between electrodes (D), and the number of electrodes (N). The domains of the decision variables were determined based on the clinical experience. Finally, the problem model was solved by using nondominated sorting genetic algorithms II (NSGA-II) algorithm to give respective optimal protocol for three sizes of cervical tumors. Every protocol was assessed by the evaluation criterion established in the study to show the efficacy in a more straightforward way. The results of the study demonstrate this approach can theoretically provide the optimal IRE protocol for different sizes of tumors and may be generalizable to other types, sizes, and locations of tumors.
不可逆电穿孔（IRE）是一种相对较新的基于能量的肿瘤消融技术，在过去十年中已证明能够安全地消融肿瘤并取得良好的临床效果，但在针对不同大小肿瘤优化IRE方案方面所做的工作很少。不完全肿瘤消融已被证明是导致局部复发进而治疗失败的主要原因。本研究的目的是开发一种通用的优化方法，以优化不同大小宫颈肿瘤的IRE方案，同时将对正常组织的损伤降至最低。这种方法可为未来IRE的个性化治疗奠定基础。首先，利用我们团队以前的数据建立了一个统计学IRE宫颈肿瘤死亡模型。然后，建立了一个多目标优化问题模型，其中决策变量是五个IRE设置参数，即脉冲强度（U）、有效尖端长度（H）、一对电极之间一轮输送的脉冲数（A）、电极间距（D）和电极数量（N）。决策变量的范围根据临床经验确定。最后，使用非支配排序遗传算法II（NSGA-II）算法求解该问题模型，以给出三种大小宫颈肿瘤各自的最佳方案。每个方案都通过本研究中建立的评估标准进行评估，以更直观地显示其疗效。研究结果表明，这种方法理论上可以为不同大小的肿瘤提供最佳的IRE方案，并且可能推广到其他类型、大小和位置的肿瘤。
