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首页> 外文期刊>IEEE Transactions on Magnetics >Simultaneous Optimization of Injection Dose and Location for Magnetic Hyperthermia Using Metaheuristic Algorithms
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Simultaneous Optimization of Injection Dose and Location for Magnetic Hyperthermia Using Metaheuristic Algorithms

机译：使用元启发式算法同时优化磁热疗的注射剂量和位置

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摘要

Magnetic hyperthermia is a tumor therapeutic modality with great potential. It ablates malignant cells using the heat from magnetic nanoparticles (MNPs) subjected to an alternating magnetic field. The temperature profile obtained during treatment is a function of the properties of the magnetic field and MNPs, and also the injection strategy. The injection strategy plays an important role in the quality of magnetic hyperthermia treatment since proper injection allows a more homogeneous temperature field to be obtained with less harm to normal tissue. This article considers a Gaussian distribution for a temperature around an injection site (IS) and proposes several methods to optimize the treatment temperature for a proposed model by considering both the injection dose and the IS locations simultaneously. Two metaheuristic algorithms are considered in this article, namely, particle swarm optimization (PSO) and simulated annealing (SA). In general, the PSO algorithm presents better results than the SA due to its smaller dependence on the initial value, but its convergence is slower. Simulation results demonstrate that treatment efficiency can be significantly increased by using the proposed approach when the PSO algorithm is considered for the simultaneous optimization of injection strategy and injection location for magnetic hyperthermia.
机译：磁热疗法是一种具有巨大潜力的肿瘤治疗方法。它利用受到交变磁场作用的磁性纳米颗粒（MNP）的热量消融恶性细胞。在治疗过程中获得的温度曲线是磁场和MNPs以及注射策略的函数。注射策略在磁热疗的质量中起着重要作用，因为适当的注射可以在不损害正常组织的情况下获得更均匀的温度场。本文考虑了注射部位（IS）周围温度的高斯分布，并提出了通过同时考虑注射剂量和IS位置来优化所提出模型的处理温度的几种方法。本文考虑了两种元启发式算法，即粒子群优化（PSO）和模拟退火（SA）。通常，由于PSO算法对初始值的依赖性较小，因此它比SA算法显示出更好的结果，但收敛速度较慢。仿真结果表明，当考虑将PSO算法同时优化磁疗的注射策略和注射位置时，使用所提出的方法可以显着提高治疗效率。

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