基于遗传算法的肿瘤热疗有效热区优化方法研究

提出一种肿瘤热疗中优化求解预期有效热区分布问题的方法，其思路是根据预定肿瘤组织靶区加热温度和避免正常组织过热的要求，引入目标函数和有关权重系数，在应用有限元法求解加热电磁场方程和生物传热方程过程中，通过遗传算法迭代修正加热物理参数，使目标函数达到极小值，获得达到理想热汤分布的优化解。该方法首次使用简化人体真实组织结构的非均质模型并应用于三极板射频电容热疗装置，获得满意的仿真计算优化结果。这项肿瘤热疗有效热区优化控制技术将对热疗装置设计和临床方案制定皆有重要的应用价值。

A Study on the Optimization of the Effective Heating Field in Hyperthermia Based on Genetic Algorithms

An inverse optimization method, applied in hyperthermia to search for the ideal heating physical configurations in the expected temperature distribution of heat-field, is proposed. First, in order to realize the target temperature distribution of tumor tissues and avoid the over-heating of healthy tissues, an objective function and some related weight coefficients are introduced. Next, based on the 2D finite element method(FEM) and the solutions of Laplace and Pennes' bio-heat transfer equations, the genetic algorithm(GA) recursively modifies the heating conditions to minimize the objective function, that is, the difference between the calculated temperature distribution and the expected one, satisfactory simulation results are demonstrated in 3aplicator RFcapacitive hyperthermia of a simplified non-homogeneous human model obtained from a XCT human slice. This technology of target heat-field temperature control is believed to have an important practical value in the design of hyperthermia devices and clinical applications.