Kowalski Marc E, Behnia Babak, Webb Andrew G, Jin Jian-Ming
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801-2991, USA.
IEEE Trans Biomed Eng. 2002 Nov;49(11):1229-41. doi: 10.1109/TBME.2002.804602.
A technique for the optimization of electromagnetic annular phased arrays (APAs) for therapeutic hyperthermia has been developed and implemented. The controllable inputs are the amplitudes and phases of the driving signals of each element of the array. Magnetic resonance imaging (MRI) is used to estimate noninvasively the temperature distribution based on the temperature dependence of the proton resonance frequency (PRF). A parametric model of the dynamics that couple the control inputs to the resultant temperature elevations is developed based on physical considerations. The unknown parameters of this model are estimated during a pretreatment identification phase and can be continuously updated as new measurement data become available. Based on the parametric model, a controller automatically chooses optimal phases and amplitudes of the driving signals of the APA. An advantage of this approach to optimizing the APA is that no a priori information is required, eliminating the need for patient-specific computational modeling and optimization. Additionally, this approach represents a first step toward employing temperature feedback to make the optimization of the APA robust with respect to modeling errors and physiological changes. The ability of the controller to choose therapeutically beneficial driving amplitudes and phases is demonstrated via simulation. Experimental results are presented which demonstrate the ability of the controller to choose optimal phases for the APA using only information from magnetic resonance thermometry (MRT).
一种用于治疗性热疗的电磁环形相控阵（APA）优化技术已被开发并实现。可控输入为阵列各元件驱动信号的幅度和相位。磁共振成像（MRI）用于基于质子共振频率（PRF）的温度依赖性无创估计温度分布。基于物理考虑，建立了将控制输入与所得温度升高相耦合的动力学参数模型。该模型的未知参数在预处理识别阶段进行估计，并可随着新测量数据的获取而不断更新。基于该参数模型，控制器自动选择APA驱动信号的最佳相位和幅度。这种优化APA的方法的一个优点是不需要先验信息，无需针对患者进行特定的计算建模和优化。此外，这种方法是朝着采用温度反馈使APA的优化对建模误差和生理变化具有鲁棒性迈出的第一步。通过仿真展示了控制器选择具有治疗益处的驱动幅度和相位的能力。给出了实验结果，这些结果证明了控制器仅使用来自磁共振测温（MRT）的信息为APA选择最佳相位的能力。
