Toward the Separation of Different Heating Mechanisms in Magnetic Particle Hyperthermia

磁性纳米粒子 粒径 磁热疗 材料科学 纳米颗粒 琼脂糖 粘度 磁选 水溶液 降水 磁场 磁滞 航程(航空) 化学工程 核磁共振 纳米技术 化学 色谱法 复合材料 凝聚态物理 物理化学 物理 量子力学 气象学 工程类 冶金
作者
Eirini Myrovali,Kyrillos Papadopoulos,Georgia Charalampous,Paraskevi Kesapidou,G. Vourlias,Th. Kehagias,M. Angelakeris,Ulf Wiedwald
出处
期刊:ACS omega [American Chemical Society]
卷期号:8 (14): 12955-12967 被引量:18
标识
DOI:10.1021/acsomega.2c05962
摘要

Magnetic particle hyperthermia (MPH) is a promising method for cancer treatment using magnetic nanoparticles (MNPs), which are subjected to an alternating magnetic field for local heating to the therapeutic range of 41-45 °C. In this window, the malignant regions (i.e., cancer cells) undergo a severe thermal shock while healthy tissues sustain this thermal regime with significantly milder side effects. Since the heating efficiency is directly associated with nanoparticle size, MNPs should acquire the appropriate size to maximize heating together with minimum toxicity. Herein, we report on facile synthetic controls to synthesize MNPs by an aqueous precipitation method, whereby tuning the pH values of the solution (9.0-13.5) results in a wide range of average MNP diameters from 16 to 76 nm. With respect to their size, the structural and magnetic properties of the MNPs are evaluated by adjusting the most important parameters, i.e. the MNP surrounding medium (water/agarose), the MNP concentration (1-4 mg mL-1), and the field amplitude (20-50 mT) and frequency (103, 375, 765 kHz). Consequently, the maximum heating efficiency is determined for each MNP size and set of parameters, outlining the optimum MNPs for MPH treatment. In this way, we can address the different heat generation mechanisms (Brownian, Néel, and hysteresis losses) to different sizes and separate Brownian and hysteresis losses for optimized sizes by studying the heat generation as a function of the medium viscosity. Finally, MNPs immobilized into agarose solution are studied under low-field MPH treatment to find the optimum conditions for clinical applications.

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