基于体外阻抗测量的恶性胶质瘤介电特性

目的研究脑胶质瘤生物电阻抗特性,探索出恶性胶质瘤组织与正常脑组织的特征性电参数,为区分恶性胶质瘤与正常脑组织提供依据。方法基于四电极法阻抗测量设计了一种体外阻抗测量传感器,利用普林斯顿阻抗分析仪Versa STAT3对10例裸鼠脑胶质瘤和脑组织进行阻抗测量,并对20Hz~250 k Hz范围内阻抗频谱特性曲线进行定量分析;结合生物阻抗谱理论,建立体外脑胶质瘤等效电路模型,并利用ZSimp Win对等效阻抗电路进行拟合仿真,以探讨脑胶质瘤在阻抗电路中的特性。结果胶质瘤的阻抗模值在20 Hz~250 k Hz范围内随频率的增大而减小,幅值曲线在200 Hz和50 k Hz附近各存在一个斜坡,这两个斜坡的斜度都小于对应的正常鼠脑组织的斜度。10组裸鼠体外实验中,胶质瘤和脑组织的虚部-实部图中有两个时间环节,可以用两个时间常数的等效电路代替,并且电路元件中的参数R1对于胶质瘤和脑组织差异明显。结论体外鼠脑胶质瘤与正常脑组织可以用阻抗特性曲线的斜坡值进行定量区别。此外,等效电路电参数中的R1也可以作为一个区分胶质瘤和脑组织的指标,这为临床检测和区分胶质瘤组织开拓了新的研究思路。

Dielectric properties of malignant gliomas based on in vitro bio-impedance measurements

Objective This paper studies on bio-impedance characteristics of malignant gliomas and brain tissues,then explores the characteristic electrical parameters and provides a fundamental basis to discriminate gliomas and normal brain tissues.Methods An in-vitro impedance sensor is designed based on four -electrode method.The impedance measurements on 10 cases of nude gliomas and brain tissues are performed using Princeton impedance analyzer VersaSTAT3 and then impedance spectrum characteristic curves are analyzed quantitatively from 20 Hz to 250 kHz.According to the electrochemical impedance spectroscopy principle,in vitro equivalent circuit model for glioma and brain tissues is established and the simulation with ZSimpWin is carried out to study the characteristics of glioma on impedance circuit model.Results Impedance magnitude varies oppositely as the frequency increases from 20 Hz to 250 kHz.Impedance spectrum curves around 200 Hz and 50 kHz have two slopes,respectively.And the slope scale for gliomas is less than that for normal brain tissues.There are two time constants in the imaginary-real plot and that can be expressed by equivalent circuit model.The parameter R1 in the circuit for glioma is significantly different from that for brain tissues.Conclusions The gliomas and normal brain tissues can be discriminated quantitatively by slope value of impedance spectrum curve.In addition,R1 in the equivalent circuit model can be viewed as an index to distinguish gliomas from normal brain tissues.The technique proposed in this paper provides a new method to detect and discriminate the gliomas from other normal tissues in cancer research.