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脑组织参数近红外实时在位微创测量技术及其应用研究

Research on Real Time, in Vivo, Minimal Invasive Measurement of Brain Tissues’ Parameters by Near Infrared Spectroscopy and Its Application

【作者】 戴丽娟

【导师】 王惠南;

【作者基本信息】 南京航空航天大学 , 精密仪器及机械, 2008, 博士

【摘要】 脑组织光学、血氧和血流动力学参数的在位精确测量是生物医学领域中脑科学的重要研究内容,而这些参数的微创综合测量还未见报道,这些综合参数可能对脑组织类型识别、脑肿瘤定性分析、脑外科手术导航、脑功能基础研究等提供更丰富的参考信息。本文从双光纤微创探头在位测量的角度出发,以实现脑组织光学、血氧和血流动力学参数较高精度的微创综合测量为研究目标,在脑组织参数测量基础理论、脑组织内部光场分布、系统设计与定标、系统在基础医学中的应用等方面进行了深入研究。主要研究内容包括:基于小距离双光纤微创探头和稳定态光纤光谱仪设计一个多参数综合测量系统,并实现测量结果实时自动分析;有关测量参数的基础理论和经验公式研究,主要有吸收和漫反射光谱特征因子提取、人工神经网络和多元线性回归分析的特征因子建模、特征因子与光学、血氧和血流动力学参数关联等;系统在大鼠C6胶质瘤综合(光学、血氧与血流)参数测量中的应用研究。论文在一些关键性技术上取得了如下创新性成果:1.设计了生物组织参数实时在位微创测量实验系统,可以同时获取穿刺轨迹上生物组织的约化散射系数、吸收系数、血氧饱和度、总血红蛋白浓度、血流量和血容量。2.采用模型实验定标法获得双光纤微创系统约化散射系数、血氧饱和度和总血红蛋白浓度的经验公式,测试精度在动物实验中得到验证,结果准确可靠。3.在血氧饱和度的测试上,利用人工神经网络建立了光谱分析数学模型,测量精度和传统的脑组织血氧饱和度测试方法相比有了一定的提高。4.利用本系统在临床医学上进行了初步应用探索,主要研究了脑胶质瘤的近红外测试特征因子。实验中实时在位获得了SD大鼠C6胶质瘤的光学、血氧和血流动力学参数,发现这些参数在胶质瘤和正常脑组织间有较显著的差异性,为疾病诊断提供了参考。5.将近红外测试技术和MRI影像结合对胶质瘤的病理特性进行了探索,研究了SD大鼠C6胶质瘤近红外测试特征因子与胶质瘤病理分级的关联,提出了近红外测试特征因子用于胶质瘤分级的方案,为临床医学应用奠定了良好的基础。

【Abstract】 In vivo accurate measurements of tissue optical, blood oxygenic and blood dynamic parameters are important contents of brain science researching of biomedical fields. However, all parameters’simultaneous measurment with one minimally-invasive system havn’t been reported, which can provide more useful information and more characteristic factors for brain tissue recognization, brain tumor quality analysis, neurosurgery operation guidance and brain function research.This study is based on minimally-invasive, in vivo measurement with a needle probe including two fibers. The researching goals are exact measurement of brain tissue optical, blood oxygenic and blood dynamic parameters with a minimally-invasive system. Basical measurement theories of brain tissue’s paremeters, light distributions in brain tissues, system design, standard establishment and calibration, and clinic application are studied. The main contents of this study include building a real time in vivo measurement system which can measure and analysis three kinds of parameters automatically based on a steady-state fiber spectrometeric and a minimally-invasive needle probe, researching about the basical theories of measurements of brain tissue paremeters and experimental equations, including extracting spectra characteristics from absorption and scattering spectra, characteristic modeling of artificial neural network and regression analysis, building relationships between the characteristics and optical, blood oxygenic and blood dynamic parameters, and applying this system in measuring parameters (optical, blood oxygenic and blood dynamic parameters) of rats’C6 glioma. The main achievements and innovative results:1. An experimental system of a minimally-invasive, real time, in vivo tissue parameters measurement system, which realizes simultaneous measurement of reduced scattering coefficient, absorption coefficient, hemoglobin oxygen saturation, total hemoglobin concentration, blood flow and blood volume of the puncturing track.2. Empiricism equations for reduced scattering coefficient, hemoglobin oxygen saturation and total hemoglobin concentration are obtained through model experiments. These equations’precisions are validated in animal experiments. The results are exact and reliable.3. Artifical Neural Network is used to design spectra analysis model in minimal-invasive measurement of hemoglobin oxygen saturation, which has higher precision compared with traditional methods in measurement of hemoglobin oxygen saturation.4. Preliminary exploring of system application in clinical medicine. In vivo optical, blood oxygenic and blood dynamic parameters of C6 glioma are obtained in real time. Obvious diversities between C6 glioma and normal brain tissue are found from these parameters, which can supply reference for tumor diagnose.5. Pathological characters of glioma are explored by combining MRI and near infrared technique. Relationship between these parameters and pathological level are discussed and some methods for glioma classification by these parameters are proposed, which make good foundation for clinical application.

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