首页> 外文会议>Conference on Biomedical Vibrational Spectroscopy and Biohazard Detection Technologies; 20040125-20040127; San Jose,CA; US >Diagnosis of atherosclerosis in human carotid artery by FT-Raman spectroscopy: Principal Components Analysis algorithm
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Diagnosis of atherosclerosis in human carotid artery by FT-Raman spectroscopy: Principal Components Analysis algorithm

机译:FT-拉曼光谱法诊断人颈动脉粥样硬化:主成分分析算法

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FT- Raman Spectroscopy (FT-Raman) could allow identification and evaluation of human atherosclerotic lesions. A Raman spectrum can provide biochemical information of arteries which can help identifying the disease status and evolution. In this study, it is shown the results of FT-Raman for identification of human carotid arteries in vitro. Fragments of human carotid arteries were analyzed using a FT-Raman spectrometer with a Nd:YAG laser at 1064nm operating at an excitation power of 300mW. Spectra were obtained with 250 scans and spectral resolution of 4 cm~(-1). Each collection time was approximately 8 min. A total of 75 carotid fragments were spectroscopically scanned and FT-Raman results were compared with histopathology. Principal Components Analysis (PCA) was used to model an algorithm for tissue classification into three categories: normal, atherosclerotic plaque without calcification and atherosclerotic plaque with calcification. Non-atherosclerotic (normal) artery, atherosclerotic plaque and calcified plaque exhibit different spectral signatures related to biochemicals presented in each tissue type, such as, bands of collagen and elastin (proteins), cholesterol and its esters and calcium hydroxyapatite and carbonate apatite respectively. Results show that there is 96% match between classifications based on PCA algorithm and histopathology. The diagnostic applied over all 75 samples had sensitivity and specificity of about 89% and 100%, respectively, for atherosclerotic plaque and 100% and 98% for calcified plaque.
机译:FT-拉曼光谱(FT-Raman)可以识别和评估人的动脉粥样硬化病变。拉曼光谱可以提供动脉的生化信息,有助于确定疾病的状态和演变。在这项研究中,显示了FT-拉曼光谱在体外鉴定人颈动脉的结果。使用FT-Raman光谱仪和1064nm的Nd:YAG激光器以300mW的激发功率对人颈动脉的碎片进行分析。通过250次扫描获得光谱,光谱分辨率为4 cm〜(-1)。每次收集时间约为8分钟。光谱分析了总共75个颈动脉碎片,并将FT-Raman结果与组织病理学进行了比较。主成分分析(PCA)用于对组织分类算法进行建模,该算法分为三类:正常,无钙化的动脉粥样硬化斑块和有钙化的动脉粥样硬化斑块。非动脉粥样硬化(正常)动脉,动脉粥样硬化斑块和钙化斑块在每种组织类型中均表现出与生化物质相关的不同光谱特征,例如胶原蛋白和弹性蛋白(蛋白质),胆固醇及其酯类,羟基磷灰石钙和碳酸盐磷灰石。结果表明,基于PCA算法的分类与组织病理学之间的匹配率为96%。适用于所有75个样品的诊断试剂对动脉粥样硬化斑块的敏感性和特异性分别约为89%和100%,对于钙化斑块的敏感性和特异性分别为100%和98%。

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