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Diagnosis of atherosclerosis in human carotid artery by FT-Raman spectroscopy: Principal Components Analysis algorithm

机译:FT-Raman光谱分析算法人类颈动脉动脉粥样硬化诊断

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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)可以识别和评估人类粥样硬化病变。拉曼光谱可以提供动脉的生化信息,其可以有助于识别疾病状态和进化。在这项研究中,示出了FT-拉曼的结果,用于鉴定体外人类颈动脉。使用具有Nd:YAG激光器的FT-拉曼光谱仪分析人类颈动脉的片段,在1064nm以300mW的激励功率操作。用250个扫描和4cm〜(-1)的光谱分辨率获得光谱。每个收集时间约为8分钟。共有75片颈动脉碎片被光谱扫描,并与组织病理学进行了比较FT-Raman结果。主要成分分析(PCA)用于将组织分类算法模拟为三类:正常,动脉粥样硬化斑块,无钙化和动脉粥样硬化斑块与钙化。非动脉粥样硬化(正常)动脉,动脉粥样硬化斑块和钙化斑块与各组织类型中呈现的生物化学相关的不同光谱签名,例如胶原蛋白和弹性蛋白(蛋白质),胆固醇及其酯和羟基磷灰石和碳酸钙磷灰石。结果表明,基于PCA算法和组织病理学的分类之间存在96%匹配。在所有75个样品上施加的诊断分别具有约89%和100%的敏感性和特异性,用于动脉粥样硬化斑块和钙化斑块的100%和98%。

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