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首页> 外文期刊>Methods of information in medicine >New methods for time-resolved fluorescence spectroscopy data analysis based on the Laguerre expansion technique--applications in tissue diagnosis.
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New methods for time-resolved fluorescence spectroscopy data analysis based on the Laguerre expansion technique--applications in tissue diagnosis.

机译:基于Laguerre扩展技术的时间分辨荧光光谱数据分析的新方法-在组织诊断中的应用

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OBJECTIVES: A new deconvolution method for the analysis of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data is introduced and applied for tissue diagnosis. METHOD: The intrinsic TR-LIFS decays are expanded on a Laguerre basis, and the computed Laguerre expansion coefficients (LEC) are used to characterize the sample fluorescence emission. The method was applied for the diagnosis of atherosclerotic vulnerable plaques. RESULTS: At a first stage, using a rabbit atherosclerotic model, 73 TR-LIFS in-vivo measurements from the normal and atherosclerotic aorta segments of eight rabbits were taken. The Laguerre deconvolution technique was able to accurately deconvolve the TR-LIFS measurements. More interesting, the LEC reflected the changes in the arterial biochemical composition and provided discrimination of lesions rich in macrophages/foam-cells with high sensitivity (> 85%) and specificity (> 95%). At a second stage, 348 TR-LIFS measurements were obtained from the explanted carotid arteries of 30 patients. Lesions with significant inflammatory cells (macrophages/foam-cells and lymphocytes) were detected with high sensitivity (> 80%) and specificity (> 90%), using LEC-based classifiers. CONCLUSION: This study has demonstrated the potential of using TR-LIFS information by means of LEC for in vivo tissue diagnosis, and specifically for detecting inflammation in atherosclerotic lesions, a key marker of plaque vulnerability.
机译:目的:介绍一种新的去卷积方法,用于分析时间分辨激光诱导荧光光谱(TR-LIFS)数据,并将其用于组织诊断。方法:本征TR-LIFS衰减在Laguerre的基础上进行扩展,并使用计算出的Laguerre扩展系数(LEC)表征样品的荧光发射。该方法用于动脉粥样硬化易损斑块的诊断。结果:在第一阶段,使用兔动脉粥样硬化模型,从八只兔的正常和动脉粥样硬化主动脉段进行了73次TR-LIFS体内测量。 Laguerre解卷积技术能够准确地解卷积TR-LIFS测量值。更有趣的是,LEC反映了动脉生化成分的变化,并以高灵敏度(> 85%)和特异性(> 95%)区分富含巨噬细胞/泡沫细胞的病变。在第二阶段,从30位患者的颈外动脉获得了348次TR-LIFS测量值。使用基于LEC的分类器,具有高灵敏度(> 80%)和特异性(> 90%)的发炎细胞(巨噬细胞/泡沫细胞和淋巴细胞)具有明显的病变。结论:这项研究证明了通过LEC利用TR-LIFS信息进行体内组织诊断的潜力,特别是可用于检测斑块易损性的关键指标动脉粥样硬化病变中的炎症。

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