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Estimation of the number of fluorescent end-members for quantitative analysis of multispectral FLIM data

机译:估计用于多光谱FLIM数据定量分析的荧光末端成员的数量

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摘要

Multispectral fluorescence lifetime imaging (m-FLIM) can potentially allow identifying the endogenous fluorophores present in biological tissue. Quantitative description of such data requires estimating the number of components in the sample, their characteristic fluorescent decays, and their relative contributions or abundances. Unfortunately, this inverse problem usually requires prior knowledge about the data, which is seldom available in biomedical applications. This work presents a new methodology to estimate the number of potential endogenous fluorophores present in biological tissue samples from time-domain m-FLIM data. Furthermore, a completely blind linear unmixing algorithm is proposed. The method was validated using both synthetic and experimental m-FLIM data. The experimental m-FLIM data include in-vivo measurements from healthy and cancerous hamster cheek-pouch epithelial tissue, and ex-vivo measurements from human coronary atherosclerotic plaques. The analysis of m-FLIM data from in-vivo hamster oral mucosa identified healthy from precancerous lesions, based on the relative concentration of their characteristic fluorophores. The algorithm also provided a better description of atherosclerotic plaques in term of their endogenous fluorophores. These results demonstrate the potential of this methodology to provide quantitative description of tissue biochemical composition.
机译:多光谱荧光寿命成像(m-FLIM)可以潜在地识别生物组织中存在的内源性荧光团。此类数据的定量描述需要估计样品中组分的数量,其特征性的荧光衰减及其相对贡献或丰度。不幸的是,这个反问题通常需要有关数据的先验知识,而在生物医学应用中很少有。这项工作提出了一种新的方法,可以从时域m-FLIM数据估算生物组织样品中存在的潜在内源性荧光团的数量。此外,提出了一种完全盲线性分解算法。使用合成和实验m-FLIM数据验证了该方法。实验性m-FLIM数据包括来自健康和癌性仓鼠脸颊袋上皮组织的体内测量,以及来自人冠状动脉粥样斑块的离体测量。根据其特征荧光团的相对浓度,对来自仓鼠口腔粘膜的m-FLIM数据进行分析,可以从癌前病变中识别出健康状态。该算法还从内源性荧光团方面更好地描述了动脉粥样硬化斑块。这些结果证明了该方法在提供组织生化成分定量描述方面的潜力。

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