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Performance of mid infrared spectroscopy in skin cancer cell type identification

机译:中红外光谱在皮肤癌细胞类型鉴定中的性能

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Marker free optical spectroscopy is a powerful tool for the rapid inspection of pathologically suspicious skin lesions and the non-invasive detection of early skin tumors. This goal can be reached by the combination of signal localization and the spectroscopical detection of chemical cell signatures. We here present the development and application of mid infrared spectroscopy (midlR) for the analysis of skin tumor cell types and three dimensional tissue phantoms towards the application of midlR spectroscopy for fast and reliable skin diagnostics. We developed standardized in vitro skin systems with increasing complexity, from single skin cell types as fibroblasts, keratinocytes and melanoma cells, to mixtures of these and finally three dimensional skin cancer phantoms. The cell systems were characterized with different systems in the midlR range up to 12 μm. The analysis of the spectra by novel data processing algorithms demonstrated the clear separation of all cell types, especially melanoma cells. Special attention and algorithm training was required for closely related mesenchymal cell types as dedifferentiated melanoma cells and fibroblasts. Proof of concept experiments with mixtures of in vivo fluorescence labelled skin cell types allowed the test of the new algorithms performance for the identification of specific cell types. The intense training of the software systems with various samples resulted in a increased sensitivity and specificity of the combined midlR and software system. These data highlight the potential of midlR spectroscopy as sensitive and specific future optical biopsy technology.
机译:无标记光谱是快速检查病理学可疑的皮肤病变和无创检测早期皮肤肿瘤的有力工具。通过将信号定位和化学细胞标记的光谱检测结合起来可以实现此目标。我们在此介绍中红外光谱(midlR)的开发和应用,以分析皮肤肿瘤细胞类型和三维组织体模,以实现midlR光谱用于快速可靠的皮肤诊断。我们开发了越来越复杂的标准化体外皮肤系统,从单一的皮肤细胞类型(如成纤维细胞,角质形成细胞和黑色素瘤细胞)到这些的混合物,最后是三维皮肤癌模型。细胞系统的特征在于在MidIR范围高达12μm的不同系统。通过新颖的数据处理算法对光谱进行的分析表明,所有细胞类型(尤其是黑色素瘤细胞)均能清晰分离。对于密切相关的间充质细胞类型(如未分化的黑色素瘤细胞和成纤维细胞),需要特别注意和进行算法培训。使用体内荧光标记的皮肤细胞类型的混合物进行概念验证实验,可以测试用于识别特定细胞类型的新算法的性能。对带有各种样本的软件系统进行了严格的培训,从而使MidIR和软件组合系统的灵敏度和特异性都得到了提高。这些数据凸显了MidlR光谱技术作为未来灵敏且特定的光学活检技术的潜力。

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