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Discrimination of brain tumours and dysplastic tissues through multimodal fibre-probe spectroscopy

机译:通过多模式纤维探针光谱辨别脑肿瘤和消化塑性组织

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Optical spectroscopy is a fast, label-free and non-invasive method for analysing tissue composition and, thus, has the potential for improving standard diagnostic capabilities. This is particularly relevant for brain surgery due to the lack of contrast between diseased tissues (e.g. malformations and tumours) and the surrounding brain. In this study, we used an optical fibre-probe system combining multiple spectroscopic techniques for analysing ex vivo human brain biopsies taken from both tumour and dysplastic tissues. Specifically, the probe - based on a fibre-bundle with optical fibres of various size and properties - allowed performing spectroscopic measurements based on fluorescence, Raman, and diffuse reflectance spectroscopy. Two visible laser diodes were used for fluorescence spectroscopy, a laser diode emitting in the NIR was used for Raman spectroscopy, and a fibre-coupled halogen lamp for diffuse reflectance. All spectral recordings were done within 30 minutes from surgical resection, and optical inspection required less than 2 minutes for each sample. The recorded data were analysed using Principal Component Analysis (PCA) for obtaining an automated classification of the examined samples based on the intrinsic spectral information provided by all three techniques. The presented method demonstrated high sensitivity and specificity in discriminating different tissue types in good agreement with histopathological examination. Furthermore, we found that the multimodal approach is crucial for improving diagnostic capabilities beyond what can be achieved from individual techniques.
机译:光学光谱是一种快速,无标记和非侵入性方法,用于分析组织组合物,因此具有改善标准诊断能力的可能性。由于患病组织(例如畸形和肿瘤)和周围大脑之间缺乏对比,这与脑外手术特别相关。在该研究中,我们使用了一种光纤探针系统,所述光纤探针系统组合多种光谱技术,用于分析来自肿瘤和消化血管组织的离体人脑活组织检查。具体地,探针 - 基于具有各种尺寸和性质的光纤的纤维束 - 允许基于荧光,拉曼和漫反射光谱进行的光谱测量。两个可见激光二极管用于荧光光谱,在NIR中发出的激光二极管用于拉曼光谱,以及用于漫射反射的纤维耦合卤素灯。所有光谱记录均在30分钟内从外科切除术进行,并且每个样品需要少于2分钟的光学检查。使用主成分分析(PCA)分析记录的数据,用于基于所有三种技术提供的内在光谱信息获得所检查样本的自动分类。呈现的方法表明,与组织病理学检查良好的协议,鉴别不同的组织类型,表现出高的敏感性和特异性。此外,我们发现多模式方法对于提高超出各个技术可以实现的诊断能力至关重要。

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