SIGNIFICANCE In multiphoton microscopy, two-photon excited fluorescence (TPEF) spectra carry valuable information on morphological and functional biological features. For measuring these biomarkers, separation of different parts of the fluorescence spectrum into channels is typically achieved by the use of optical band pass filters. However, spectra from different biomarkers can be unknown or overlapping, creating a crosstalk in between the channels. Previously, establishing these channels relied on prior knowledge or heuristic testing. AIM The presented method aims to provide spectral bands with optimal separation between groups of specimens expressing different biomarkers. APPROACH We have developed a system capable of resolving TPEF with high spectral resolution for the characterization of biomarkers. In addition, an algorithm is created to simulate and optimize optical band pass filters for fluorescence detection channels. To demonstrate the potential improvements in cell and tissue classification using these optimized channels, we recorded spectrally resolved images of cancerous (HT29) and normal epithelial colon cells (FHC), cultivated in 2D layers and in 3D to form spheroids. To provide an example of an application, we relate the results with the widely used redox ratio. RESULTS We show that in the case of two detection channels, our system and algorithm enable the selection of optimized band pass filters without the need of knowing involved fluorophores. An improvement of 31,5% in separating different 2D cell cultures is achieved, compared to using established spectral bands that assume NAD(P)H and FAD as main contributors of autofluorescence. The compromise is a reduced SNR in the images. CONCLUSIONS We show that the presented method has the ability to improve imaging contrast and can be used to tailor a given label-free optical imaging system using optical band pass filters targeting a specific biomarker or application.

中文翻译：

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选择最佳光谱带以改进多光子显微镜中自发荧光生物标志物的检测。

意义在多光子显微镜中，双光子激发荧光 (TPEF) 光谱携带有关形态学和功能生物学特征的宝贵信息。为了测量这些生物标志物，通常通过使用光学带通滤波器将荧光光谱的不同部分分离到通道中。然而，来自不同生物标志物的光谱可能未知或重叠，从而在通道之间产生串扰。以前，建立这些渠道依赖于先验知识或启发式测试。目的所提出的方法旨在提供在表达不同生物标志物的样本组之间具有最佳分离的光谱带。方法 我们已经开发出一种能够以高光谱分辨率解析 TPEF 的系统，用于表征生物标志物。此外，创建了一种算法来模拟和优化荧光检测通道的光学带通滤波器。为了证明使用这些优化通道在细胞和组织分类方面的潜在改进，我们记录了癌变 (HT29) 和正常上皮结肠细胞 (FHC) 的光谱分辨图像，在 2D 层和 3D 中培养以形成球体。为了提供应用示例，我们将结果与广泛使用的氧化还原比相关联。结果我们表明，在两个检测通道的情况下，我们的系统和算法能够选择优化的带通滤波器，而无需知道所涉及的荧光团。与使用假定 NAD(P)H 和 FAD 作为自发荧光的主要贡献者的已建立光谱带相比，在分离不同的 2D 细胞培养物方面实现了 31.5% 的改进。妥协是降低图像中的 SNR。结论我们表明，所提出的方法具有提高成像对比度的能力，并可用于使用针对特定生物标志物或应用的光学带通滤波器来定制给定的无标记光学成像系统。