Phasor Representation Approach for Rapid Exploratory Analysis of Large Infrared Spectroscopic Imaging Data Sets.
Phasor Representation Approach for Rapid Exploratory Analysis of Large Infrared Spectroscopic Imaging Data Sets.
复制标题
用于快速探索性分析大型红外光谱成像数据集的相量表示方法。
DOI：
10.1021/acs.analchem.3c01539
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发表时间：
2023
影响因子：
7.4
通讯作者：
Bhargava,Rohit
中科院分区：
文献类型：
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作者：
Mukherjee,SudiptaS;Bhargava,Rohit
红外 (IR) 光谱成像对于数字组织病理学可能有用，因为它提供空间分辨的分子吸收光谱，随后可以通过强大的人工智能方法产生有用的信息。使用红外成像数据进行化学病理学的典型分析流程通常涉及分割、评估和分析的迭代过程，因此需要快速数据探索。在这里，我们提出了一种基于光谱相量表示的快速、可靠和直观的方法，并讨论了其对红外成像数据的独特适用性。我们模拟红外光谱中存在的不同特征并讨论它们对相量波形的影响；同样，我们在变换空间中进行红外图像分析，以了解光谱相似性和方差。我们使用各种样本证明了相量分析在生物医学组织成像中的潜力，使用新鲜冷冻手术前列腺切除和福尔马林固定石蜡包埋的乳腺癌组织微阵列样本作为跨越常见组织病理学实践的模型系统。为了进一步证明这种方法的通用性，我们将该方法应用于不同实验条件下的数据，包括使用透射和透反射模式的标准（5.5 μm × 5.5 μm 像素大小）和高清（1.1 μm × 1.1 μm 像素大小）傅里叶变换红外 (FTIR) 光谱成像。我们的方法的定量分割结果与之前的研究进行了比较，显示出良好的一致性和快速的可视化。该方法快速、易于使用，并且能够很好地解读成分差异，为红外成像数据的探索性分析提供了一种方便的工具。
Infrared (IR) spectroscopic imaging is potentially useful for digital histopathology as it provides spatially resolved molecular absorption spectra, which can subsequently yield useful information by powerful artificial intelligence methods. A typical analysis pipeline in using IR imaging data for chemical pathology often involves iterative processes of segmentation, evaluation, and analysis that necessitate rapid data exploration. Here, we present a fast, reliable, and intuitive method based on a phasor representation of spectra and discuss its unique applicability for IR imaging data. We simulate different features extant in IR spectra and discuss their influence on the phasor waveforms; similarly, we undertake IR image analysis in the transform space to understand spectral similarity and variance. We demonstrate the potential of phasor analysis for biomedical tissue imaging using a variety of samples, using fresh frozen surgical prostate resections and formalin-fixed paraffin-embedded breast cancer tissue microarray samples as model systems that span common histopathology practice. To demonstrate further generalizability of this approach, we apply the method to data from different experimental conditions─including standard (5.5 μm × 5.5 μm pixel size) and high-definition (1.1 μm × 1.1 μm pixel size) Fourier transform IR (FTIR) spectroscopic imaging using transmission and transflection modes. Quantitative segmentation results from our approach are compared to previous studies, showing good agreement and quick visualization. The presented method is rapid, easy to use, and highly capable of deciphering compositional differences, presenting a convenient tool for exploratory analysis of IR imaging data.