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基于彩色空间光干涉显微镜(cSLIM)的染色组织定量组织学分析。

Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM).

机构信息

Quantitative Light Imaging (QLI) Lab, Department of Bioengineering, Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana Champaign, 405 N. Matthews, Urbana, IL, 61801, USA.

Laboratory for Optical and Computational Instrumentation (LOCI), Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, 53706, USA.

出版信息

Sci Rep. 2019 Oct 11;9(1):14679. doi: 10.1038/s41598-019-50143-x.

Abstract

Tissue biopsy evaluation in the clinic is in need of quantitative disease markers for diagnosis and, most importantly, prognosis. Among the new technologies, quantitative phase imaging (QPI) has demonstrated promise for histopathology because it reveals intrinsic tissue nanoarchitecture through the refractive index. However, a vast majority of past QPI investigations have relied on imaging unstained tissues, which disrupts the established specimen processing. Here we present color spatial light interference microscopy (cSLIM) as a new whole-slide imaging modality that performs interferometric imaging on stained tissue, with a color detector array. As a result, cSLIM yields in a single scan both the intrinsic tissue phase map and the standard color bright-field image, familiar to the pathologist. Our results on 196 breast cancer patients indicate that cSLIM can provide stain-independent prognostic information from the alignment of collagen fibers in the tumor microenvironment. The effects of staining on the tissue phase maps were corrected by a mathematical normalization. These characteristics are likely to reduce barriers to clinical translation for the new cSLIM technology.

摘要

临床中的组织活检评估需要用于诊断的定量疾病标志物,最重要的是,需要用于预后的定量疾病标志物。在新技术中,定量相位成像(QPI)已经在组织病理学中显示出了前景,因为它通过折射率揭示了组织的固有纳米结构。然而,过去绝大多数的 QPI 研究都依赖于对未染色组织进行成像,这会破坏既定的样本处理过程。在这里,我们提出了彩色空间光干涉显微镜(cSLIM)作为一种新的全切片成像方式,它可以在染色组织上进行干涉成像,并使用彩色探测器阵列。结果,cSLIM 在单次扫描中即可获得组织的固有相位图和标准的彩色明场图像,这对病理学家来说是熟悉的。我们对 196 名乳腺癌患者的研究结果表明,cSLIM 可以通过肿瘤微环境中胶原纤维的排列提供不依赖于染色的预后信息。通过数学归一化来校正染色对组织相位图的影响。这些特性可能会降低新技术 cSLIM 向临床转化的障碍。

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