Multiscale image analysis reveals structural heterogeneity of the cell microenvironment in homotypic spheroids.
Multiscale image analysis reveals structural heterogeneity of the cell microenvironment in homotypic spheroids.
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DOI：
10.1038/srep43693
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发表时间：
2017-03-03
影响因子：
4.6
通讯作者：
Stelzer EH
中科院分区：
文献类型：
--
作者：
Schmitz A;Fischer SC;Mattheyer C;Pampaloni F;Stelzer EH
三维多细胞聚集体，如球体，在体外为组织提供了可靠的替代品。球体在细胞水平上的定量表征是基本的。我们介绍了第一条以细胞分辨率提供完整球体的三维、高质量图像的流水线，以及一个全面的图像分析，它完成了由其他领域的算法完成的传统图像分割。该管道结合了光学透明球体的基于光片的荧光显微镜与自动核分割(F分数：0.88)以及来自图形分析和计算拓扑的概念。结合细胞图形和阿尔法形状，提供了单个核、细胞邻域和椭圆形的30多个特征。我们的管道应用于一组乳腺癌球体，显示了超过30,000个细胞的两个不同细胞密度的同心层。外层细胞的厚度取决于椭球体的大小，在半径的50%到75%之间变化。在不同大小的球体中，我们检测到不同细胞密度的斑块，从5 × 10 5到1 × 10 6 细胞/mm~3不等。由于细胞密度影响组织中的细胞行为，结构异质性需要纳入现有模型。我们的图像分析流水线提供了一种多尺度的方法来获取相关数据，以便在系统级别上了解组织结构。
Three-dimensional multicellular aggregates such as spheroids provide reliable in vitro substitutes for tissues. Quantitative characterization of spheroids at the cellular level is fundamental. We present the first pipeline that provides three-dimensional, high-quality images of intact spheroids at cellular resolution and a comprehensive image analysis that completes traditional image segmentation by algorithms from other fields. The pipeline combines light sheet-based fluorescence microscopy of optically cleared spheroids with automated nuclei segmentation (F score: 0.88) and concepts from graph analysis and computational topology. Incorporating cell graphs and alpha shapes provided more than 30 features of individual nuclei, the cellular neighborhood and the spheroid morphology. The application of our pipeline to a set of breast carcinoma spheroids revealed two concentric layers of different cell density for more than 30,000 cells. The thickness of the outer cell layer depends on a spheroid’s size and varies between 50% and 75% of its radius. In differently-sized spheroids, we detected patches of different cell densities ranging from 5 × 105 to 1 × 106 cells/mm3. Since cell density affects cell behavior in tissues, structural heterogeneities need to be incorporated into existing models. Our image analysis pipeline provides a multiscale approach to obtain the relevant data for a system-level understanding of tissue architecture.