Institute for Pathology, Hannover Medical School, Hannover, Germany.
Definiens AG, Munich, Germany.
PLoS Comput Biol. 2020 Feb 21;16(2):e1007385. doi: 10.1371/journal.pcbi.1007385. eCollection 2020 Feb.
Our aim is to complement observer-dependent approaches of immune cell evaluation in microscopy images with reproducible measures for spatial composition of lymphocytic infiltrates. Analyzing such patterns of inflammation is becoming increasingly important for therapeutic decisions, for example in transplantation medicine or cancer immunology. We developed a graph-based assessment of lymphocyte clustering in full whole slide images. Based on cell coordinates detected in the full image, a Delaunay triangulation and distance criteria are used to build neighborhood graphs. The composition of nodes and edges are used for classification, e.g. using a support vector machine. We describe the variability of these infiltrates on CD3/CD20 duplex staining in renal biopsies of long-term functioning allografts, in breast cancer cases, and in lung tissue of cystic fibrosis patients. The assessment includes automated cell detection, identification of regions of interest, and classification of lymphocytic clusters according to their degree of organization. We propose a neighborhood feature which considers the occurrence of edges with a certain type in the graph to distinguish between phenotypically different immune infiltrates. Our work addresses a medical need and provides a scalable framework that can be easily adjusted to the requirements of different research questions.
我们的目的是用可重复的方法来补充显微镜图像中免疫细胞评估的观察者依赖方法，以评估淋巴细胞浸润的空间组成。分析这种炎症模式对于治疗决策变得越来越重要，例如在移植医学或癌症免疫学中。我们开发了一种基于图的方法来评估全幻灯片图像中的淋巴细胞聚类。基于在全图像中检测到的细胞坐标，使用 Delaunay 三角剖分和距离标准来构建邻接图。节点和边的组成用于分类，例如使用支持向量机。我们描述了在长期功能同种异体移植肾活检、乳腺癌病例和囊性纤维化患者肺组织中 CD3/CD20 双染的这些浸润的可变性。评估包括自动细胞检测、感兴趣区域的识别以及根据淋巴细胞簇的组织程度进行分类。我们提出了一种邻域特征，该特征考虑了图中具有特定类型的边的出现，以区分表型不同的免疫浸润。我们的工作满足了医疗需求，并提供了一个可扩展的框架，可以轻松地适应不同研究问题的要求。
