Highly Adaptable Analysis Tools for Mapping Spatial Features of Cellular Aggregates in Tissues

Andrew Sawyer, Nick Weingaertner, Ellis Patrick, Carl G. Feng
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Abstract

Multiplex imaging technologies have developed rapidly over the past decades. The advancement of multiplex imaging has been driven in part by the recognition that the spatial organization of cells can represent important prognostic biomarkers and that simply studying the composition of cells in diseased tissue is often insufficient. There remains a lack of tools that can perform spatial analysis at the level of cellular aggregates (a common histopathological presentation) such as tumors and granulomas, with most analysis packages focusing on smaller regions of interest and potentially missing patterns in the overall lesion structure and cellular distribution. Here, we present protocols to quantitatively describe the cellular structure of entire tissue lesions, built around two novel metrics. The Total Cell Preference Index reports whether a lesion tends to change in density in its central versus peripheral areas and can indicate the extent of necrosis across the entire lesion. The Immune Cell Preference Index then reports whether each immune cell type is located more centrally or peripherally across the entire lesion. The output of both indexes is a single number readout for simple interpretation and visualization, and these indexes can be applied to lesions of any size or shape. This simplifies cross-lesion comparison compared to traditional Euclidian distance–based analysis, which outputs multiple values for each lesion (one for output for each band used in the infiltration analysis). Additionally, this approach can be applied to any slide-scanning multiplexed imaging system, based on either protein or nucleic acid staining. Finally, the approach uses the open-source software QuPath and can be utilized by researchers with a basic understanding of QuPath, with the full analysis able to be applied to pre-generated images within 1 hr. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC.

Basic Protocol 1: Image preparation and lesion selection

Basic Protocol 2: Total Cell Preference Index and Immune Cell Preference Index

Abstract Image

组织中细胞聚集体空间特征映射的高适应性分析工具
在过去的几十年里,多路成像技术发展迅速。多重成像技术的进步部分是由于人们认识到细胞的空间组织可以代表重要的预后生物标志物,而仅仅研究病变组织中细胞的组成往往是不够的。目前仍然缺乏能够在细胞聚集(一种常见的组织病理学表现)水平上进行空间分析的工具,例如肿瘤和肉芽肿,大多数分析包都集中在较小的感兴趣区域,并且可能在整体病变结构和细胞分布中缺失模式。在这里,我们提出了定量描述整个组织病变的细胞结构的方案,建立在两个新的指标。总细胞偏好指数报告病变是否倾向于在其中心区域和周围区域密度变化,并可以指示整个病变的坏死程度。免疫细胞偏好指数报告了每一种免疫细胞类型是位于整个病变的中心还是外围。这两个指标的输出都是一个数字读数,便于解释和可视化,这些指标可以应用于任何大小或形状的病变。与传统的基于欧几里得距离的分析相比,这简化了跨病变比较,传统的欧几里得距离分析为每个病变输出多个值(浸润分析中使用的每个波段输出一个值)。此外,这种方法可以应用于任何基于蛋白质或核酸染色的滑动扫描多路成像系统。最后,该方法使用开源软件QuPath,对QuPath有基本了解的研究人员可以使用该软件,并在1小时内将完整分析应用于预生成的图像。©2025作者。由Wiley期刊有限责任公司发表的当前方案。基本方案1:图像准备和病变选择基本方案2:总细胞偏好指数和免疫细胞偏好指数
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