An Open‐Source Workflow for Semi‐Automated Spatial Profiling of Multiplex Immunofluorescent Images

计算机科学 多路复用 工作流程 空间分析 仿形(计算机编程) 聚类分析 数据挖掘 软件 分割 人工智能 图像分割 图像处理 管道(软件) 模式识别(心理学) 图像分辨率 计算生物学 协议(科学) 计算机视觉 脚本语言 像素 可扩展性 生物信息学 可视化 自动化
作者
Alisha R. Dabb,Cynthia A. Morgan,Sophia Noble,Alfonso Schmidt
出处
期刊:Current protocols [Wiley]
卷期号:6 (3): e70331-e70331
标识
DOI:10.1002/cpz1.70331
摘要

Multiplex immunofluorescence microscopy facilitates the quantification and spatial analysis of cellular features within tissue sections, allowing greater understanding of disease progression or the effects of drug treatment or other exposures on cellular organization and tissue structure. Recent advances in image analysis and computational methods such as machine-learning-based cell segmentation and automated cell phenotyping have enhanced the depth of information gained from these historically qualitative images. However, many spatial analysis pipelines are technically challenging or require proprietary software or hardware, limiting accessibility and reproducibility. The free and open-source software QuPath provides a novel resource for quantifying and spatially profiling multiplex images. Here, we describe a detailed primary protocol for the semi-automated spatial analysis of 2D multiplex immunofluorescent images using QuPath, which uses object and pixel classification, cell distance, and cluster measurements for spatial profiling of tissue samples. This pipeline also includes the use of training images and basic scripting for batch processing to ensure that analysis is objective and standardized within and between projects. We also provide an alternate protocol that details a pipeline modification for whole-section images, and an extended protocol that describes the use of a free, browser-based tool to complete unsupervised, rapid processing and consolidation of the spatial data provided by QuPath, with automated reporting of cell spatial plots, cell-to-object measurements, and cell clustering data. These protocols provide an accessible, standardized, and scalable method for the spatial analysis of multiplex immunofluorescence microscopy images, facilitating reproducible quantification of cellular organization and tissue structure and thereby strengthening the integration of spatial data into translational research, biomarker discovery, and mechanistic studies. © 2026 Wiley Periodicals LLC. Basic Protocol 1: QuPath image processing Alternate Protocol: Whole-section image processing Basic Protocol 2: Use of the QuPath Spatial Analysis and Visualisation Tool.
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