Imaging mass cytometry (IMC) allows the detection of multiple antigens (approximately 40 markers) combined with spatial information, making it a unique tool for the evaluation of complex biological systems. Due to its widespread availability and retained tissue morphology, formalin-fixed, paraffin-embedded (FFPE) tissues are often a material of choice for IMC studies. However, antibody performance and signal to noise ratios can differ considerably between FFPE tissues as a consequence of variations in tissue processing, including fixation. In contrast to batch effects caused by differences in the immunodetection procedure, variations in tissue processing are difficult to control. We investigated the effect of immunodetection-related signal intensity fluctuations on IMC analysis and phenotype identification, in a cohort of 12 colorectal cancer tissues. Furthermore, we explored different normalization strategies and propose a workflow to normalize IMC data by semi-automated background removal, using publicly available tools. This workflow can be directly applied to previously acquired datasets and considerably improves the quality of IMC data, thereby supporting the analysis and comparison of multiple samples.

中文翻译：

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半自动背景去除限制了数据丢失并使成像质量流式细胞仪数据标准化

成像质谱流式 (IMC) 允许结合空间信息检测多种抗原（约 40 个标记），使其成为评估复杂生物系统的独特工具。由于其广泛的可用性和保留的组织形态，福尔马林固定、石蜡包埋 (FFPE) 组织通常是 IMC 研究的首选材料。然而，由于组织处理（包括固定）的变化，FFPE 组织之间的抗体性能和信噪比可能存在很大差异。与免疫检测程序差异引起的批次效应相反，组织处理的变化难以控制。我们研究了免疫检测相关信号强度波动对 IMC 分析和表型鉴定的影响，在一组 12 个结直肠癌组织中。此外，我们探索了不同的归一化策略，并提出了一种工作流程，使用公开可用的工具通过半自动背景去除来归一化 IMC 数据。该工作流程可以直接应用于之前采集的数据集，大大提高了 IMC 数据的质量，从而支持多个样本的分析和比较。