Buckels Emma Jane, Ross Jacqueline Mary, Phua Hui Hui, Bloomfield Frank Harry, Jaquiery Anne Louise
Liggins Institute, University of Auckland, Auckland, New Zealand.
Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
MethodsX. 2022 Sep 13;9:101856. doi: 10.1016/j.mex.2022.101856. eCollection 2022.
Quantification of cell populations in tissue sections is frequently examined in studies of human disease. However, traditional manual imaging of sections stained with immunohistochemistry is laborious, time-consuming, and often assesses fields of view rather than the whole tissue section. The analysis is usually manual or utilises expensive proprietary image analysis platforms. Whole-slide imaging allows rapid automated visualisation of entire tissue sections. This approach increases the quantum of data generated per slide, decreases user time compared to manual microscopy, and reduces selection bias. However, such large data sets mean that manual image analysis is no longer practicable, requiring an automated process. In the case of diabetes, the contribution of various pancreatic endocrine cell populations is often investigated in preclinical and clinical samples. We developed a two-part method to measure pancreatic endocrine cell mass, firstly describing imaging using an automated slide-scanner, and secondly, the analysis of the resulting large image data sets using the open-source software, Fiji, which is freely available to all researchers and has cross-platform compatibility. This protocol is highly versatile and may be applied either in full or in part to analysis of IHC images created using other imaging platforms and/or the analysis of other tissues and cell markers.
在人类疾病研究中，经常会对组织切片中的细胞群体进行定量分析。然而，传统的免疫组织化学染色切片手动成像既费力又耗时，而且通常评估的是视野而非整个组织切片。分析通常是手动进行的，或者使用昂贵的专有图像分析平台。全玻片成像能够对整个组织切片进行快速自动可视化。这种方法增加了每张玻片产生的数据量，与手动显微镜相比减少了用户时间，并减少了选择偏差。然而，如此庞大的数据集意味着手动图像分析不再可行，需要自动化流程。在糖尿病研究中，常常会在临床前和临床样本中研究各种胰腺内分泌细胞群体的作用。我们开发了一种两部分的方法来测量胰腺内分泌细胞质量，首先描述使用自动玻片扫描仪进行成像，其次，使用开源软件Fiji对生成的大量图像数据集进行分析，所有研究人员都可以免费使用该软件，并且它具有跨平台兼容性。该方案具有高度的通用性，可全部或部分应用于使用其他成像平台创建的免疫组化图像分析和/或其他组织及细胞标志物的分析。
