MSIreg:用于质谱和 H&E 图像无监督核心配准的 R 软件包。

Sai Srikanth Lakkimsetty, Andreas Weber, Kylie A Bemis, Verena Stehl, Peter Bronsert, Melanie C Föll, Olga Vitek
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引用次数: 0

摘要

摘要:质谱图像(MS 图像)与苏木精和伊红(H&E)染色组织的显微镜图像的联合分析有助于病理学家确定组织形态结构的特征并进行诊断。遗憾的是,由于这些模式在长宽比、空间分辨率、每幅图像的通道数等方面存在很大差异,而且一幅图像相对于另一幅图像存在较大的整体或较小的局部弹性空间变形,因此影响了分析效果。因此,准确的图像核心注册是联合解读的关键前提。我们介绍了 MSIreg,这是一个用于 MSI 和 H&E 图像核心注册的开源 R 软件包。MSIreg 专为高维 MSI 实验而设计,其中每个空间位置都由数千个质量特征表示。与大多数现有的核心注册方法不同,MSIreg 实现了无地标工作流程和性能评估量化指标。我们在六个案例研究中评估了 MSIreg 的性能,包括具有较大变形的连续组织的核心注册,以及 29 个组织微阵列核心的同步核心注册:R软件包、安装说明以及描述方法和案例研究的完全可重现的小故事可在GPL-3.0许可下开源,网址为:https://github.com/sslakkimsetty/msireg/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MSIreg: an R package for unsupervised coregistration of mass spectrometry and H&E images.

Summary: Joint analysis of mass spectrometry images (MS images) and microscopy images of hematoxylin and eosin (H&E) stained tissues assists pathologists in characterizing the morphological structure of the tissues, and in performing diagnosis. Unfortunately, the analysis is undermined by substantial differences between these modalities in terms of aspect ratios, spatial resolution, number of channels in each image, as well as by large global or small local elastic spatial deformations of one image with respect to the other. Therefore, accurate coregistration of the images is a critical pre-requisite for their joint interpretation. We introduce MSIreg, an open-source R package for coregistration of MSI and H&E images. MSIreg is designed for high-dimensional MSI experiments where each spatial location is represented by thousands of mass features. Unlike most existing coregistration methods, MSIreg implements a landmark free workflow, and quantitative metrics for performance evaluation. We evaluate the performance of MSIreg on six case studies, including coregistration of contiguous tissues with large deformations, as well as simultaneous coregistration of 29 tissue microarray cores.

Availability and implementation: The R package, installation instructions, and fully reproducible vignettes describing methods and Case Studies are available open-source under the GPL-3.0 license at https://github.com/sslakkimsetty/msireg/.

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