Spatial Pathomics Toolkit for Quantitative Analysis of Podocyte Nuclei with Histology and Spatial Transcriptomics Data in Renal Pathology.

Jiayuan Chen, Yu Wang, Ruining Deng, Quan Liu, Can Cui, Tianyuan Yao, Yilin Liu, Jianyong Zhong, Agnes B Fogo, Haichun Yang, Shilin Zhao, Yuankai Huo
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Abstract

Podocytes, specialized epithelial cells that envelop the glomerular capillaries, play a pivotal role in maintaining renal health. The current description and quantification of features on pathology slides are limited, prompting the need for innovative solutions to comprehensively assess diverse phenotypic attributes within Whole Slide Images (WSIs). In particular, understanding the morphological characteristics of podocytes, terminally differentiated glomerular epithelial cells, is crucial for studying glomerular injury. This paper introduces the Spatial Pathomics Toolkit (SPT) and applies it to podocyte pathomics. The SPT consists of three main components: (1) instance object segmentation, enabling precise identification of podocyte nuclei; (2) pathomics feature generation, extracting a comprehensive array of quantitative features from the identified nuclei; and (3) robust statistical analyses, facilitating a comprehensive exploration of spatial relationships between morphological and spatial transcriptomics features. The SPT successfully extracted and analyzed morphological and textural features from podocyte nuclei, revealing a multitude of podocyte morphomic features through statistical analysis. Additionally, we demonstrated the SPT's ability to unravel spatial information inherent to podocyte distribution, shedding light on spatial patterns associated with glomerular injury. By disseminating the SPT, our goal is to provide the research community with a powerful and user-friendly resource that advances cellular spatial pathomics in renal pathology. The toolkit's implementation and its complete source code are made openly accessible at the GitHub repository: https://github.com/hrlblab/spatial_pathomics.

空间病理学工具包,定量分析足细胞核与组织学和空间转录组学数据在肾脏病理。
足细胞是包裹肾小球毛细血管的特化上皮细胞,在维持肾脏健康中起关键作用。目前病理切片特征的描述和量化是有限的,这促使需要创新的解决方案来全面评估全切片图像(wsi)中的不同表型属性。特别是,了解足细胞(终末分化的肾小球上皮细胞)的形态学特征,对研究肾小球损伤至关重要。本文介绍了空间病理工具箱(SPT),并将其应用于足细胞病理。SPT主要由三个部分组成:(1)实例对象分割,实现足细胞核的精确识别;(2)病理特征生成,从已识别的细胞核中提取全面的定量特征;(3)稳健的统计分析,有助于全面探索形态和空间转录组学特征之间的空间关系。SPT成功地提取并分析了足细胞细胞核的形态和纹理特征,通过统计分析揭示了大量足细胞形态特征。此外,我们证明了SPT能够揭示足细胞分布固有的空间信息,揭示与肾小球损伤相关的空间模式。通过传播SPT,我们的目标是为研究界提供一个强大且用户友好的资源,以推进肾脏病理中的细胞空间病理学。该工具包的实现及其完整的源代码可以在GitHub存储库中公开访问:https://github.com/hrlblab/spatial_pathomics。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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