Shunxing Bao, Sichen Zhu, Vasantha L Kolachala, Lucas W Remedios, Yeonjoo Hwang, Yutong Sun, Ruining Deng, Can Cui, Rendong Zhang, Yike Li, Jia Li, Joseph T Roland, Qi Liu, Ken S Lau, Subra Kugathasan, Peng Qiu, Keith T Wilson, Lori A Coburn, Bennett A Landman, Yuankai Huo
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引用次数: 0
摘要
克罗恩病(Crohn's disease,CD)是一种影响部分胃肠道的慢性复发性炎症。克罗恩病的活动性是由组织学结果决定的,特别是在苏木精和伊红染色(H&E)成像中观察到的中性粒细胞的密度。然而,除了细胞计数和组织形态之外,了解更广泛的形态学和局部细胞排列仍然具有挑战性。为了解决这个问题,我们从 H&E 图像中描述了六种不同的细胞类型,并开发了一种新方法来确定每个细胞的局部空间特征。具体来说,我们创建了一个 10 个细胞的邻近矩阵,代表每个单个细胞的邻近细胞排列。利用 t-SNE 在散点图和核密度估计等高线图格式中进行非线性空间投影,我们的研究考察了与活动 CD 组和对照组空间模式几率比相关的细胞环境差异模式。该分析基于两个研究所收集的数据。研究结果揭示了不同的近邻模式,表明了细胞集群的不同趋势,特别是在直肠区域。这些差异凸显了数据异质性对 CD 患者细胞空间排列的影响。此外,两个研究基地之间的空间分布差异也凸显了医疗机构之间合作的重要性。所有研究分析管道工具均可在 https://github.com/MASILab/cellNN 上获取。
Cell Spatial Analysis in Crohn's Disease: Unveiling Local Cell Arrangement Pattern with Graph-based Signatures.
Crohn's disease (CD) is a chronic and relapsing inflammatory condition that affects segments of the gastrointestinal tract. CD activity is determined by histological findings, particularly the density of neutrophils observed on Hematoxylin and Eosin stains (H&E) imaging. However, understanding the broader morphometry and local cell arrangement beyond cell counting and tissue morphology remains challenging. To address this, we characterize six distinct cell types from H&E images and develop a novel approach for the local spatial signature of each cell. Specifically, we create a 10-cell neighborhood matrix, representing neighboring cell arrangements for each individual cell. Utilizing t-SNE for non-linear spatial projection in scatter-plot and Kernel Density Estimation contour-plot formats, our study examines patterns of differences in the cellular environment associated with the odds ratio of spatial patterns between active CD and control groups. This analysis is based on data collected at the two research institutes. The findings reveal heterogeneous nearest-neighbor patterns, signifying distinct tendencies of cell clustering, with a particular focus on the rectum region. These variations underscore the impact of data heterogeneity on cell spatial arrangements in CD patients. Moreover, the spatial distribution disparities between the two research sites highlight the significance of collaborative efforts among healthcare organizations. All research analysis pipeline tools are available at https://github.com/MASILab/cellNN.