不同突变型星形细胞瘤细胞特征差异的数字化组织学图像分析
Analysis of Cellular Feature Differences of Astrocytomas with Distinct Mutational Profiles Using Digitized Histopathology Images
摘要：
从组织病理学图像中获得的细胞表型特征是病理诊断的基础，并且被认为与潜在的分子特征相关。由于压倒性的细胞数量和群体异质性，定量计算和比较具有不同分子特征的细胞的特征仍然具有挑战性。在这项研究中，我们提出了一个独立的和有效的分析框架，支持不同分子组的细胞表型差异的定量分析。为了证明有效性，我们使用来自癌症基因组图谱数据库的成像数据定量分析了分子特征为异柠檬酸脱氢酶（IDH）突变体（MUT）或野生型（WT）的星形细胞瘤。在分割、特征计算、数据修剪、降维和无监督聚类之后，检索这两组之间表型不同的代表性细胞实例。我们的分析是通用的，可以应用于广泛的基于细胞的生物医学研究。
英文摘要：
Cellular phenotypic features derived from histopathology images are the basis of pathologic diagnosis and are thought to be related to underlying molecular profiles. Due to overwhelming cell numbers and population heterogeneity, it remains challenging to quantitatively compute and compare features of cells with distinct molecular signatures. In this study, we propose a self-reliant and efficient analysis framework that supports quantitative analysis of cellular phenotypic difference across distinct molecular groups. To demonstrate efficacy, we quantitatively analyze astrocytomas that are molecularly characterized as either Isocitrate Dehydrogenase (IDH) mutant (MUT) or wildtype (WT) using imaging data from The Cancer Genome Atlas database. Representative cell instances that are phenotypically different between these two groups are retrieved after segmentation, feature computation, data pruning, dimensionality reduction, and unsupervised clustering. Our analysis is generic and can be applied to a wide set of cell-based biomedical research.
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