2022
DOI: 10.3390/biomedicines10123133
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Pixel-Level Clustering of Hematoxylin–Eosin-Stained Sections of Mouse and Human Biliary Tract Cancer

Abstract: We previously established mouse models of biliary tract cancer (BTC) based on the injection of cells with biliary epithelial stem cell properties derived from KRAS(G12V)-expressing organoids into syngeneic mice. The resulting mouse tumors appeared to recapitulate the pathological features of human BTC. Here we analyzed images of hematoxylin and eosin (H&E) staining for both the mouse tumor tissue and human cholangiocarcinoma tissue by pixel-level clustering with machine learning. A pixel-clustering model t… Show more

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Cited by 3 publications
(1 citation statement)
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“…The resulting mouse tumors appeared to recapitulate the pathological features of human cholangiocarcinoma [58]. Machine learning analysis of H&E-stained images of tumor tissue revealed similarities between the mouse tumors and human cholangiocarcinoma [59]. In the biliary tract cancer models, CD4 + T cells, CD8 + T cells, F4/80 + macrophages, and CD31 + endothelial cells were detected mostly in desmoplastic areas of tumor tissue where cancer cells were surrounded by stromal cells and the ECM [58].…”
Section: Animal Modelsmentioning
confidence: 89%
“…The resulting mouse tumors appeared to recapitulate the pathological features of human cholangiocarcinoma [58]. Machine learning analysis of H&E-stained images of tumor tissue revealed similarities between the mouse tumors and human cholangiocarcinoma [59]. In the biliary tract cancer models, CD4 + T cells, CD8 + T cells, F4/80 + macrophages, and CD31 + endothelial cells were detected mostly in desmoplastic areas of tumor tissue where cancer cells were surrounded by stromal cells and the ECM [58].…”
Section: Animal Modelsmentioning
confidence: 89%