3.8 Proceedings Paper

MICROSATELLITE INSTABILITY PREDICTION OF UTERINE CORPUS ENDOMETRIAL CARCINOMA BASED ON H&E HISTOLOGY WHOLE-SLIDE IMAGING

Publisher

IEEE
DOI: 10.1109/isbi45749.2020.9098647

Keywords

Microsatellite instability; histopathology; deep residual learning

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Microsatellite instability is an important clinical marker for various types of cancers and is related to patients' prognosis and response to immunotherapy. Currently, identifying microsatellite status relies on genetic tests, which are not widely accessible for every patient. We propose a novel pipeline to predict MSI directly from histology slides which represent the gold standard for cancer diagnosis and are ubiquitously available for cancer patients. Our method outperformed existing method on the uterine corpus endometrial carcinoma cohort in The Cancer Genome Atlas (AUC 0.73 vs. 0.56).

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