作者
Amelie Echle, Heike Irmgard Grabsch, Philip Quirke, Piet A van den Brandt, Nicholas P West, Gordon GA Hutchins, Lara R Heij, Xiuxiang Tan, Susan D Richman, Jeremias Krause, Elizabeth Alwers, Josien Jenniskens, Kelly Offermans, Richard Gray, Hermann Brenner, Jenny Chang-Claude, Christian Trautwein, Alexander T Pearson, Peter Boor, Tom Luedde, Nadine Therese Gaisa, Michael Hoffmeister, Jakob Nikolas Kather
发表日期
2020/10/1
期刊
Gastroenterology
卷号
159
期号
4
页码范围
1406-1416. e11
出版商
WB Saunders
简介
Background & Aims
Microsatellite instability (MSI) and mismatch-repair deficiency (dMMR) in colorectal tumors are used to select treatment for patients. Deep learning can detect MSI and dMMR in tumor samples on routine histology slides faster and less expensively than molecular assays. However, clinical application of this technology requires high performance and multisite validation, which have not yet been performed.
Methods
We collected H&E-stained slides and findings from molecular analyses for MSI and dMMR from 8836 colorectal tumors (of all stages) included in the MSIDETECT consortium study, from Germany, the Netherlands, the United Kingdom, and the United States. Specimens with dMMR were identified by immunohistochemistry analyses of tissue microarrays for loss of MLH1, MSH2, MSH6, and/or PMS2. Specimens with MSI were identified by genetic analyses. We trained a deep-learning …
学术搜索中的文章
A Echle, HI Grabsch, P Quirke, PA van den Brandt… - Gastroenterology, 2020