Kris Lami, Noriaki Ota, Shinsuke Yamaoka, Andrey Bychkov, Keitaro Matsumoto, Wataru Uegami, Jijgee Munkhdelger, Kurumi Seki, Odsuren Sukhbaatar, Richard Attanoos, Sabina Berezowska, Luka Brcic, Alberto Cavazza, John C English, Alexandre Todorovic Fabro, Kaori Ishida, Yukio Kashima, Yuka Kitamura, Brandon T Larsen, Alberto M Marchevsky, Takuro Miyazaki, Shimpei Morimoto, Mutsumi Ozasa, Anja C Roden, Frank Schneider, Maxwell L Smith, Kazuhiro Tabata, Angela M Takano, Tomonori Tanaka, Tomoshi Tsuchiya, Takeshi Nagayasu, Hidenori Sakanashi, Junya Fukuoka
The histopathologic distinction of lung adenocarcinoma (LADC) subtypes is subject to high interobserver variability, which can compromise the optimal assessment of patient prognosis. Therefore, this study developed convolutional neural networks capable of distinguishing LADC subtypes and predicting disease-specific survival, according to the recently established LADC tumor grades. Consensus LADC histopathologic images were obtained from 17 expert pulmonary pathologists and one pathologist in training. Two deep learning models (AI-1 and AI-2) were trained to predict eight different LADC classes...
August 5, 2023: American Journal of Pathology