Liver imaging features by convolutional neural network to predict the metachronous liver metastasis in stage I-III colorectal cancer patients based on preoperative abdominal CT scan.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Introducing deep learning approach to medical images has rendered a large amount of un-decoded information into usage in clinical research. But mostly, it has been focusing on the performance of the prediction modeling for disease-related entity, but not on the clinical implication of the feature itself. Here we analyzed liver imaging features of abdominal CT images collected from 2019 patients with stage I - III colorectal cancer (CRC) using convolutional neural network (CNN) to elucidate its clinical implication in oncological perspectives.

Authors

  • Sangwoo Lee
    Samsung Electronics, Suwon, South Korea.
  • Eun Kyung Choe
    Department of Surgery, Seoul National University Hospital Healthcare System Gangnam Center, 39FL Gangnam Finance Center 152, Teheran-ro, Gangnam-gu, Seoul, 135-984, South Korea. snuhcr@naver.com.
  • So Yeon Kim
  • Hua Sun Kim
    Department of Radiology, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, South Korea.
  • Kyu Joo Park
    Department of Surgery, Seoul National University College of Medicine, Seoul, 03080, South Korea.
  • Dokyoon Kim
    Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania, Philadelphia, USA.