Deep Learning Features Improve the Performance of a Radiomics Signature for Predicting KRAS Status in Patients with Colorectal Cancer.

Journal: Academic radiology
Published Date:

Abstract

RATIONALE AND OBJECTIVES: We assess the performance of a model combining a deep convolutional neural network and a hand-crafted radiomics signature for predicting KRAS status in patients with colorectal cancer (CRC).

Authors

  • Xiaomei Wu
  • YaJun Li
    Department of Electronics and Information Engineering, Shunde Polytechnic, Foshan 528300, China.
  • Xin Chen
    University of Nottingham, Nottingham, United Kingdom.
  • Yanqi Huang
    Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, 510080, China.
  • Lan He
    Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, Guangdong Province, China.
  • Ke Zhao
    Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
  • Xiaomei Huang
    Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, Guangdong Province, China; Southern Medical University, Guangzhou, Guangdong Province, PR China.
  • Wen Zhang
    Oil Crops Research Institute, Chinese Academy of Agricultural Sciences Wuhan 430062 China peiwuli@oilcrops.cn zhangqi521x@126.com +86-27-8681-2943 +86-27-8671-1839.
  • Yucun Huang
    Southern Medical University, Guangzhou, Guangdong Province, PR China.
  • Yexing Li
    Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, Guangdong Province, China; Shantou University, Shantou, Guangdong Province, PR China.
  • Mengyi Dong
    Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, Guangdong Province, China; Southern Medical University, Guangzhou, Guangdong Province, PR China.
  • Jia Huang
    Shanghai Lung Tumor Clinical Medical Center, Shanghai Chest Hospital, Shanghai Jiao Tong University (SJTU), Shanghai 200030, China.
  • Ting Xia
    School of Medicine, South China University of Technology, Guangzhou, Guangdong Province, China; Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, Guangdong Province, China.
  • Changhong Liang
    Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, 510080, China.
  • Zaiyi Liu
    Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.