Ensemble learning-based radiomics model for discriminating brain metastasis from glioblastoma.

Journal: European journal of radiology
PMID:

Abstract

OBJECTIVE: Differentiating between brain metastasis (BM) and glioblastoma (GBM) preoperatively is challenging due to their similar imaging features on conventional brain MRI. This study aimed to enhance diagnostic accuracy through a machine learning model based on MRI radiomics data.

Authors

  • Qi Zeng
    Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada.
  • Fangxu Jia
    Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.
  • Shengming Tang
    Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.
  • Haoling He
    Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Yan Fu
    School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300350, PR China. Electronic address: fuyan@tju.edu.cn.
  • Xueying Wang
    Institute of Intelligent System and Bioinformatics, College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Jinfan Zhang
    Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.
  • Zeming Tan
    Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
  • Haiyun Tang
    Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China. Electronic address: 405016@csu.edu.cn.
  • Jing Wang
    Endoscopy Center, Peking University Cancer Hospital and Institute, Beijing, China.
  • Xiaoping Yi
    Department of Radiology, Xiangya Hospital, Central South University, Changsha, China.
  • Bihong T Chen
    Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, United States. Electronic address: Bechen@coh.org.