Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
PMID: 39716317

Abstract

OBJECTIVE: This study aims to evaluate the effectiveness of deep learning features derived from multi-sequence magnetic resonance imaging (MRI) in determining the O-methylguanine-DNA methyltransferase (MGMT) promoter methylation status among glioblastoma patients.

Authors

  • Xuan Yu
    School of Computer Engineering and Science, Shanghai University, Shanghai, China.
  • Jing Zhou
  • Yaping Wu
    Department of Imaging, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Yan Bai
    Department of Radiology, Henan Provincial People's Hospital, China.
  • Nan Meng
  • Qingxia Wu
    College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, Liaoning, China.
  • Shuting Jin
    Department of Computer Science, School of Information Science and Technology, Xiamen University, Xiamen 361005, China. stjin.xmu@gmail.com.
  • Huanhuan Liu
    Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, No. 1665 Kongjiang Road, Shanghai, 200092, China.
  • Panlong Li
    The School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, 450001, China.
  • Meiyun Wang

Keywords

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