Prediction of 1p/19q state in glioma by integrated deep learning method based on MRI radiomics.

Journal: BMC cancer
Published Date: Jul 28, 2025

Abstract

PURPOSE: To predict the 1p/19q molecular status of Lower-grade glioma (LGG) patients nondestructively, this study developed a deep learning (DL) approach using radiomic to provide a potential decision aid for clinical determination of molecular stratification of LGG.

Authors

  • Fengda Li
    Department of Neurosurgery, Changshu Hospital Affiliated to Soochow University, Changshu, China.
  • Zeyi Li
    School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China.
  • Hong Xu
    Department of Neurosurgery, Changshu Hospital Affiliated to Soochow University, Changshu, China.
  • Gang Kong
    Department of Neurosurgery, Changshu Hospital Affiliated to Soochow University, Changshu, China.
  • Ze Zhang
    Department of Stomatology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, 528308, China.
  • Kaiyuan Cheng
    Department of Neurosurgery, Changshu Hospital Affiliated to Soochow University, Changshu, China.
  • Longyuan Gu
    Department of Neurosurgery, Ji'an Central People's Hospital, Ji'an, China.
  • Lei Hua
    Department of Computer and Information Science, Hefei University of Technology, Hefei, China.

Keywords

External Resources

Popular Topics
Recent Journals