The application value of support vector machine model based on multimodal MRI in predicting IDH-1mutation and Ki-67 expression in glioma.

Journal: BMC medical imaging
PMID: 39285364

Abstract

PURPOSE: To investigate the application value of support vector machine (SVM) model based on diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) and amide proton transfer- weighted (APTW) imaging in predicting isocitrate dehydrogenase 1(IDH-1) mutation and Ki-67 expression in glioma.

Authors

  • He-Xin Liang
    Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
  • Zong-Ying Wang
    Department of Radiology, Weifang People's Hospital, Weifang, China.
  • Yao Li
    Center of Robotics and Intelligent Machine, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Science, No. 266 Fangzhen Road, Beibei District, Chongqing, 400714, China.
  • An-Ning Ren
    Medical Imaging Center of the Affiliated Hospital of Weifang Medical University, Weifang, China.
  • Zhi-Feng Chen
    Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia.
  • Xi-Zhen Wang
    Medical Imaging Center of the Affiliated Hospital of Weifang Medical University, Weifang, China.
  • Xi-Ming Wang
    Department of Radiology, The First Affiliated Hospital of Soochow University, 188N, Shizi Road, 215006, Suzhou, Jiangsu, China.
  • Zhen-Guo Yuan
    Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China. yuanzg88@126.com.

Keywords

External Resources

Popular Topics
Recent Journals