Deep Learning Radiomics for the Assessment of Telomerase Reverse Transcriptase Promoter Mutation Status in Patients With Glioblastoma Using Multiparametric MRI.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date: Mar 10, 2023

Abstract

BACKGROUND: Studies have shown that magnetic resonance imaging (MRI)-based deep learning radiomics (DLR) has the potential to assess glioma grade; however, its role in predicting telomerase reverse transcriptase (TERT) promoter mutation status in patients with glioblastoma (GBM) remains unclear.

Authors

  • Hongbo Zhang
    Department of Computer Science and Engineering, Huaqiao University, Xiamen, China.
  • Hanwen Zhang
    Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China.
  • Yuze Zhang
    ModiFace - A L'Oréal Group Company, Toronto, ON, Canada.
  • Beibei Zhou
    EMAI LLC, Laurel, MD 20723, USA.
  • Lei Wu
    Advanced Photonics Center, Southeast University, Nanjing, 210096, China.
  • Yi Lei
    Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, 518035, China.
  • Biao Huang
    Institute of Quality Standards & Testing Technology for Agro-products, Fujian Academy of Agricultural Sciences/ Fujian Key Laboratory of Agro-products Quality and Safety, Fuzhou, 350003, China.

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