LMSST-GCN: Longitudinal MRI sub-structural texture guided graph convolution network for improved progression prediction of knee osteoarthritis.

Journal: Computer methods and programs in biomedicine
Published Date: Jan 13, 2025

Abstract

BACKGROUND AND OBJECTIVES: Accurate prediction of progression in knee osteoarthritis (KOA) is significant for early personalized intervention. Previous methods commonly focused on quantifying features from a specific sub-structure imaged at baseline and resulted in limited performance. We proposed a longitudinal MRI sub-structural texture-guided graph convolution network (LMSST-GCN) for improved KOA progression prediction.

Authors

  • Wenbing Lv
    Department of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
  • Junyi Peng
    School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.
  • Jiaping Hu
    Department of Medical Imaging, The Third Affiliated Hospital of Southern Medical University (Academy of Orthopedics· Guangdong Province), Guangzhou, China.
  • Yijun Lu
    School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Road, Guangzhou 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, 1023 Shatai Road, Guangzhou 510515, China.
  • Zidong Zhou
    School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.
  • Hui Xu
    No 202 Hospital of People's Liberation Army, Liaoning 110003, China.
  • Kongzai Xing
    Precision Radiotherapy Center, Foshan Fosun Changcheng Hospital, Foshan 528031, China.
  • Xiaodong Zhang
    The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Lijun Lu
    School of Biomedical Engineering, Southern Medical University, Guangzhou, China.

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