Use of MRI-based deep learning radiomics to diagnose sacroiliitis related to axial spondyloarthritis.

Journal: European journal of radiology
Published Date:

Abstract

OBJECTIVES: This study aimed to evaluate the performance of a deep learning radiomics (DLR) model, which integrates multimodal MRI features and clinical information, in diagnosing sacroiliitis related to axial spondyloarthritis (axSpA).

Authors

  • Ke Zhang
    Center for Radiation Oncology, Affiliated Hangzhou Cancer Hospital, Zhejiang University School of Medicine, Hangzhou 310001, China.
  • Chaoran Liu
    School of Reliability and Systems Engineering, Beihang University, Beijing, China; Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing, China.
  • Jielin Pan
    Department of Radiology, Zhuhai People's Hospital, Zhuhai Hospital affiliated with Jinan University, Zhuhai, 519000, China.
  • Yunfei Zhu
    Department of Radiology, the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai 519000, China.
  • Ximeng Li
    Department of Radiology, the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai 519000, China.
  • Jing Zheng
    Shandong Institute for Food and Drug Control, Jinan 250101, China.
  • Yingying Zhan
    Department of Radiology, the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai 519000, China.
  • Wenjuan Li
    Faculty of Chemistry and Material Science, Langfang Normal University, Langfang 065000, Hebei, China.
  • ShaoLin Li
    From the Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital of Capital Medical University, China (Q.L., P.J., Y.J., H.G., S.L., H.J., Y.L.).
  • Guibo Luo
    Shenzhen Graduate School, Peking University, Xili, Nanshan District, Shenzhen 518055, China. Electronic address: luogb@pku.edu.cn.
  • Guobin Hong
    Department of Radiology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, 519000, Guangdong Province, China. honggb@mail.sysu.edu.cn.