Prediction of ISUP grading of clear cell renal cell carcinoma using support vector machine model based on CT images.

Journal: Medicine
Published Date: Apr 1, 2019

Abstract

BACKGROUND: To explore whether radiomics combined with computed tomography (CT) images can be used to establish a model for differentiating high grade (International Society of Urological Pathology [ISUP] grade III-IV) from low-grade (ISUP I-II) clear cell renal cell carcinoma (ccRCC).

Authors

  • Xiaoqing Sun
    Department of Radiology, China-Japan Union Hospital of Jilin University.
  • Lin Liu
    Institute of Natural Sciences, MOE-LSC, School of Mathematical Sciences, CMA-Shanghai, SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University; Shanghai Artificial Intelligence Laboratory.
  • Kai Xu
    Department of Anesthesiology, Huai'an Hospital Affiliated to Yangzhou University (The Fifth People's Hospital of Huai'an), Huaian, China.
  • Wenhui Li
    College of Computer Science and Technology, Jilin University.
  • Ziqi Huo
    Department of Radiology, China-Japan Union Hospital of Jilin University.
  • Heng Liu
    Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, College of Pharmacy, Dali University, Dali, Yunnan, PR China; National-Local Joint Engineering Research Center of Entomoceutics, Dali, PR China.
  • Tongxu Shen
    Department of Radiology, China-Japan Union Hospital of Jilin University.
  • Feng Pan
    Department of Radiation Oncology, China-Japan Union Hospital of Jilin University, Changchun, China.
  • Yuqing Jiang
    Department of Radiology, China-Japan Union Hospital of Jilin University.
  • Mengchao Zhang
    Department of Radiology, China-Japan Union Hospital of Jilin University.

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