Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram.

Journal: European radiology
PMID: 37498380

Abstract

OBJECTIVES: Hepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus fluorouracil and leucovorin) is a promising option for advanced hepatocellular carcinoma (Ad-HCC). As identifying patients with Ad-HCC who would obtain objective response (OR) to HAIC preoperatively remains a challenge, we aimed to develop an automatic and non-invasive model for predicting HAIC response.

Authors

  • Ziming Xu
  • Chao An
    Department of Minimal invasive intervention, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Feng Shi
    Department of Research and Development, Shanghai United Imaging Intelligence, Co., Ltd. Shanghai, China.
  • He Ren
    Department of Ultrasound in Medicine, Navy General Hospital of PLA, Beijing, China.
  • Yuze Li
    Disinfection and Supply Center, Liyang People's Hospital, Liyang 213300, Jiangsu, China.
  • Song Chen
    Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China.
  • Jiaqi Dou
    Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
  • Yajie Wang
    Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
  • Shaozhen Yan
    Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, No. 45, Changchun Street, Xicheng District, Beijing, 100053, China.
  • Jie Lu
    Department of Endocrinology and Metabolism, the Affiliated Hospital of Qingdao University, Qingdao, People's Republic of China.
  • Huijun Chen
    Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China. Electronic address: chenhj_cbir@mail.tsinghua.edu.cn.

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