Voxel-level radiomics and deep learning for predicting pathologic complete response in esophageal squamous cell carcinoma after neoadjuvant immunotherapy and chemotherapy.

Journal: Journal for immunotherapy of cancer
PMID:

Abstract

BACKGROUND: Accurate prediction of pathologic complete response (pCR) following neoadjuvant immunotherapy combined with chemotherapy (nICT) is crucial for tailoring patient care in esophageal squamous cell carcinoma (ESCC). This study aimed to develop and validate a deep learning model using a novel voxel-level radiomics approach to predict pCR based on preoperative CT images.

Authors

  • Zhen Zhang
    School of Pharmacy, Jining Medical University, Rizhao, Shandong, China.
  • Tianchen Luo
    Institute of System Science, National University of Singapore, 119260, Singapore.
  • Meng Yan
    School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
  • Haixia Shen
    Zhejiang Cancer Hospital,Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
  • Kaiyi Tao
    Zhejiang Cancer Hospital,Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
  • Jian Zeng
    Longgang District Central Hospital of Shenzhen Shenzhen China.
  • Jingping Yuan
    Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Min Fang
    Department of Clinical Laboratory, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, China.
  • Jian Zheng
    Biospheric Assessment for Waste Disposal Team, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage, Chiba 263-8555, Japan; Fukushima Project Headquarters, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage, Chiba 263-8555, Japan. Electronic address: zheng.jian@qst.go.jp.
  • Inigo Bermejo
    Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, 6229 ET, Netherlands.
  • Andre Dekker
    Department of Radiation Oncology (MAASTRO Clinic), Dr. Tanslaan 12, Maastricht, The Netherlands.
  • Dirk De Ruysscher
    Department of Radiation Oncology (Maastro),GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands.
  • Leonard Wee
    Maastricht University Medical Centre, Netherlands.
  • Wencheng Zhang
    School of Food and Biological Engineering, Hefei University of Technology, Hefei 230601, China; Engineering Research Center of Bio-Process, Ministry of Education, Hefei University of Technology, Hefei 230601, China. Electronic address: zwc1012@163.com.
  • Youhua Jiang
    Zhejiang Cancer Hospital,Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China jiyl@zjcc.org.cn jiangyh@zjcc.org.cn.
  • Yongling Ji
    Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, China.