Progress of magnetic resonance imaging radiomics in preoperative lymph node diagnosis of esophageal cancer

被引:3
|
作者
Xu, Yan-Han [1 ]
Lu, Peng [2 ]
Gao, Ming-Cheng [1 ]
Wang, Rui [1 ]
Li, Yang-Yang [1 ]
Song, Jian-Xiang [1 ]
机构
[1] Nantong Univ, Yancheng Peoples Hosp 3, Affiliated Hosp 6, Dept Thorac Surg, 500 Yonghe Rd, Yancheng 224000, Jiangsu, Peoples R China
[2] Nantong Univ, Yancheng Peoples Hosp 3, Affiliated Hosp 6, Dept Imaging, Yancheng 224000, Jiangsu, Peoples R China
来源
WORLD JOURNAL OF RADIOLOGY | 2023年 / 15卷 / 07期
关键词
Esophageal cancer; Diffusion-weighted imaging; Dynamic contrast-enhanced imaging; Radiomics; Lymph nodes; SQUAMOUS-CELL CARCINOMA; APPARENT DIFFUSION-COEFFICIENT; LIMITED TRANSHIATAL RESECTION; NEOADJUVANT CHEMORADIATION; ENDOSCOPIC ULTRASOUND; HISTOGRAM ANALYSIS; PROGNOSTIC IMPACT; ECHO SEQUENCE; MRI; ADENOCARCINOMA;
D O I
10.4329/wjr.v15.i7.216
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Esophageal cancer, also referred to as esophagus cancer, is a prevalent disease in the cardiothoracic field and is a leading cause of cancer-related mortality in China. Accurately determining the status of lymph nodes is crucial for developing treatment plans, defining the scope of intraoperative lymph node dissection, and ascertaining the prognosis of patients with esophageal cancer. Recent advances in diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging (MRI) have improved the effectiveness of MRI for assessing lymph node involvement, making it a beneficial tool for guiding personalized treatment plans for patients with esophageal cancer in a clinical setting. Radiomics is a recently developed imaging technique that transforms radiological image data from regions of interest into high-dimensional feature data that can be analyzed. The features, such as shape, texture, and waveform, are associated with the cancer phenotype and tumor microenvironment. When these features correlate with the clinical disease outcomes, they form the basis for specific and reliable clinical evidence. This study aimed to review the potential clinical applications of MRI-based radiomics in studying the lymph nodes affected by esophageal cancer. The combination of MRI and radiomics is a powerful tool for diagnosing and treating esophageal cancer, enabling a more personalized and effectual approach.
引用
收藏
页数:11
相关论文
共 50 条
  • [41] PREOPERATIVE ASSESSMENT OF CERVICAL LYMPH-NODE INVOLVEMENT IN ESOPHAGEAL CANCER
    SAITO, T
    KUWAHARA, A
    KAKETANI, K
    HIRAO, E
    MIYAHARA, M
    SHIMODA, K
    KOBAYASHI, M
    JAPANESE JOURNAL OF SURGERY, 1991, 21 (02): : 145 - 153
  • [42] Preoperative Magnetic Resonance Imaging Radiomics for Predicting Early Recurrence of Glioblastoma
    Wang, Jing
    Yi, Xiaoping
    Fu, Yan
    Pang, Peipei
    Deng, Huihuang
    Tang, Haiyun
    Han, Zaide
    Li, Haiping
    Nie, Jilin
    Gong, Guanghui
    Hu, Zhongliang
    Tan, Zeming
    Chen, Bihong T.
    FRONTIERS IN ONCOLOGY, 2021, 11
  • [43] Exploring Applications of Radiomics in Magnetic Resonance Imaging of Head and Neck Cancer: A Systematic Review
    Jethanandani, Amit
    Lin, Timothy A.
    Volpe, Stefanie
    Elhalawani, Hesham
    Mohamed, Abdallah S. R.
    Yang, Pei
    Fuller, Clifton D.
    FRONTIERS IN ONCOLOGY, 2018, 8
  • [44] Dual-mode ultrasound radiomics and intrinsic imaging phenotypes for diagnosis of lymph node lesions
    Chen, Ying
    Jiang, Jianwei
    Shi, Jie
    Chang, Wanying
    Shi, Jun
    Chen, Man
    Zhang, Qi
    ANNALS OF TRANSLATIONAL MEDICINE, 2020, 8 (12)
  • [45] Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study
    Yu, Yunfang
    He, Zifan
    Ouyang, Jie
    Tan, Yujie
    Chen, Yongjian
    Gu, Yang
    Mao, Luhui
    Ren, Wei
    Wang, Jue
    Lin, Lili
    Wu, Zhuo
    Liu, Jingwen
    Ou, Qiyun
    Hu, Qiugen
    Li, Anlin
    Chen, Kai
    Li, Chenchen
    Lu, Nian
    Li, Xiaohong
    Su, Fengxi
    Liu, Qiang
    Xie, Chuanmiao
    Yao, Herui
    EBIOMEDICINE, 2021, 69
  • [46] Role of magnetic resonance imaging and positron emission tomography/computed tomography in preoperative lymph node detection of uterine cervical cancer
    Chung, Hyun Hoon
    Kang, Keon Wook
    Cho, Jeong Yeon
    Kim, Jae Weon
    Park, Noh-Hyun
    Song, Yong-Sang
    Kim, Seung Hyup
    Chung, June-Key
    Kang, Soon-Beom
    AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY, 2010, 203 (02) : 156.e1 - 156.e5
  • [47] Deep Learning Radiomics of Preoperative Breast MRI for Prediction of Axillary Lymph Node Metastasis in Breast Cancer
    Yanhong Chen
    Lijun Wang
    Xue Dong
    Ran Luo
    Yaqiong Ge
    Huanhuan Liu
    Yuzhen Zhang
    Dengbin Wang
    Journal of Digital Imaging, 2023, 36 : 1323 - 1331
  • [48] Diagnostic performance of diffusion-weighted magnetic resonance imaging in assessing lymph node metastasis of esophageal cancer compared with PET
    Kiyohiko Shuto
    Tsuguaki Kono
    Toru Shiratori
    Yasunori Akutsu
    Masaya Uesato
    Mikito Mori
    Kazuo Narushima
    Shunsuke Imanishi
    Yoshihiro Nabeya
    Noriyuki Yanagawa
    Shinichi Okazumi
    Keiji Koda
    Hisahiro Matsubara
    Esophagus, 2020, 17 : 239 - 249
  • [49] Magnetic resonance imaging-based radiomics signature for preoperative prediction of Ki67 expression in bladder cancer
    Zheng, Zongtai
    Gu, Zhuoran
    Xu, Feijia
    Maskey, Niraj
    He, Yanyan
    Yan, Yang
    Xu, Tianyuan
    Liu, Shenghua
    Yao, Xudong
    CANCER IMAGING, 2021, 21 (01)
  • [50] Diagnostic performance of diffusion-weighted magnetic resonance imaging in assessing lymph node metastasis of esophageal cancer compared with PET
    Shuto, Kiyohiko
    Kono, Tsuguaki
    Shiratori, Toru
    Akutsu, Yasunori
    Uesato, Masaya
    Mori, Mikito
    Narushima, Kazuo
    Imanishi, Shunsuke
    Nabeya, Yoshihiro
    Yanagawa, Noriyuki
    Okazumi, Shinichi
    Koda, Keiji
    Matsubara, Hisahiro
    ESOPHAGUS, 2020, 17 (03) : 239 - 249