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中华胸部外科电子杂志 ›› 2025, Vol. 12 ›› Issue (04) : 228 -234. doi: 10.3877/cma.j.issn.2095-8773.2025.04.06

综述

CT影像组学在食管癌TNM分期中应用的研究进展
刘轶炜, 党艳, 张齐, 马宇航, 张仁泉()   
  1. 230022 合肥,安徽医科大学第一附属医院胸外科
  • 收稿日期:2025-07-20 修回日期:2025-08-03 接受日期:2025-09-26 出版日期:2025-11-28
  • 通信作者: 张仁泉

Research progress of CT radiomics in TNM staging of esophageal cancer

Yiwei Liu, Yan Dang, Qi Zhang, Yuhang Ma, Renquan Zhang()   

  1. Department of Thoracic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
  • Received:2025-07-20 Revised:2025-08-03 Accepted:2025-09-26 Published:2025-11-28
  • Corresponding author: Renquan Zhang
引用本文:

刘轶炜, 党艳, 张齐, 马宇航, 张仁泉. CT影像组学在食管癌TNM分期中应用的研究进展[J/OL]. 中华胸部外科电子杂志, 2025, 12(04): 228-234.

Yiwei Liu, Yan Dang, Qi Zhang, Yuhang Ma, Renquan Zhang. Research progress of CT radiomics in TNM staging of esophageal cancer[J/OL]. Chinese Journal of Thoracic Surgery(Electronic Edition), 2025, 12(04): 228-234.

食管癌位列全球十大恶性肿瘤之列,预后很差,对全球卫生健康构成了重大威胁,成为亟待解决的重大医学难题。一直以来,计算机断层扫描(CT)在食管癌的术前分期、诊断以及术后评估中占据核心地位,它依赖于详细的解剖信息来评价病灶的进程和治疗反应。然而,尽管CT技术不可或缺,但其精度仍有提升空间。尽管活检被誉为诊断的"黄金标准",但它也面临着显著的侵入性以及可能存在误差的风险。随着新型影像技术的迅速涌现,影像组学在恶性肿瘤领域备受瞩目,引发了广泛关注与研究。特别是在癌症的精确分期和肿瘤异质性评估等多个关键环节,影像组学已经显示出前所未有的应用潜力。尤其在食管癌的TNM分期体系中,CT影像组学的应用正展现出极为广阔的前景和实际价值。本文系统梳理CT影像组学在食管癌TNM分期中的应用现状与研究进展,旨在为食管癌精准分期及制订个体化治疗策略提供更具针对性的理论依据与实践参考。

Esophageal cancer ranks among the top 10 malignant tumors worldwide, with a very poor prognosis, posing a major challenge to global health and representing a critical medical problem to be addressed. Computed tomography (CT) has long played a central role in the preoperative staging, diagnosis and postoperative evaluation of esophageal cancer, it relies on detailed anatomical information to evaluate the progress of the lesion and the response to treatment. However, although CT technology is indispensable, there is still room for improvement in its accuracy. Although biopsy is known as the "gold standard" for diagnosis, it faces significant invasiveness and potential error risks. With the rapid emergence of new imaging techniques, radiomics has garnered significant attention and extensive research in the field of malignant tumors. In particular, radiomics has shown unprecedented application potential in many key areas such as accurate staging of cancer and assessment of tumor heterogeneity. Especially in the TNM staging system of esophageal cancer, the application of CT radiomics is showing extremely broad prospects and practical value. This paper reviews the application and research progress of CT radiomics in TNM staging of esophageal cancer, to provide theoretical support and guidance for future research on accurate diagnosis and treatment of esophageal cancer.

图1 食管癌影像分析关键环节示意图。A:原始图像;B:勾画感兴趣区域;C:重构肿瘤形态;D:特征提取
图2 食管癌影像组学评估分期流程图。ROI:感兴趣区域
表1 各研究模型性能
1
Sung HFerlay JSiegel RL,et al.Global Cancer Statistics 2020:GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries[J].CA Cancer J Clin202171(3):209-249.
2
Arnold MAbnet CCNeale RE,et al.Global Burden of 5 Major Types of Gastrointestinal Cancer[J].Gastroenterology2020159(1):335-349.e15.
3
Siegel RLMiller KDWagle NS,et al.Cancer statistics,2023[J].CA Cancer J Clin202373(1):17-48.
4
Deboever NJones CMYamashita K,et al.Advances in diagnosis and management of cancer of the esophagus[J].BMJ2024385:e074962.
5
Lambin PRios-Velazquez ELeijenaar R,et al.Radiomics:extracting more information from medical images using advanced feature analysis. Eur J Cancer201248(4):441-446.
6
Cheng FLiu YDu L,et al.Evaluation of optimal monoenergetic images acquired by dual-energy CT in the diagnosis of T staging of thoracic esophageal cancer[J].Insights Imaging202314(1):33.
7
Shimada HFukagawa THaga Y,et al.Clinical TNM staging for esophageal,gastric,and colorectal cancers in the era of neoadjuvant therapy:A systematic review of the literature[J].Ann Gastroenterol Surg20215(4):404-418.
8
Guo JWang ZQin J,et al.A prospective analysis of the diagnostic accuracy of 3 T MRI,CT and endoscopic ultrasound for preoperative T staging of potentially resectable esophageal cancer[J].Cancer Imaging202020(1):64.
9
朱宗明,冯银波,陶广宇,et al. 基于CT图像纹理分析方法对胸段食管癌术前T分期的研究价值. 临床放射学杂志201938(01):72-6.
10
Zhao BYan SJia ZY,et al.CT radiomics in the identification of preoperative understaging in patients with clinical stage T1~2N0 esophageal squamous cell carcinoma[J].Quant Imaging Med Surg202313(12):7996-8008.
11
Wu LWang CTan X,et al.Radiomics approach for preoperative identification of stages Ⅰ~Ⅱ and Ⅲ~Ⅳ of esophageal cancer[J].Chin J Cancer Res201830(4):396-405.
12
Lei XCao ZWu Y,et al.Preoperative prediction of clinical and pathological stages for patients with esophageal cancer using PET/CT radiomics[J].Insights Imaging202314(1):174.
13
Zeybek AErdoğan AGülkesen KH,et al.Significance of tumor length as prognostic factor for esophageal cancer[J].Int Surg201398(3):234-240.
14
Wang YHuang YZhao QY,et al.Esophageal wall thickness on CT scans:can it predict the T stage of primary thoracic esophageal squamous cell carcinoma?[J].Esophagus202219(2):269-277.
15
Yang MHu PLi M,et al.Computed Tomography-Based Radiomics in Predicting T Stage and Length of Esophageal Squamous Cell Carcinoma[J].Front Oncol202111:722961.
16
Gao DTan BGChen XQ,et al.Contrast-enhanced CT radiomics features to preoperatively identify differences between tumor and proximal tumor-adjacent and tumor-distant tissues of resectable esophageal squamous cell carcinoma[J].Cancer Imaging202424(1):11.
17
Tan XZMa RLiu P,et al.Decoding tumor stage by peritumoral and intratumoral radiomics in resectable esophageal squamous cell carcinoma[J].Abdom Radiol (NY)202449(1):301-311.
18
Wakita AMotoyama SSato Y,et al.Evaluation of metastatic lymph nodes in cN0 thoracic esophageal cancer patients with inconsistent pathological lymph node diagnosis[J].World J Surg Oncol202018(1):111.
19
Liu LLiao HZhao Y,et al.CT-based radiomics for predicting lymph node metastasis in esophageal cancer:a systematic review and meta-analysis[J].Front Oncol202414:1267596.
20
Wu YPWu LOu J,et al.Preoperative CT radiomics of esophageal squamous cell carcinoma and lymph node to predict nodal disease with a high diagnostic capability[J].Eur J Radiol2024170:111197.
21
李扬.CT影像组学预测食管癌淋巴血管侵犯状态的研究[D].石家庄:河北医科大学,2022
22
余鎏,黄玲玲,袁振亚,等.基于CT平扫影像组学模型预测食管癌淋巴结转移[J].中国医学影像技术202137(9):1333-1337.
23
Zhu CMu FWang S,et al.Prediction of distant metastasis in esophageal cancer using a radiomics-clinical model[J].Eur J Med Res202227(1):272.
24
Wang YLiu WYu Y,et al.Prediction of the Depth of Tumor Invasion in Gastric Cancer:Potential Role of CT Radiomics[J].Acad Radiol202027(8):1077-1084.
25
Zhou HZhou JQin C,et al.Preoperative Prediction of Perineural Invasion in Oesophageal Squamous Cell Carcinoma Based on CT Radiomics Nomogram:A Multicenter Study[J].Acad Radiol202431(4):1355-1366.
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