Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review

被引:5
|
作者
Chen, Mengting [1 ]
Jiang, Yundan [1 ]
Zhou, Xuhui [1 ]
Wu, Di [1 ]
Xie, Qiuxia [1 ]
机构
[1] Sun Yat Sen Univ, Affiliated Hosp 8, Dept Radiol, Shenzhen 518036, Peoples R China
关键词
DECT; metastatic lymph nodes; cancer; radiomics; artificial intelligence; deep learning; PAPILLARY THYROID-CARCINOMA; PREOPERATIVE DIAGNOSIS; SPECTRAL CT; QUANTITATIVE PARAMETERS; IODINE QUANTIFICATION; CANCER; RADIOMICS; ULTRASONOGRAPHY;
D O I
10.3390/diagnostics14040377
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The accurate and timely assessment of lymph node involvement is paramount in the management of patients with malignant tumors, owing to its direct correlation with cancer staging, therapeutic strategy formulation, and prognostication. Dual-energy computed tomography (DECT), as a burgeoning imaging modality, has shown promising results in the diagnosis and prediction of preoperative metastatic lymph nodes in recent years. This article aims to explore the application of DECT in identifying metastatic lymph nodes (LNs) across various cancer types, including but not limited to thyroid carcinoma (focusing on papillary thyroid carcinoma), lung cancer, and colorectal cancer. Through this narrative review, we aim to elucidate the clinical relevance and utility of DECT in the detection and predictive assessment of lymph node metastasis in malignant tumors, thereby contributing to the broader academic discourse in oncologic radiology and diagnostic precision.
引用
收藏
页数:12
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