Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review
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 m...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/14/4/377 |
| _version_ | 1797298469024563200 |
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| author | Mengting Chen Yundan Jiang Xuhui Zhou Di Wu Qiuxia Xie |
| author_facet | Mengting Chen Yundan Jiang Xuhui Zhou Di Wu Qiuxia Xie |
| author_sort | Mengting Chen |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-07T22:35:18Z |
| format | Article |
| id | doaj.art-326dc381bfd344fab621fb0a9f78dd14 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-07T22:35:18Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-326dc381bfd344fab621fb0a9f78dd142024-02-23T15:13:43ZengMDPI AGDiagnostics2075-44182024-02-0114437710.3390/diagnostics14040377Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive ReviewMengting Chen0Yundan Jiang1Xuhui Zhou2Di Wu3Qiuxia Xie4Department of Radiology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518036, ChinaDepartment of Radiology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518036, ChinaDepartment of Radiology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518036, ChinaDepartment of Radiology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518036, ChinaDepartment of Radiology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518036, ChinaThe 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.https://www.mdpi.com/2075-4418/14/4/377DECTmetastatic lymph nodescancerradiomicsartificial intelligencedeep learning |
| spellingShingle | Mengting Chen Yundan Jiang Xuhui Zhou Di Wu Qiuxia Xie Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review Diagnostics DECT metastatic lymph nodes cancer radiomics artificial intelligence deep learning |
| title | Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review |
| title_full | Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review |
| title_fullStr | Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review |
| title_full_unstemmed | Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review |
| title_short | Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review |
| title_sort | dual energy computed tomography in detecting and predicting lymph node metastasis in malignant tumor patients a comprehensive review |
| topic | DECT metastatic lymph nodes cancer radiomics artificial intelligence deep learning |
| url | https://www.mdpi.com/2075-4418/14/4/377 |
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