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The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy
Esophageal cancer (EC) is one of the fatal malignant neoplasms worldwide. Neoadjuvant therapy (NAT) combined with surgery has become the standard treatment for locally advanced EC. However, the treatment efficacy for patients with EC who received NAT varies from patient to patient. Currently, the ev...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117779/ https://www.ncbi.nlm.nih.gov/pubmed/37091180 http://dx.doi.org/10.3389/fonc.2023.1082960 |
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author | Guo, Hai Tang, Hong-Tao Hu, Wen-Long Wang, Jun-Jie Liu, Pei-Zhi Yang, Jun-Jie Hou, Sen-Lin Zuo, Yu-Jie Deng, Zhi-Qiang Zheng, Xiang-Yun Yan, Hao-Ji Jiang, Kai-Yuan Huang, Heng Zhou, Hai-Ning Tian, Dong |
author_facet | Guo, Hai Tang, Hong-Tao Hu, Wen-Long Wang, Jun-Jie Liu, Pei-Zhi Yang, Jun-Jie Hou, Sen-Lin Zuo, Yu-Jie Deng, Zhi-Qiang Zheng, Xiang-Yun Yan, Hao-Ji Jiang, Kai-Yuan Huang, Heng Zhou, Hai-Ning Tian, Dong |
author_sort | Guo, Hai |
collection | PubMed |
description | Esophageal cancer (EC) is one of the fatal malignant neoplasms worldwide. Neoadjuvant therapy (NAT) combined with surgery has become the standard treatment for locally advanced EC. However, the treatment efficacy for patients with EC who received NAT varies from patient to patient. Currently, the evaluation of efficacy after NAT for EC lacks accurate and uniform criteria. Radiomics is a multi-parameter quantitative approach for developing medical imaging in the era of precision medicine and has provided a novel view of medical images. As a non-invasive image analysis method, radiomics is an inevitable trend in NAT efficacy prediction and prognosis classification of EC by analyzing the high-throughput imaging features of lesions extracted from medical images. In this literature review, we discuss the definition and workflow of radiomics, the advances in efficacy prediction after NAT, and the current application of radiomics for predicting efficacy after NAT. |
format | Online Article Text |
id | pubmed-10117779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101177792023-04-21 The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy Guo, Hai Tang, Hong-Tao Hu, Wen-Long Wang, Jun-Jie Liu, Pei-Zhi Yang, Jun-Jie Hou, Sen-Lin Zuo, Yu-Jie Deng, Zhi-Qiang Zheng, Xiang-Yun Yan, Hao-Ji Jiang, Kai-Yuan Huang, Heng Zhou, Hai-Ning Tian, Dong Front Oncol Oncology Esophageal cancer (EC) is one of the fatal malignant neoplasms worldwide. Neoadjuvant therapy (NAT) combined with surgery has become the standard treatment for locally advanced EC. However, the treatment efficacy for patients with EC who received NAT varies from patient to patient. Currently, the evaluation of efficacy after NAT for EC lacks accurate and uniform criteria. Radiomics is a multi-parameter quantitative approach for developing medical imaging in the era of precision medicine and has provided a novel view of medical images. As a non-invasive image analysis method, radiomics is an inevitable trend in NAT efficacy prediction and prognosis classification of EC by analyzing the high-throughput imaging features of lesions extracted from medical images. In this literature review, we discuss the definition and workflow of radiomics, the advances in efficacy prediction after NAT, and the current application of radiomics for predicting efficacy after NAT. Frontiers Media S.A. 2023-04-06 /pmc/articles/PMC10117779/ /pubmed/37091180 http://dx.doi.org/10.3389/fonc.2023.1082960 Text en Copyright © 2023 Guo, Tang, Hu, Wang, Liu, Yang, Hou, Zuo, Deng, Zheng, Yan, Jiang, Huang, Zhou and Tian https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Guo, Hai Tang, Hong-Tao Hu, Wen-Long Wang, Jun-Jie Liu, Pei-Zhi Yang, Jun-Jie Hou, Sen-Lin Zuo, Yu-Jie Deng, Zhi-Qiang Zheng, Xiang-Yun Yan, Hao-Ji Jiang, Kai-Yuan Huang, Heng Zhou, Hai-Ning Tian, Dong The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy |
title | The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy |
title_full | The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy |
title_fullStr | The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy |
title_full_unstemmed | The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy |
title_short | The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy |
title_sort | application of radiomics in esophageal cancer: predicting the response after neoadjuvant therapy |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117779/ https://www.ncbi.nlm.nih.gov/pubmed/37091180 http://dx.doi.org/10.3389/fonc.2023.1082960 |
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