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
Abstract
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.
Cited by
4 articles.
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