Image-based artificial intelligence predicts the efficacy of neoadjuvant chemoradiotherapy for esophageal cancer
10.3760/cma.j.cn113030-20240312-00095
- VernacularTitle:影像人工智能预测食管癌新辅助放化疗疗效
- Author:
Yunsong LIU
1
;
Zeliang MA
;
Yu MEN
;
Zhouguang HUI
Author Information
1. 国家癌症中心/国家肿瘤临床医学研究中心/中国医学科学院北京协和医学院肿瘤医院放疗科，北京 100021
- Keywords:
Esophageal neoplasms;
Medical imaging;
Artificial intelligence;
Neoadjuvant chemoradiotherapy
- From:
Chinese Journal of Radiation Oncology
2024;33(11):1070-1076
- CountryChina
- Language:Chinese
-
Abstract:
Neoadjuvant chemoradiotherapy combined with surgery is the standard treatment for patients with locally advanced esophageal cancer. However, there is significant variability in how patients respond to neoadjuvant chemoradiotherapy. The value of existing conventional diagnostic methods in predicting the effectiveness of neoadjuvant chemoradiotherapy is limited. Image-based artificial intelligence (AI), particularly radiomics and deep learning technologies, have shown great potential in predicting the efficacy of neoadjuvant chemoradiotherapy by automatically quantifying and analyzing a vast amount of information in medical images. This review summarizes AI research based on CT, positron emission computed tomography (PET-CT), and other imaging modalities, highlighting the current limitations and future directions of the research.
