A machine learning approach using 18F-FDG PET and enhanced CT scan-based radiomics combined with clinical model to predict pathological complete response in ESCC patients after neoadjuvant chemoradiotherapy and anti-PD-1 inhibitors

BackgroundWe aim to evaluate the value of an integrated multimodal radiomics with machine learning model to predict the pathological complete response (pCR) of primary tumor in a prospective cohort of esophageal squamous cell carcinoma (ESCC) treated with neoadjuvant chemoradiotherapy (nCRT) and ant...

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Bibliographic Details

Published in:	Frontiers in Immunology
Main Authors:	Wei-Xiang Qi, Shuyan Li, Jifeng Xiao, Huan Li, Jiayi Chen, Shengguang Zhao
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2024-01-01
Subjects:	radiomics neoadjuvant chemoradiotherapy esophageal squamous cell carcinoma pathological complete response immune checkpoint inhibitor
Online Access:	https://www.frontiersin.org/articles/10.3389/fimmu.2024.1351750/full