Publication Name	World Journal of Gastrointestinal Oncology
Manuscript ID	119986
Country	India

Category	Gastroenterology & Hepatology
Manuscript Type	Minireviews
Article Title	Artificial intelligence in quantitative imaging of esophageal cancer: A review on radiomics, sarcopenia, and survival modeling
Manuscript Source	Invited Manuscript
All Author List	Sivan Sathish, Ankita Jain, Kratee Sharma and Karthika B
Funding Agency and Grant Number
Corresponding Author	Sivan Sathish, Head, Professor, Department of Oral Medicine and Radiology, Teerthanker Mahaveer Dental College and Research Centre, Teerthanker Mahaveer University, Delhi Road, Moradabad 244001, Uttar Pradesh, India. sivansathishmfds@yahoo.co.in
Key Words	Esophageal cancer; Artificial intelligence; Radiomics; Deep learning; Sarcopenia; Survival prediction; Quantitative imaging
Core Tip	This article highlights how artificial intelligence (AI) enables a shift from anatomy-based staging to quantitative, image-driven prognostication in esophageal cancer. By integrating tumor radiomics with AI-derived body composition markers such as sarcopenia, survival models can capture both tumor aggressiveness and host vulnerability from routine imaging modalities. These multimodal approaches consistently outperform conventional staging in survival prediction and risk stratification. Despite challenges in standardization and validation, AI-based quantitative imaging offers a clinically scalable pathway toward personalized survival modeling and precision treatment planning in esophageal cancer.
Citation	Sathish S, Jain A, Sharma K, Karthika B . Artificial intelligence in quantitative imaging of esophageal cancer: A review on radiomics, sarcopenia, and survival modeling. World J Gastrointest Oncol 2026; In press

Received	2026-02-12 02:54
Peer-Review Started	2026-02-12 02:58
First Decision by Editorial Office Director	2026-02-27 08:38
Return for Revision	2026-02-27 08:38
Revised	2026-03-09 08:32
Publication Fee Transferred
Second Decision by Editor	2026-04-16 02:37
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-04-16 06:13
Articles in Press	2026-04-16 06:13
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	1948-5204 (online)
Open Access	This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
Copyright	©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
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