Publication Name	World Journal of Gastroenterology
Manuscript ID	120899
DOI	10.3748/wjg.120899
Country	China

Category	Imaging Science & Photographic Technology
Manuscript Type	Retrospective Study
Article Title	Endoscopic ultrasound-based deep learning for predicting chemotherapy response in unresectable pancreatic ductal adenocarcinoma
Manuscript Source	Unsolicited Manuscript
All Author List	Ze-Hua Li, Jun Weng, Yu-Hong Zeng, Shi-Yong Lin, Shuo Li, Kun-Hao Bai and Guo-Liang Xu
Funding Agency and Grant Number	Funding Agency Grant Number National Natural Science Foundation of China (General Program) No. 82403973, No. 82200442, and No. 82373118 Guangdong Basic and Applied Basic Research Foundation No. 2023A1515010828 Science and Technology Program of Guangzhou No. 2025A04J3768 Guangdong Medical Equipment Association Research Fund No. YZXH2025KT07 Hong Kong Scholar, Hong Kong Scholar No. XJWQ2025016
Corresponding Author	Guo-Liang Xu, Department of Endoscopy, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, No. 651 Dongfeng East Road, Yuexiu District, Guangzhou 510060, Guangdong Province, China. xugl@sysucc.org.cn
Key Words	Pancreatic ductal adenocarcinoma; Endoscopic ultrasound; Convolutional neural network; Deep learning; Chemotherapy response
Core Tip	Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, and predicting chemotherapy response remains challenging. This study developed deep learning models based on pre-treatment endoscopic ultrasound images to predict chemotherapy response in PDAC. Four convolutional neural network architectures were evaluated, with ResNeXt50 demonstrating the best performance in the independent test cohort. The model also enabled effective risk stratification for overall survival, outperforming conventional serum biomarker carbohydrate antigen 19-9. These findings suggest that endoscopic ultrasound-based convolutional neural network models may provide a noninvasive tool to support individualized treatment planning in PDAC.
Citation	Li ZH, Weng J, Zeng YH, Lin SY, Li S, Bai KH, Xu GL. Endoscopic ultrasound-based deep learning for predicting chemotherapy response in unresectable pancreatic ductal adenocarcinoma. World J Gastroenterol 2026; In press DOI: https://doi.org/10.3748/wjg.120899

Received	2026-03-12 02:22
Peer-Review Started	2026-03-12 02:22
First Decision by Editorial Office Director	2026-04-03 09:15
Return for Revision	2026-04-03 09:15
Revised	2026-04-20 16:43
Publication Fee Transferred	2026-04-21 15:18
Second Decision by Editor	2026-06-03 02:34
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-06-03 07:14
Articles in Press	2026-06-03 07:14
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	1007-9327 (print) and 2219-2840 (online)
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