Publication Name	World Journal of Gastrointestinal Oncology
Manuscript ID	115635
Country	China

Category	Gastroenterology & Hepatology
Manuscript Type	Retrospective Cohort Study
Article Title	Deep learning radiomics nomogram based on multi-regional features for predicting lymph node metastasis and prognosis in colorectal cancer
Manuscript Source	Unsolicited Manuscript
All Author List	Xue-Di Lei, Gui-Xiang Qian, Zhi-Gang Sun, Zi-Qi Tang, Yuan-Cheng Liu, Rui Du and Yong-Hai Li
Funding Agency and Grant Number	Funding Agency Grant Number Anhui Provincial Research Project on the Inheritance and Innovation of Traditional Chinese Medicine No. 2024CCCX007 Graduate Research and Innovation Program of Bengbu Medical University No. Byycxz24046
Corresponding Author	Yong-Hai Li, MD, Department of Anorectal Surgery, The First People’s Hospital of Hefei, No. 390 Huaihe Road, Hefei 230001, Anhui Province, China. liyonghai@ahmu.edu.cn
Key Words	Colorectal cancer; Radiomics; Deep learning; Lymph node metastasis; Prognosis; Contrast-enhanced computed tomography; Nomogram; Shapley additive explanation
Core Tip	Accurate preoperative prediction of lymph node metastasis is crucial for optimizing treatment strategies in colorectal cancer. In this study, we developed an interpretable clinical-deep learning-radiomics nomogram (DLRN) by integrating clinical features with multi-regional radiomics and deep learning features. Moreover, the DLRN-based prognostic model effectively predicted 3-year recurrence-free survival. As a noninvasive preoperative tool, the DLRN demonstrated strong predictive accuracy for lymph node metastasis in colorectal cancer and offers a practical means for individualized risk stratification and informed treatment decision-making.
Citation	Lei XD, Qian GX, Sun ZG, Tang ZQ, Liu YC, Du R, Li YH. Deep learning radiomics nomogram based on multi-regional features for predicting lymph node metastasis and prognosis in colorectal cancer. World J Gastrointest Oncol 2026; In press

Received	2025-10-22 09:47
Peer-Review Started	2025-10-22 09:49
First Decision by Editorial Office Director	2025-11-19 10:44
Return for Revision	2025-11-20 13:54
Revised	2025-12-04 12:32
Publication Fee Transferred	2025-12-09 10:27
Second Decision by Editor	2026-02-04 02:52
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-02-04 06:59
Articles in Press	2026-02-04 06:59
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	1948-5204 (online)
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