Publication Name	World Journal of Gastrointestinal Oncology
Manuscript ID	96598
Country	China

Received	2024-05-10 13:41
Peer-Review Started	2024-05-10 13:41
To Make the First Decision
Return for Revision	2024-08-25 03:57
Revised	2024-09-06 13:26
Second Decision	2024-09-27 02:36
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-09-27 08:48
Articles in Press	2024-09-27 08:48
Publication Fee Transferred	2024-09-29 12:50
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-11-21 03:42
Publish the Manuscript Online	2024-12-12 09:30

ISSN	1948-5204 (online)
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Category	Gastroenterology & Hepatology
Manuscript Type	Retrospective Cohort Study
Article Title	Multiparameter magnetic resonance imaging-based radiomics model for the prediction of rectal cancer metachronous liver metastasis
Manuscript Source	Unsolicited Manuscript
All Author List	Zhi-Da Long, Xiao Yu, Zhi-Xiang Xing and Rui Wang
ORCID	Author(s) ORCID Number Rui Wang http://orcid.org/0009-0004-5263-6745
Funding Agency and Grant Number
Corresponding Author	Rui Wang, MD, Department of Hepatobiliary and Pancreaticosplenic Surgery, Jingzhou Hospital, Yangtze University, No. 26 Chuyuan Road, Jingzhou District, Jingzhou 434100, Hubei Province, China. hyhq0216@163.com
Key Words	Rectal cancer; Metachronous liver metastases; Magnetic resonance imaging; Radiomics; Machine learning
Core Tip	In recent years, with the rapid development of data and information technology, imaging omics has been gradually applied in the clinical diagnosis and treatment of tumors, as it can non-invasive extract high-throughput heterogeneity information within tumors and integrate patient clinical information to improve the accuracy of models. Up to now, imaging omics models based on computed tomography or magnetic resonance imaging (MRI) images have shown potential application value in preoperative T and N staging and efficacy evaluation of rectal cancer. However, there is currently very little imaging omics research based on MRI of primary rectal cancer tumors. In fact, MRI is the most accurate imaging method for diagnosing rectal cancer, which can better display the invasion of adjacent lymph nodes, blood vessels, or surrounding organs by primary rectal cancer tumors. In view of this, this study attempts to establish a non-invasive preoperative prediction model for metachronous liver metastasis in rectal cancer based on the imaging omics features of the initial diagnosis MRI images of rectal cancer, combined with machine learning algorithms, and verify its effectiveness. This will provide clinical assistance for clinicians to make personalized monitoring and treatment decision.
Publish Date	2024-12-12 09:30
Citation	<p>Long ZD, Yu X, Xing ZX, Wang R. Multiparameter magnetic resonance imaging-based radiomics model for the prediction of rectal cancer metachronous liver metastasis. <i>World J Gastrointest Oncol</i> 2025; 17(1): 96598</p>
URL	https://www.wjgnet.com/1948-5204/full/v17/i1/96598.htm
DOI	https://dx.doi.org/10.4251/wjgo.v17.i1.96598

Full Article (PDF)	WJGO-17-96598-with-cover.pdf
STROBE Statement	96598-STROBE-statement.pdf
Manuscript File	96598_Auto_Edited_024108.docx
Answering Reviewers	96598-answering-reviewers.pdf
Audio Core Tip	96598-audio.m4a
Biostatistics Review Certificate	96598-biostatistics-statement.pdf
Conflict-of-Interest Disclosure Form	96598-conflict-of-interest-statement.pdf
Copyright License Agreement	96598-copyright-assignment.pdf
Signed Informed Consent Form(s) or Document(s)	96598-informed-consent-statement.pdf
Institutional Review Board Approval Form or Document	96598-institutional-review-board-statement.pdf
Non-Native Speakers of English Editing Certificate	96598-non-native-speakers.pdf
Supplementary Material	96598-supplementary-material.pdf
Peer-review Report	96598-peer-reviews.pdf
Scientific Misconduct Check	96598-scientific-misconduct-check.png
Scientific Editor Work List	96598-scientific-editor-work-list.pdf
CrossCheck Report	96598-crosscheck-report.png
CrossCheck Report	96598-crosscheck-report.pdf