Publication Name	World Journal of Clinical Cases
Manuscript ID	109397
Country	United States

Category	Oncology
Manuscript Type	Letter to the Editor
Article Title	Advancing predictive oncology: Integrating clinical and radiomic models to optimize transarterial chemoembolization outcomes in hepatocellular carcinoma
Manuscript Source	Invited Manuscript
All Author List	Sujatha Baddam
Funding Agency and Grant Number
Corresponding Author	Sujatha Baddam, Academic Editor, Consultant, MD, Researcher, Department of Internal Medicine, Huntsville Hospital, 101 Sivley Road SW, Huntsville, AL 35801, United States. drsujathabaddam@gmail.com
Key Words	Hepatocellular carcinoma; Radiomics; Transarterial chemoembolization; Alpha-fetoprotein; Predictive modeling; Machine learning; Computed tomography; Texture analysis; Treatment response; Personalized oncology
Core Tip	Radiomic analysis of computed tomography (CT) images—particularly texture and shape features—combined with clinical biomarkers such as alpha-fetoprotein (AFP), enables accurate prediction of response to transarterial chemoembolization (TACE) in hepatocellular carcinoma (HCC), with area under the curve (AUC) values exceeding 0.90. These noninvasive models allow early identification of non-responders, support personalized treatment selection, and may improve outcomes through timely initiation of alternative therapies in liver cancer management.
Citation	Baddam S. Advancing predictive oncology: Integrating clinical and radiomic models to optimize transarterial chemoembolization outcomes in hepatocellular carcinoma. World J Clin Cases 2025; In press

Received	2025-05-12 08:38
Peer-Review Started	2025-05-12 08:38
To Make the First Decision
Return for Revision	2025-05-17 07:58
Revised	2025-05-20 00:54
Second Decision	2025-07-04 02:37
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-07-04 07:35
Articles in Press	2025-07-04 07:35
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2307-8960 (online)
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