Copyright: ©Author(s) 2026. 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.
World J Clin Oncol. Mar 24, 2026; 17(3): 113226
Published online Mar 24, 2026. doi: 10.5306/wjco.v17.i3.113226
Published online Mar 24, 2026. doi: 10.5306/wjco.v17.i3.113226
Evolving and novel applications of artificial intelligence in interventional oncology
Sabrina Y Almashni, Dannah C Javens, Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
Fady Bassem Fayek, Department of Radiology, Thomas Jefferson University, Sidney Kimmel Medical College, Philadelphia, PA 19107, United States
Michael T Boulis, Department of Radiology, Texas A&M University College of Medicine, Bryan, TX 77807, United States
Mina S Makary, Division of Vascular and Interventional Radiology, Department of Radiology, The Ohio State University Medical Center, Columbus, OH 43210, United States
Co-corresponding authors: Sabrina Y Almashni and Mina S Makary.
Author contributions: Almashni SY, Fayek FB, Javens DC, Boulis MT, and Makary MS contributed to the writing and preparation of the manuscript and have read and approved the final manuscript. Almashni SY and Makary MS served as co-corresponding authors, jointly conceiving and designing the study. Both Almashni SY and Makary MS were equally responsible for critical revision of the manuscript and final approval. Almashni SY served as the primary corresponding author and was responsible for all communication with the journal throughout submission, peer review, and publication.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Sabrina Y Almashni, Department of Radiology, The Ohio State Uni
Received: August 19, 2025
Revised: September 4, 2025
Accepted: January 26, 2026
Published online: March 24, 2026
Processing time: 216 Days and 10.7 Hours
Revised: September 4, 2025
Accepted: January 26, 2026
Published online: March 24, 2026
Processing time: 216 Days and 10.7 Hours
Core Tip
Core Tip: Artificial intelligence is transforming interventional oncology by enhancing precision, streamlining workflows, and enabling personalized care across all procedural stages. This review highlights emerging applications and outlines how artificial intelligence integration is reshaping practice, improving outcomes, and setting the foundation for data-driven, adaptive interventions in image-guided oncology.