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©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Radiol. Sep 28, 2025; 17(9): 110447
Published online Sep 28, 2025. doi: 10.4329/wjr.v17.i9.110447
Published online Sep 28, 2025. doi: 10.4329/wjr.v17.i9.110447
Artificial intelligence in carotid computed tomography angiography plaque detection: Decade of progress and future perspectives
Dong-Yang Wang, Bing-Lin Li, Hang Yang, Department of Nursing, The Third People’s Hospital of Henan Province, Zhengzhou 450000, Henan Province, China
Tie Yang, Department of Publicity, The Third People’s Hospital of Henan Province, Zhengzhou 450000, Henan Province, China
Chong-Tao Zhang, Department of Vice President, The Third People’s Hospital of Henan Province, Zhengzhou 450000, Henan Province, China
Peng-Chao Zhan, Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
Zhen-Xing Miao, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 73170, Krung Thep Maha Nakhon, Thailand
Hang Yang, Faculty of Humanities and Social Sciences, Macao Polytechnic University, Macau 999078, China
Co-first authors: Dong-Yang Wang and Tie Yang.
Author contributions: Wang D designed the framework and drafted the manuscript; Yang T performed literature analysis; Wang DY and Yang T contributed equally to this work as the co-first authors of the paper; Zhang CT supervised technical content; Zhan PC and Miao ZX collected clinical data; Li BL critically revised the manuscript; all of the authors read and approved the final version of the manuscript to be published.
Supported by Henan Province International Science and Technology Cooperation Project, 2024, No. 242102520054.
Conflict-of-interest statement: All authors declare no conflict of interest in publishing the manuscript.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Hang Yang, Department of Nursing, The Third People’s Hospital of Henan Province, No. 346 Funiu Road, Zhengzhou 450000, Henan Province, China.
Received: June 9, 2025
Revised: August 2, 2025
Accepted: August 27, 2025
Published online: September 28, 2025
Processing time: 112 Days and 6.7 Hours
Revised: August 2, 2025
Accepted: August 27, 2025
Published online: September 28, 2025
Processing time: 112 Days and 6.7 Hours
Core Tip
Core Tip: This is the first mini-review to comprehensively analyze artificial intelligence (AI)-driven advancements in carotid computed tomography angiography plaque detection over ten years. We provide novel insights into hybrid deep learning architectures, domain adaptation techniques, and their clinical translation. The work establishes quantitative benchmarks for diagnostic performance and highlights future directions for explainable AI systems in vascular imaging.