Chen TY, Yang ZG, Li Y, Li MQ. Radiomic advances in the transarterial chemoembolization related therapy for hepatocellular carcinoma. World J Radiol 2023; 15(4): 89-97 [PMID: 37181821 DOI: 10.4329/wjr.v15.i4.89]
Corresponding Author of This Article
Mao-Quan Li, MD, PhD, Director, Professor, Department of Interventional & Vascular Surgery, Tenth People's Hospital of Tongji University, Institute of Interventional & Vascular Surgery, Tongji University, No. 301 Middle Yan Chang Road, Shanghai 200072, China. cjr.limaoquan@vip.163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
World J Radiol. Apr 28, 2023; 15(4): 89-97 Published online Apr 28, 2023. doi: 10.4329/wjr.v15.i4.89
Radiomic advances in the transarterial chemoembolization related therapy for hepatocellular carcinoma
Tian-You Chen, Zong-Guo Yang, Ying Li, Mao-Quan Li
Tian-You Chen, Department of Interventional Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
Zong-Guo Yang, Department of Integrative Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
Ying Li, Department of Radiology, Jinshan Hospital, Fudan University, Shanghai 201508, China
Mao-Quan Li, Department of Interventional & Vascular Surgery, Tenth People's Hospital of Tongji University, Tongji University, Shanghai 200433, China
Author contributions: Chen TY, Yang ZG, Li Y, Li MQ equally contributed to this paper with conception and design of the study, literature review and analysis, drafting and critical revision and editing, and final approval of the final version.
Conflict-of-interest statement: All the authors declare that they have no conflicting interests.
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: Mao-Quan Li, MD, PhD, Director, Professor, Department of Interventional & Vascular Surgery, Tenth People's Hospital of Tongji University, Institute of Interventional & Vascular Surgery, Tongji University, No. 301 Middle Yan Chang Road, Shanghai 200072, China. cjr.limaoquan@vip.163.com
Received: November 18, 2022 Peer-review started: November 18, 2022 First decision: February 15, 2023 Revised: March 3, 2023 Accepted: March 30, 2023 Article in press: March 30, 2023 Published online: April 28, 2023 Processing time: 158 Days and 23.6 Hours
Abstract
Radiomics is a hot topic in the research on customized oncology treatment, efficacy evaluation, and tumor prognosis prediction. To achieve the goal of mining the heterogeneity information within the tumor tissue, the image features concealed within the tumoral images are turned into quantifiable data features. This article primarily describes the research progress of radiomics and clinical-radiomics combined model in the prediction of efficacy, the choice of treatment modality, and survival in transarterial chemoembolization (TACE) and TACE combination therapy for hepatocellular carcinoma.
Core Tip: Hepatic cancer is a highly varied primary liver malignancy, and distinct tumor stages necessitate different techniques to guarantee appropriate therapeutic efficacy. Radiomics is a potential method, which can predict the benefits of patients with different treatment methods and different tumor stages through the obtained potential information of clinical medical imaging that is difficult to identify with the naked eye, and predict the outcome of patients, thereby assisting precision medical decision-making. In this paper, we propose and discuss the possible use of radiomics in the selection of treatment modalities and efficacy prediction for liver cancer.
