Copyright
©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma
Yi-Di Chen, Ling Zhang, Zhi-Peng Zhou, Bin Lin, Zi-Jian Jiang, Cheng Tang, Yi-Wu Dang, Yu-Wei Xia, Bin Song, Li-Ling Long
Yi-Di Chen, Ling Zhang, Zi-Jian Jiang, Cheng Tang, Li-Ling Long, Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
Zhi-Peng Zhou, Bin Lin, Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin 541001, Guangxi Zhuang Autonomous Region, China
Yi-Wu Dang, Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 5350021, Guangxi Zhuang Autonomous Region, China
Yu-Wei Xia, Department of Technology, Huiying Medical Technology (Beijing), Beijing 100192, China
Bin Song, Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Li-Ling Long, Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
Li-Ling Long, Guangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
Author contributions: Chen YD and Zhang L contributed equally to this work; Chen YD and Long LL was the guarantor and designed the study; Zhang L, Lin B, Jiang ZJ, Tang C, Dang YW, and Xia YW participated in the acquisition, analysis, interpretation of the data, and drafted the initial manuscript; Zhou ZP and Song B revised the article critically for important intellectual content.
Supported by the National Natural Science Foundation of China, No. 82060310; and Science and Technology Support Program of Sichuan Province, No. 2022YFS0071.
Institutional review board statement: The study was reviewed and approved by The First Affiliated Hospital of Guangxi Medical University Ethical Review Committee, No. 2019 KY-E-65.
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: There are no conflicts of interest to report.
Data sharing statement: The data that support the findings of this study are available in the Baidu Netdisk or our AI Scientific Research Platform (
https://mics.radcloud.cn/). Further enquiries can be directed to the corresponding author.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
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: Li-Ling Long, MD, Chairman, Chief Doctor, Professor, Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, China. cjr.longliling@vip.163.com
Received: December 14, 2021
Peer-review started: December 14, 2021
First decision: January 27, 2022
Revised: February 5, 2022
Accepted: July 24, 2022
Article in press: July 24, 2022
Published online: August 21, 2022
ARTICLE HIGHLIGHTS
Research background
Microvascular invasion (MVI) of hepatocellular carcinoma (HCC) is an independent poor prognostic factor.
Research motivation
It is difficult to determine MVI of small hepatocellular carcinoma (HCC) (≤ 3.0 cm) by preoperative MRI conventional features.
Research objectives
To develop and validate radiomics scores and nomogram of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) for preoperative prediction of MVI in sHCC.
Research methods
Radiomics models of Gd-EOB-DTPA enhanced MRI and diffusion weighted images were constructed and validated by machine learning from data sets of three hospitals. A nomogram prediction model was developed using multivariable logistic regression analysis which included the radiomics scores, radiologic features, and alpha-fetoprotein (AFP) level.
Research results
AFP and MRI conventional features had poor diagnostic value for MVI of small HCC. The nomogram model (combined radiomics and clinic features) exhibited good calibration and discrimination in the testing and two external validation cohorts (in the two external validation cohorts, C-index was 0.912 and 0.808, respectively).
Research conclusions
As a noninvasive preoperative prediction method, the MRI radiomics nomogram shows favorable predictive accuracy for evaluate MVI in sHCC.
Research perspectives
This clinical prediction model may help in the selection of treatment options for small HCC.
