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©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
Application of texture signatures based on multiparameter-magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma: Retrospective study
Hai-Yang Nong, Yong-Yi Cen, Mi Qin, Wen-Qi Qin, You-Xiang Xie, Lin Li, Man-Rong Liu, Ke Ding
Hai-Yang Nong, Mi Qin, Wen-Qi Qin, You-Xiang Xie, Ke Ding, Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
Hai-Yang Nong, Department of Radiology, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China
Yong-Yi Cen, Department of Radiology, The First Affiliated Hospital of Guangxi University of Traditional Chinese Medicine, Nanning 530031, Guangxi Zhuang Autonomous Region, China
Lin Li, Department of Hepatobiliary Surgery, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
Man-Rong Liu, Department of Ultrasound, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
Co-corresponding authors: Man-Rong Liu and Ke Ding.
Author contributions: Nong HY, Ding K, Cen YY, and Qin M carried out the studies, participated in collecting data, and drafted the manuscript; Ding K, Liu MR, Nong HY, and Li L performed the statistical analysis and participated in its design; Qin WQ and Xie YX helped to draft the manuscript; all authors read and approved the final manuscript. Liu MR and Ding K contributed equally to this study and serve as co-corresponding authors of this study.
Supported by National Natural Science Foundation of China, No. 81560278; and the Health Commission of Guangxi Zhuang Autonomous Region, No. Z-A20221157, No. Z20200953, and No. G201903023.
Institutional review board statement: The study protocol was approved by the Ethics Committees of The Third Affiliated Hospital of Guangxi Medical University.
Informed consent statement: All the patients provided written informed consent for participation.
Conflict-of-interest statement: There are no conflicts of interest to report.
Data sharing statement: No additional data are available.
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: Ke Ding, MD, Doctor, Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, No. 13 Dancun Road, Nanning 530031, Guangxi Zhuang Autonomous Region, China. 272480365@qq.com
Received: October 30, 2023
Peer-review started: October 30, 2023
First decision: December 5, 2023
Revised: December 18, 2023
Accepted: February 5, 2024
Article in press: February 5, 2024
Published online: April 15, 2024
BACKGROUND
Despite continuous changes in treatment methods, the survival rate for advanced hepatocellular carcinoma (HCC) patients remains low, highlighting the importance of diagnostic methods for HCC.
AIM
To explore the efficacy of texture analysis based on multi-parametric magnetic resonance (MR) imaging (MRI) in predicting microvascular invasion (MVI) in preoperative HCC.
METHODS
This study included 105 patients with pathologically confirmed HCC, categorized into MVI-positive and MVI-negative groups. We employed Original Data Analysis, Principal Component Analysis, Linear Discriminant Analysis (LDA), and Non-LDA (NDA) for texture analysis using multi-parametric MR images to predict preoperative MVI. The effectiveness of texture analysis was determined using the B11 program of the MaZda4.6 software, with results expressed as the misjudgment rate (MCR).
RESULTS
Texture analysis using multi-parametric MRI, particularly the MI + PA + F dimensionality reduction method combined with NDA discrimination, demonstrated the most effective prediction of MVI in HCC. Prediction accuracy in the pulse and equilibrium phases was 83.81%. MCRs for the combination of T2-weighted imaging (T2WI), arterial phase, portal venous phase, and equilibrium phase were 22.86%, 16.19%, 20.95%, and 20.95%, respectively. The area under the curve for predicting MVI positivity was 0.844, with a sensitivity of 77.19% and specificity of 91.67%.
CONCLUSION
Texture analysis of arterial phase images demonstrated superior predictive efficacy for MVI in HCC compared to T2WI, portal venous, and equilibrium phases. This study provides an objective, non-invasive method for preoperative prediction of MVI, offering a theoretical foundation for the selection of clinical therapy.
Core Tip: Texture analysis using arterial phase images provides superior predictive efficacy for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) compared to T2-weighted imaging, portal venous, and equilibrium phases. The texture analysis of liver magnetic resonance images holds significant value for the preoperative prediction of MVI in HCC patients.
