Observational Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Dec 7, 2024; 30(45): 4801-4816
Published online Dec 7, 2024. doi: 10.3748/wjg.v30.i45.4801
Evaluating microvascular invasion in hepatitis B virus-related hepatocellular carcinoma based on contrast-enhanced computed tomography radiomics and clinicoradiological factors
Zi-Ling Xu, Gui-Xiang Qian, Yong-Hai Li, Jian-Lin Lu, Ming-Tong Wei, Xiang-Yi Bu, Yong-Sheng Ge, Yuan Cheng, Wei-Dong Jia
Zi-Ling Xu, Jian-Lin Lu, Ming-Tong Wei, Department of General Surgery, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei 230001, Anhui Province, China
Gui-Xiang Qian, Xiang-Yi Bu, Yong-Sheng Ge, Yuan Cheng, Wei-Dong Jia, Department of General Surgery, Anhui Provincial Hospital, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Science and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China
Yong-Hai Li, Department of Anorectal Surgery, The First People's Hospital of Hefei, Hefei 230001, Anhui Province, China
Co-first authors: Zi-Ling Xu and Gui-Xiang Qian.
Co-corresponding authors: Yuan Cheng and Wei-Dong Jia.
Author contributions: Xu ZL, Cheng Y and Jia WD designed and conceptualized the research; Xu ZL, Qian GX, Li YH, Lu JL, Bu XY and Wei MT screened patients and acquired clinical data; Xu ZL, Qian GX, Li YH, Lu JL, Bu XY, Wei MT, Cheng Y and Ge YS performed Data analysis; Xu ZL, Qian GX, Cheng Y, Ge YS, Jia WD wrote the paper; All the authors have read and approved the final manuscript. Xu ZL proposed, designed and performed data analysis and prepared the first draft of the manuscript. Qian GX was responsible for patient screening, enrollment, collection of clinical data and radiomics analysis. Both authors have made crucial and indispensable contributions towards the completion of the project and thus qualified as the co-first authors of the paper. Both Cheng Y and Jia WD have played important and indispensable roles in the experimental design, data interpretation and manuscript preparation as the co-corresponding authors.
Supported by Anhui Provincial Key Research and Development Plan, No. 202104j07020048.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of the University of Science and Technology of China (Anhui Provincial Hospital), No. 2021-RE-043.
Informed consent statement: Patients were not required to give informed consent to the study because the study was retrospective.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The data that support our study are not publicly available due to patients’ privacy but are available from the corresponding author upon reasonable request.
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: Wei-Dong Jia, PhD, Doctor, Department of General Surgery, Anhui Provincial Hospital, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Science and Medicine, University of Science and Technology of China, No. 17 Lujiang Road, Hefei 230001, Anhui Province, China. jwd1968@ustc.edu.cn
Received: April 23, 2024
Revised: August 28, 2024
Accepted: September 23, 2024
Published online: December 7, 2024
Processing time: 203 Days and 18.6 Hours
Abstract
BACKGROUND

Microvascular invasion (MVI) is a significant indicator of the aggressive behavior of hepatocellular carcinoma (HCC). Expanding the surgical resection margin and performing anatomical liver resection may improve outcomes in patients with MVI. However, no reliable preoperative method currently exists to predict MVI status or to identify patients at high-risk group (M2).

AIM

To develop and validate models based on contrast-enhanced computed tomography (CECT) radiomics and clinicoradiological factors to predict MVI and identify M2 among patients with hepatitis B virus-related HCC (HBV-HCC). The ultimate goal of the study was to guide surgical decision-making.

METHODS

A total of 270 patients who underwent surgical resection were retrospectively analyzed. The cohort was divided into a training dataset (189 patients) and a validation dataset (81) with a 7:3 ratio. Radiomics features were selected using intra-class correlation coefficient analysis, Pearson or Spearman’s correlation analysis, and the least absolute shrinkage and selection operator algorithm, leading to the construction of radscores from CECT images. Univariate and multivariate analyses identified significant clinicoradiological factors and radscores associated with MVI and M2, which were subsequently incorporated into predictive models. The models’ performance was evaluated using calibration, discrimination, and clinical utility analysis.

RESULTS

Independent risk factors for MVI included non-smooth tumor margins, absence of a peritumoral hypointensity ring, and a high radscore based on delayed-phase CECT images. The MVI prediction model incorporating these factors achieved an area under the curve (AUC) of 0.841 in the training dataset and 0.768 in the validation dataset. The M2 prediction model, which integrated the radscore from the 5 mm peritumoral area in the CECT arterial phase, α-fetoprotein level, enhancing capsule, and aspartate aminotransferase level achieved an AUC of 0.865 in the training dataset and 0.798 in the validation dataset. Calibration and decision curve analyses confirmed the models’ good fit and clinical utility.

CONCLUSION

Multivariable models were constructed by combining clinicoradiological risk factors and radscores to preoperatively predict MVI and identify M2 among patients with HBV-HCC. Further studies are needed to evaluate the practical application of these models in clinical settings.

Keywords: Radiomics; Contrast-enhanced computed tomography; Hepatocellular carcinoma; Microvascular invasion; Hepatitis B virus

Core Tip: Preoperative microvascular invasion (MVI) prediction in patients with hepatocellular carcinoma (HCC) is paramount for guiding surgical decisions. Based on contrast-enhanced computed tomography radiomics and clinicoradiological factors, our models offer valuable predictive capabilities for MVI and high-risk groups among those with hepatitis B virus-related HCC, supporting personalized surgical planning and clinical management.