Retrospective Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jul 7, 2024; 30(25): 3166-3178
Published online Jul 7, 2024. doi: 10.3748/wjg.v30.i25.3166
Predicting hepatocellular carcinoma: A new non-invasive model based on shear wave elastography
Dong Jiang, Yi Qian, Yi-Jun Gu, Ru Wang, Hua Yu, Hui Dong, Dong-Yu Chen, Yan Chen, Hao-Zheng Jiang, Bi-Bo Tan, Min Peng, Yi-Ran Li
Dong Jiang, Yi Qian, Yi-Jun Gu, Ru Wang, Dong-Yu Chen, Yan Chen, Bi-Bo Tan, Yi-Ran Li, Department of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai 200433, China
Hua Yu, Hui Dong, Department of Pathology, Shanghai Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai 200433, China
Hao-Zheng Jiang, Department of College of Art and Science, Case Western Reserve University, Cleveland, OH 44106, United States
Min Peng, Ultrasound Diagnosis, PLA Naval Medical Center, Shanghai 200437, China
Co-first authors: Dong Jiang and Yi Qian.
Co-corresponding authors: Min Peng and Yi-Ran Li.
Author contributions: Li YR, Jiang D, Qian Y, Wang R, Chen DY, and Tan BB designed the research study; Jiang HZ, Gu YJ, Yu H, Peng M, and Dong H performed the research; Chen Y, Qian Y, Wang R, and Jiang HZ contributed new reagents and analytic tools; Jiang D, Li YR, Tan BB, Gu YJ, Peng M, and Yu H analyzed the data and wrote the manuscript; and all authors have read and approved the final manuscript. Jiang D and Qian Y contributed equally to this work as co-first authors; Peng M and Li YR contributed equally to this work as co-corresponding authors. The reasons for designating Peng M and Li YR as co-corresponding authors are that they share the responsibility of guidance, communication, and organization.
Supported by the National Natural Science Foundation of China Youth Training Project, No. 2021GZR003; and Medical-engineering Interdisciplinary Research Youth Training Project, No. 2022YGJC001.
Institutional review board statement: The study was reviewed and approved by the Shanghai Eastern Hepatobiliary Surgery Hospital (Approval No. EHBHKY2023-K034-P001).
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: All the authors have no conflict of interest related to the manuscript.
Data sharing statement: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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: Yi-Ran Li, MD, Attending Doctor, Department of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, No. 225 Changhai Road, Shanghai 200433, China. liyiranehsh@sina.com
Received: March 7, 2024
Revised: May 22, 2024
Accepted: May 27, 2024
Published online: July 7, 2024
Processing time: 115 Days and 23.3 Hours
Abstract
BACKGROUND

Integrating conventional ultrasound features with 2D shear wave elastography (2D-SWE) can potentially enhance preoperative hepatocellular carcinoma (HCC) predictions.

AIM

To develop a 2D-SWE-based predictive model for preoperative identification of HCC.

METHODS

A retrospective analysis of 884 patients who underwent liver resection and pathology evaluation from February 2021 to August 2023 was conducted at the Oriental Hepatobiliary Surgery Hospital. The patients were divided into the modeling group (n = 720) and the control group (n = 164). The study included conventional ultrasound, 2D-SWE, and preoperative laboratory tests. Multiple logistic regression was used to identify independent predictive factors for malignant liver lesions, which were then depicted as nomograms.

RESULTS

In the modeling group analysis, maximal elasticity (Emax) of tumors and their peripheries, platelet count, cirrhosis, and blood flow were independent risk indicators for malignancies. These factors yielded an area under the curve of 0.77 (95% confidence interval: 0.73-0.81) with 84% sensitivity and 61% specificity. The model demonstrated good calibration in both the construction and validation cohorts, as shown by the calibration graph and Hosmer-Lemeshow test (P = 0.683 and P = 0.658, respectively). Additionally, the mean elasticity (Emean) of the tumor periphery was identified as a risk factor for microvascular invasion (MVI) in malignant liver tumors (P = 0.003). Patients receiving antiviral treatment differed significantly in platelet count (P = 0.002), Emax of tumors (P = 0.033), Emean of tumors (P = 0.042), Emax at tumor periphery (P < 0.001), and Emean at tumor periphery (P = 0.003).

CONCLUSION

2D-SWE’s hardness value serves as a valuable marker for enhancing the preoperative diagnosis of malignant liver lesions, correlating significantly with MVI and antiviral treatment efficacy.

Keywords: Shear wave elastography, Predicting model, Microvascular invasion, Antiviral treatment, Hepatocellular carcinoma

Core Tip: This study pioneers a new model utilizing two-dimensional shear wave elastography (2D-SWE) to enhance preoperative diagnosis of hepatocellular carcinoma. This study highlights the prognostic value of 2D-SWE stiffness values in assessing malignant liver lesions in patients with chronic hepatitis B, their microvascular invasion potential, and monitoring the efficacy of antiviral treatments. The predictive map validated by receiver operating characteristic analysis provides a promising tool for clinicians in the management of liver cancer and represents an important step forward in precision oncology.