Observational Study
Copyright ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. May 26, 2019; 7(10): 1122-1132
Published online May 26, 2019. doi: 10.12998/wjcc.v7.i10.1122
Diagnostic value of two dimensional shear wave elastography combined with texture analysis in early liver fibrosis
Zhao-Cheng Jian, Jin-Feng Long, Yu-Jiang Liu, Xiang-Dong Hu, Ji-Bin Liu, Xian-Quan Shi, Wei-Sheng Li, Lin-Xue Qian
Zhao-Cheng Jian, Yu-Jiang Liu, Xiang-Dong Hu, Xian-Quan Shi, Wei-Sheng Li, Lin-Xue Qian, Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
Zhao-Cheng Jian, Jin-Feng Long, Medical Imaging Center, Affiliated Hospital of Weifang Medical University, Weifang 261031, Shandong Province, China
Ji-Bin Liu, Institute of Ultrasound, Thomas Jefferson University Hospital, Philadelphia, PA 19107, United States
Author contributions: All authors helped to perform the research; Jian ZC manuscript writing, performing procedures and data analysis; Long JF contribution to writing the manuscript, performing experiments, and data analysis; Liu YJ and Hu XD contribution to performing experiments; Liu JB contribution to writing the manuscript; Shi XQ and Li WS contribution to data analysis; Qian LX manuscript writing, drafting conception and design, performing experiments, and data analysis.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of Beijing Friendship Hospital, Capital Medical University.
Informed consent statement: Patient's informed consent was obtained before the study,though the clinical data used in this study were anonymous.
Conflict-of-interest statement: All authors declare no conflicts-of-interest related to this article.
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 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/
Corresponding author: Lin-Xue Qian, MD, Chief Doctor, Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, Xicheng District, Beijing 100050, China. qianlinxue2002@163.com
Telephone: +86-13562645007 Fax: +86-10-63138576
Received: February 2, 2019
Peer-review started: February 2, 2019
First decision: March 10, 2019
Revised: March 19, 2019
Accepted: April 8, 2019
Article in press: April 9, 2019
Published online: May 26, 2019
Abstract
BACKGROUND

Staging diagnosis of liver fibrosis is a prerequisite for timely diagnosis and therapy in patients with chronic hepatitis B. In recent years, ultrasound elastography has become an important method for clinical noninvasive assessment of liver fibrosis stage, but its diagnostic value for early liver fibrosis still needs to be further improved. In this study, the texture analysis was carried out on the basis of two dimensional shear wave elastography (2D-SWE), and the feasibility of 2D-SWE plus texture analysis in the diagnosis of early liver fibrosis was discussed.

AIM

To assess the diagnostic value of 2D-SWE combined with textural analysis in liver fibrosis staging.

METHODS

This study recruited 46 patients with chronic hepatitis B. Patients underwent 2D-SWE and texture analysis; Young's modulus values and textural patterns were obtained, respectively. Textural pattern was analyzed with regard to contrast, correlation, angular second moment (ASM), and homogeneity. Pathological results of biopsy specimens were the gold standard; comparison and assessment of the diagnosis efficiency were conducted for 2D-SWE, texture analysis and their combination.

RESULTS

2D-SWE displayed diagnosis efficiency in early fibrosis, significant fibrosis, severe fibrosis, and early cirrhosis (AUC > 0.7, P < 0.05) with respective AUC values of 0.823 (0.678-0.921), 0.808 (0.662-0.911), 0.920 (0.798-0.980), and 0.855 (0.716-0.943). Contrast and homogeneity displayed independent diagnosis efficiency in liver fibrosis stage (AUC > 0.7, P < 0.05), whereas correlation and ASM showed limited values. AUC of contrast and homogeneity were respectively 0.906 (0.779-0.973), 0.835 (0.693-0.930), 0.807 (0.660-0.910) and 0.925 (0.805-0.983), 0.789 (0.639-0.897), 0.736 (0.582-0.858), 0.705 (0.549-0.883) and 0.798 (0.650-0.904) in four liver fibrosis stages, which exhibited equivalence to 2D-SWE in diagnostic efficiency (P > 0.05). Combined diagnosis (PRE) displayed diagnostic efficiency (AUC > 0.7, P < 0.01) for all fibrosis stages with respective AUC of 0.952 (0.841-0.994), 0.896 (0.766-0.967), 0.978 (0.881-0.999), 0.947 (0.835-0.992). The combined diagnosis showed higher diagnosis efficiency over 2D-SWE in early liver fibrosis (P < 0.05), whereas no significant differences were observed in other comparisons (P > 0.05).

CONCLUSION

Texture analysis was capable of diagnosing liver fibrosis stage, combined diagnosis had obvious advantages in early liver fibrosis, liver fibrosis stage might be related to the hepatic tissue hardness distribution.

Keywords: Elastography, Two-dimensional shear wave, Texture analysis, Liver fibrosis, Staging

Core tip: This study explored the diagnostic value of texture analysis in early liver fibrosis in patients with chronic hepatitis B on the basis of two dimensional shear wave elastography. It demonstrated that texture analysis was capable of diagnosing liver fibrosis, combined diagnosis had obvious advantages in early liver fibrosis, and the liver fibrosis stage might be related to the spatial heterogeneity of hepatic tissue hardness distribution.