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©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Feb 27, 2021; 13(2): 127-140
Published online Feb 27, 2021. doi: 10.4240/wjgs.v13.i2.127
Model for liver hardness using two-dimensional shear wave elastography, durometer, and preoperative biomarkers
Bing-Jie Ju, Ming Jin, Yang Tian, Xiang Zhen, De-Xing Kong, Wei-Lin Wang, Sheng Yan
Bing-Jie Ju, Ming Jin, Yang Tian, Xiang Zhen, De-Xing Kong, Wei-Lin Wang, Sheng Yan, Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, Zhejiang Province, China
Bing-Jie Ju, Ming Jin, Yang Tian, Xiang Zhen, Wei-Lin Wang, Sheng Yan, Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou 310009, Zhejiang Province, China
Bing-Jie Ju, Ming Jin, Yang Tian, Xiang Zhen, Wei-Lin Wang, Sheng Yan, Research Center of Diagnosis and Treatment Technology for Hepatocellular Carcinoma of Zhejiang Province, Hangzhou 310009, Zhejiang Province, China
Bing-Jie Ju, Ming Jin, Yang Tian, Xiang Zhen, Wei-Lin Wang, Sheng Yan, Clinical Medicine Innovation Center of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Disease of Zhejiang University, Hangzhou 310009, Zhejiang Province, China
Bing-Jie Ju, Ming Jin, Yang Tian, Xiang Zhen, Wei-Lin Wang, Sheng Yan, Clinical Research Center of Hepatobiliary and Pancreatic Diseases of Zhejiang Province, Hangzhou 310009, Zhejiang Province, China
De-Xing Kong, School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, Zhejiang Province, China
Author contributions: Ju BJ and Tian Y reviewed the literature; Ju BJ, Jin M, Tian Y, and Zheng X collected patient data; Ju BJ analyzed all data and wrote the paper under the supervision of Kong DX, Wang WL and Yan S; All authors approved the final version of the manuscript.
Supported by National Natural Science Foundation of China, No. 81372626; Key Research and Development Project of Science and Technology Department of Zhejiang, China, No. 2015C03053; and Zhejiang Provincial Program for the Cultivation of High-level Innovative Health Talents.
Institutional review board statement: The study was reviewed and approved by the Institutional Review Board at the Second Affiliated Hospital, Zhejiang University School of Medicine.
Informed consent statement: The requirement for informed consent was waived by the Institutional Review Board.
Conflict-of-interest statement: All authors are free from any economical or personal interest this paper may cause. There is no conflict of interest to report for any of the authors.
Data sharing statement: Dataset available from the corresponding author at shengyan@zju.edu.cn. Informed consent was not obtained but the presented data are anonymized and risk of identification is low. No additional data are available.
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:
http://creativecommons.org/Licenses/by-nc/4.0/ Corresponding author: Sheng Yan, MD, Professor, Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, No. 88 Jiefang Road, Hangzhou 310009, Zhejiang Province, China. shengyan@zju.edu.cn
Received: August 27, 2020
Peer-review started: August 27, 2020
First decision: November 4, 2020
Revised: November 27, 2020
Accepted: December 16, 2020
Article in press: December 16, 2020
Published online: February 27, 2021
BACKGROUND
Post-hepatectomy liver failure (PHLF) increases morbidity and mortality after liver resection for patients with advanced liver fibrosis and cirrhosis. Preoperative liver stiffness using two-dimensional shear wave elastography (2D-SWE) is widely used to evaluate the degree of fibrosis. However, the 2D-SWE results were not accurate. A durometer measures hardness by quantifying the ability of a material to locally resist the intrusion of hard objects into its surface. However, the durometer score can only be obtained during surgery.
AIM
To measure correlations among 2D-SWE, palpation by surgeons, and durometer-measured objective liver hardness and to construct a liver hardness regression model.
METHODS
We enrolled 74 hepatectomy patients with liver hardness in a derivation cohort. Tactile-based liver hardness scores (0-100) were determined through palpation of the liver tissue by surgeons. Additionally, liver hardness was measured using a durometer. Correlation coefficients for durometer-measured hardness and preoperative parameters were calculated. Multiple linear regression models were constructed to select the best predictive durometer scale. Receiver operating characteristic (ROC) curves and univariate and multivariate analyses were used to calculate the best model’s prediction of PHLF and risk factors for PHLF, respectively. A separate validation cohort (n = 162) was used to evaluate the model.
RESULTS
The stiffness measured using 2D-SWE and palpation scale had good linear correlation with durometer-measured hardness (Pearson rank correlation coefficient 0.704 and 0.729, respectively, P < 0.001). The best model for the durometer scale (hardness scale model) was based on stiffness, hepatitis B virus surface antigen, and albumin level and had an R2 value of 0.580. The area under the ROC for the durometer and hardness scale for PHLF prediction were 0.807 (P = 0.002) and 0.785 (P = 0.005), respectively. The optimal cutoff value of the durometer and hardness scale was 27.38 (sensitivity = 0.900, specificity = 0.660) and 27.87 (sensitivity = 0.700, specificity = 0.787), respectively. Patients with a hardness scale score of > 27.87 were at a significantly higher risk of PHLF with hazard ratios of 7.835 (P = 0.015). The model’s PHLF predictive ability was confirmed in the validation cohort.
CONCLUSION
Liver stiffness assessed by 2D-SWE and palpation correlated well with durometer hardness values. The multiple linear regression model predicted durometer hardness values and PHLF.
Core Tip: In this study, we developed a linear regression model to predict liver hardness and found that surgeons’ subjective palpation scores were comparable with durometer measures of liver hardness. The hardness model had a good ability to predict post-hepatectomy liver failure.
