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Model for liver hardness using two-dimensional shear wave elastography, durometer, and preoperative biomarkers.
Bing-Jie Ju1, Ming Jin1, Yang Tian1
1Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, Zhejiang Province, China.
World Journal of Gastrointestinal Surgery
|March 1, 2021
Summary
This study shows that liver stiffness measured by 2D-SWE and surgeon palpation accurately predicts liver hardness and post-hepatectomy liver failure (PHLF) risk. A new hardness scale model improves PHLF prediction in liver resection patients.
Area of Science:
- Hepatobiliary surgery
- Liver disease diagnostics
- Medical device technology
Background:
- Post-hepatectomy liver failure (PHLF) is a significant risk for patients undergoing liver resection, especially those with advanced liver fibrosis or cirrhosis.
- Preoperative liver stiffness assessment using two-dimensional shear wave elastography (2D-SWE) is common but lacks accuracy.
- Durometers offer objective hardness measurement but are only usable during surgery.
Purpose of the Study:
- To correlate two-dimensional shear wave elastography (2D-SWE) and surgeon palpation with objective durometer-measured liver hardness.
- To develop a regression model for predicting liver hardness and post-hepatectomy liver failure (PHLF).
Main Methods:
- A derivation cohort of 74 hepatectomy patients had liver hardness assessed via surgeon palpation and durometer.
- Multiple linear regression models were built to predict durometer hardness, using preoperative parameters.
- Receiver operating characteristic (ROC) curves and survival analyses evaluated the model's PHLF prediction accuracy in a validation cohort (n=162).
Main Results:
- 2D-SWE and palpation scores showed strong linear correlations with durometer-measured hardness (r=0.704 and r=0.729, respectively; P < 0.001).
- A predictive model incorporating stiffness, HBsAg, and albumin achieved R²=0.580 for durometer hardness.
- The developed hardness scale model demonstrated good predictive performance for PHLF (AUC=0.785), with scores >27.87 indicating significantly higher risk (HR=7.835).
Conclusions:
- Liver stiffness measurements by 2D-SWE and surgeon palpation correlate well with objective durometer hardness.
- A novel multiple linear regression model effectively predicts liver hardness and identifies patients at high risk for PHLF.
- The validated model offers a promising tool for improving preoperative risk assessment in liver resection.
