Published online Feb 27, 2021. doi: 10.4240/wjgs.v13.i2.127
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
Processing time: 161 Days and 4.8 Hours
Preoperative noninvasive measurement of liver stiffness using shear wave elastography (SWE) is widely used to evaluate the degree of fibrosis. The SWE measurement involves applying a time-varying force to the tissue, and liver tissue with increased stiffness is considered harder, indicating severe fibrosis. Some studies reported that SWE predicted high-grade post-hepatectomy liver failure (PHF).
The results of the two-dimensional SWE are not a good representation of the actual hardness of the liver. Predicting liver hardness before surgery can prompt the surgeon to prepare for surgical practice.
This study aimed to construct a preoperative liver hardness model.
Correlation coefficients for durometer-measured hardness and preoperative parameters were calculated. Multiple linear regression models were constructed to select the best predictive durometer scale.
In the present 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 PHF.
Liver stiffness assessed by two-dimensional shear wave elastography correlated well with durometer hardness values. The multiple linear regression model predicted durometer hardness values and post-hepatectomy liver failure.
The ultimate goal should be to combine three-dimensional printing technology to build a model that works in both touch and vision to guide surgical planning and drill surgery procedure with the spirit of accuracy medicine and enhanced recovery after surgery.