Predicting hepatocellular carcinoma: A new non-invasive model based on shear wave elastography

Area of Science:

• Hepatobiliary Surgery
• Medical Imaging
• Oncology

Background:

• Conventional ultrasound and 2D shear wave elastography (2D-SWE) integration may improve preoperative hepatocellular carcinoma (HCC) prediction.
• Accurate preoperative assessment of liver lesions is crucial for effective treatment planning.

Purpose of the Study:

• To develop and validate a predictive model for preoperative identification of malignant liver lesions using 2D-SWE.
• To assess the correlation of 2D-SWE parameters with microvascular invasion (MVI) and treatment efficacy.

Main Methods:

• Retrospective analysis of 884 patients undergoing liver resection.
• Inclusion of conventional ultrasound, 2D-SWE, and laboratory test data.
• Development of a predictive model using multiple logistic regression and nomograms.

Main Results:

• Maximal elasticity (Emax) of tumors and peripheries, platelet count, cirrhosis, and blood flow were independent predictors of malignancy (AUC 0.77).
• Mean elasticity (Emean) of the tumor periphery predicted microvascular invasion (MVI).
• 2D-SWE parameters showed significant differences in patients receiving antiviral treatment.

Conclusions:

• 2D-SWE hardness values are valuable markers for preoperative diagnosis of malignant liver lesions.
• The developed model enhances diagnostic accuracy and provides insights into MVI and treatment response.