Clinical Application of Shear Wave Elastography With Shear Wave Dispersion Imaging in the Preoperative Evaluation of Hepatic Parenchyma in Patients With Liver Tumors

Ultrasonic surface acoustic wave elastography: A review of basic theories, technical developments, and medical applications

Physiological and pathological changes in tissues often cause changes in tissue mechanical properties, making tissue elastography an effective modality in medical imaging. Among the existing elastography methods, ultrasound elastography is of great interest due to the inherent advantages of ultrasound imaging technology, such as low cost, portability, safety, and wide availability. However, most current ultrasound elastography methods are based on the bulk shear wave; they can image deep tissues but cannot image superficial tissues. To address this challenge, ultrasonic elastography methods based on surface acoustic waves have been proposed. In this paper, we present a comprehensive review of ultrasound-based surface acoustic wave elastography techniques, including their theoretical foundations, technical implementations, and existing medical applications. The goal is to provide a concise summary of the state-of-the-art of this field, hoping to offer a reliable reference for the further development of these techniques and foster the expansion of their medical applications.

Shear Wave Dispersion in Chronic Liver Disease: From Physical Principles to Clinical Usefulness

The development of new applications in ultrasound (US) imaging in recent years has strengthened the role of this imaging technique in the management of different pathologies, particularly in the setting of liver disease. Improved B-mode imaging (3D and 4D), contrast-enhanced US (CEUS) and especially US-based elastography techniques have created the concept of multiparametric ultrasound (MP-US), a term borrowed from radiological sectional imaging. Among the new elastography techniques, shear wave dispersion is a newly developed imaging technology which enables the assessment of the shear waves' dispersion slope. The analysis of the dispersion qualities of shear waves might be indirectly related to the tissue viscosity, thus providing biomechanical information concerning the pathologic state of the liver such as necroinflammation. Some of the most recent US devices have been embedded with software that evaluate the dispersion of shear waves/liver viscosity. In this review, the feasibility and the clinical applications of liver viscosity are reviewed based on the preliminary findings of both animal and human studies.

Shear Wave Dispersion Slope Measured with Shear Wave Dispersion Imaging Is Associated with Variceal Hemorrhage in Cirrhotic Patients

Background and Objectives: Portal hypertension (PH), as the main consequence of cirrhosis, leads to the development of gastroesophageal varices (GEVs). Variceal hemorrhage (VH) caused by the rupture of GEVs is a life-threatening emergency. Thus, the prediction of VH risk is considerably important. Our pilot study aimed to identify the risk factors of variceal hemorrhage (VH) in cirrhosis. Materials and Methods: Cirrhotic patients were prospectively included and divided into two groups according to the presence or absence of VH. Conventional ultrasound and shear wave dispersion (SWD) imaging were conducted to detect the portal vein diameter, spleen diameter, ascites, liver stiffness (LS) and shear wave dispersion slope (SWDS). The laboratory tests were recorded, including platelets (PLT), alanine transaminase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL) and albumin (ALB). The risk factors of VH were screened using univariate analyses and identified using multivariate logistic regression. The ROC curves were used to assess diagnostic accuracy. Comparisons between AUCs were performed using the Delong method. Results: Sixty-five patients with 22 VHs were finally included. The SWDS, spleen diameter and ascites were identified as independent risk factors for VH. The SWDS showed good performance for diagnosing VH (AUC = 0.768, 95% CI: 0.647−0.864), and sensitively identified 95.5% (95% CI: 77.2%−99.9%) of patients with VH. Including the three risk factors in multivariate logistic regression, we obtained a formula for diagnosing VH: −20.749 + 0.804 × SWDS + 0.449 × spleen diameter + 1.803 × ascites (no ascites = 0, ascites = 1). Comparison of AUCs revealed that the formula (AUC = 0.900, 95% CI: 0.800−0.961) performed better than LS, SWDS, and spleen diameter in diagnosing VH (p < 0.001; p < 0.05; p < 0.05). Conclusions: SWDS is a sensitive parameter for assessing the risk of VH. Combining the SWDS, spleen diameter and ascites resulted in good diagnostic accuracy.