Diagnostic performance of two-dimensional shear wave elastography and attenuation imaging for fibrosis and steatosis assessment in chronic liver disease.

Purpose: We investigated the diagnostic performance of two-dimensional shear wave elastography (2D-SWE) and attenuation imaging (ATI) in detecting fibrosis and steatosis in patients with chronic liver disease (CLD), comparing them with established methods.

Methods: In 190 patients with CLD, 2D-SWE and vibration-controlled transient elastography (VCTE) were used for liver stiffness measurement (LSM), and ATI and controlled attenuation parameter (CAP) were used for steatosis quantification. The correlations between these new and established methods were analyzed.

Development of novel deep multimodal representation learning-based model for the differentiation of liver tumors on B-mode ultrasound images.

Background And Aim: Recently, multimodal representation learning for images and other information such as numbers or language has gained much attention. The aim of the current study was to analyze the diagnostic performance of deep multimodal representation model-based integration of tumor image, patient background, and blood biomarkers for the differentiation of liver tumors observed using B-mode ultrasonography (US).

Method: First, we applied supervised learning with a convolutional neural network (CNN) to 972 liver nodules in the training and development sets to develop a predictive model using segmented B-mode tumor images.

Utility of hepatic vein waveform and transient elastography in patients with Budd-Chiari syndrome who require angioplasty: Two case reports.

Rationale: Budd-Chiari syndrome (BCS), which causes congestive hepatopathy and aggravates cirrhosis, is typically treated by interventional angioplasty to ameliorate blood flow. X-ray venography is useful for the evaluation of inferior vena cava (IVC) stenosis and determination of treatment timing, but it is invasive and thus unsuitable for repeated examinations. The development of a simple method for the prediction of IVC stenosis would reduce the burden on patients with BCS.

A Novel Non-invasive Method for Predicting Liver Fibrosis by Quantifying the Hepatic Vein Waveform.

The hepatic vein (HV) waveform by Doppler ultrasound reflects the severity of liver fibrosis. We conducted a proof-of-concept study of a new method for quantifying the HV waveform. We calculated the coefficient of variation (CV) of the HV flow velocity and created a new index "q-HV" (quantified HV) and analyzed its performance for predicting histologic liver fibrosis in 114 patients with chronic liver disease.

Liver stiffness measurements in chronic hepatitis C: Treatment evaluation and risk assessment.

Background And Aim: Liver stiffness (LS), measured by transient elastography, has been validated as a non-invasive surrogate for liver fibrosis.

Methods: We investigated the long-term predictive ability of LS for hepatocellular carcinoma (HCC) development and overall survival in 1146 patients with chronic hepatitis C by using LS value at enrollment. We also investigated chronological changes in LS based on antiviral therapy and its outcome in 752 patients.