Abstract
Biliary atresia is an aggressive liver disease of infancy and can cause death without timely surgical intervention. Early diagnosis of biliary atresia is critical to the recovery of bile drainage and long-term transplant-free survival. Ultrasound is recommended as the initial imaging strategy for the diagnosis of biliary atresia. Numerous ultrasound features have been proved helpful for the diagnosis of biliary atresia. In recent years, with the help of new technologies such as elastography ultrasound, contrast-enhanced ultrasound and artificial intelligence, the diagnostic performance of ultrasound has been significantly improved. In this review, various ultrasound features in the diagnosis of biliary atresia are summarized. A diagnostic decision flow chart for biliary atresia is proposed on the basis of the hybrid technologies, combining conventional ultrasound, elastography and contrast-enhanced ultrasound. In addition, the application of artificial intelligence in the diagnosis of biliary atresia with ultrasound images is also introduced.
Highlights
Biliary atresia (BA) is a severe obliterative fibrosing cholangiopathy of infancy, with a worldwide prevalence ranging from 1 in 5000 to 19,000 livebirths [1,2,3]
To overcome the shortcomings of the already existed triangular cord (TC) thickness, we proposed a modified TC thickness, which was defined as the thickness of the echogenic anterior wall of the anterior branch of the right portal vein just distal to the right portal vein on a longitudinal image (Figure 2c), without including the right hepatic artery (HA) [20]
Chen et al [55]. proposed an algorithm with risk stratification to distinguish BA, which was composed of five predictors: shear wave speed, TC sign, GGT, gallbladder abnormalities and clay stool. This algorithm showed promising results with an AUC of 0.983. These findings indicate that the combination of elastography, US features and clinical data can obtain a better predictive value for the diagnosis of BA than that yielded by using elastography alone [54,55]
Summary
Biliary atresia (BA) is a severe obliterative fibrosing cholangiopathy of infancy, with a worldwide prevalence ranging from 1 in 5000 to 19,000 livebirths [1,2,3]. The clinical symptoms of infants with BA mainly include persistent jaundice, pale stools and dark urine shortly after birth [4] Such clinical symptoms are caused by cholestasis, which is characterized of conjugated hyperbilirubinemia Hepatobiliary scintigraphy can be used for the assessment of the patency of the bile duct by observing the excretion of the tracer into the small intestine, but the specificity was as low as 70.4% [11]. It is time-consuming and radiation-active [12]. The application of artificial intelligence (AI) in the diagnosis of BA with US images is introduced
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