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Early Prediction of Biliary Atresia Using Combi-Elastography in Infants ≤ 60 Days of Age
Fenglin Xu1, Chenpeng Zheng1, Caihui Hu1
1Department of Ultrasound Children's Hospital of Chongqing Medical University, National Clinical Research Center for Children and Adolescents' Health and Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Municipal Health Commission Key Laboratory of Children's Vital Organ Development and Diseases, Chongqing 400014, China.
Insights
A new nomogram model integrating combi-elastography and GGT levels can help differentiate biliary atresia (BA) from other infant cholestatic liver diseases. This tool shows promise for early BA recognition and timely treatment.
Area of Science:
- Pediatric Gastroenterology
- Medical Imaging
- Diagnostic Biomarkers
Background:
- Biliary atresia (BA) requires early diagnosis for effective treatment.
- Distinguishing BA from other neonatal cholestatic conditions is challenging.
- Novel imaging techniques are needed to improve diagnostic accuracy.
Purpose of the Study:
- To develop and validate a predictive model for early biliary atresia (BA) detection.
- To integrate combi-elastography with laboratory markers for improved diagnostic performance.
- To differentiate BA from non-BA cholestatic liver diseases in infants.
Main Methods:
- Retrospective enrollment of 69 infants (<60 days) with cholestatic hepatitis.
- Application of conventional ultrasonography, combi-elastography, and laboratory tests.
- Logistic regression analysis to construct a nomogram model using GGT, gallbladder morphology, and combi-elastography fibrosis index.
Main Results:
- GGT, gallbladder morphology, and combi-elastography fibrosis index were significant predictors (p<0.05).
- The nomogram achieved an AUC of 0.887, with 86.4% sensitivity and 76.0% specificity.
- Internal validation confirmed the model's reliable predictive performance for identifying BA.
Conclusions:
- A nomogram integrating combi-elastography and liver function indices effectively predicts biliary atresia risk.
- This model offers significant clinical value for early BA diagnosis in infants.
- Combi-elastography shows promise as a tool to improve BA recognition.
Abstract:
Background: To improve the early recognition of biliary atresia (BA) and timely treatment, this study developed a predictive model integrating combi-elastography, a novel form of elastography, to distinguish biliary atresia from other cholestatic liver diseases (non-BA) in infants. Method: A total of 69 children aged < 60 days with cholestatic hepatitis were retrospectively enrolled. All patients underwent conventional ultrasonography, combi-elastography, and laboratory testing. The variables were selected using logistic regression to construct a nomogram model, and the performance of the model was evaluated. Results: Multifactorial logistic regression analysis indicated that GGT (p = 0.015), the gallbladder morphology (p = 0.017), and the fibrosis index of the combi-elastography (p = 0.017) could be used as independent predictors to differentiate BA from other causes of cholestasis. A nomogram model constructed with these three indexes showed better performance, with an area under the operating characteristic curve (AUC) of 0.887 (0.823, 0.952) (p < 0.001), sensitivity of 86.4%, and specificity of 76.0%. Using 1000 Bootstrap resamples for internal validation of the model, the predictive effect of the nomogram model to identify biliary atresia from other cholestatic liver diseases was in good agreement with the actual situation. Decision-curve analysis showed that the use of the nomogram model to predict biliary atresia gained more clinical value at a risk threshold of 0.10-0.80. Conclusion: The nomogram constructed integrating combi-elastography and liver function indices shows promising value for predicting the risk for developing biliary atresia.
