The utility of shear wave elastography and serum biomarkers for diagnosing biliary atresia and predicting clinical outcomes

Liu, Yakun; Peng, Chunhui; Wang, Kai; Wu, Dongyang; Yan, Jun; Tu, Wen‐Jun; Chen, Yajun

doi:10.1007/s00431-021-04176-y

Cited by 16 publications

(25 citation statements)

References 32 publications

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“…These findings are reasonable since they reflect liver conditions, either directly in terms of the liver structure by US stiffness or indirectly by TB and DB reflecting liver function. These observations are concordant and confirm previous experiences in which a predictive role of serum bilirubin levels and US liver stiffness has been suggested in patients with BA treated with KP during early and long-term follow-up [ 19 , 40 , 41 , 42 , 43 , 44 ]. In particular, among the used ML algorithms, the RF algorithm was the best either for laboratory or for US parameters, while SVM and kNN algorithms were the best according to MR parameters.…”

Section: Discussionsupporting

confidence: 91%

Machine Learning Evaluation of Biliary Atresia Patients to Predict Long-Term Outcome after the Kasai Procedure

et al. 2021

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Kasai portoenterostomy (KP) represents the first-line treatment for biliary atresia (BA). The purpose was to compare the accuracy of quantitative parameters extracted from laboratory tests, US imaging, and MR imaging studies using machine learning (ML) algorithms to predict the long-term medical outcome in native liver survivor BA patients after KP. Twenty-four patients were evaluated according to clinical and laboratory data at initial evaluation (median follow-up = 9.7 years) after KP as having ideal (n = 15) or non-ideal (n = 9) medical outcomes. Patients were re-evaluated after an additional 4 years and classified in group 1 (n = 12) as stable and group 2 (n = 12) as non-stable in the disease course. Laboratory and quantitative imaging parameters were merged to test ML algorithms. Total and direct bilirubin (TB and DB), as laboratory parameters, and US stiffness, as an imaging parameter, were the only statistically significant parameters between the groups. The best algorithm in terms of accuracy, sensitivity, specificity, and AUCROC was naive Bayes algorithm, selecting only laboratory parameters (TB and DB). This preliminary ML analysis confirms the fundamental role of TB and DB values in predicting the long-term medical outcome for BA patients after KP, even though their values may be within the normal range. Physicians should be alert when TB and DB values change slightly.

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Section: Discussionsupporting

confidence: 91%

Machine Learning Evaluation of Biliary Atresia Patients to Predict Long-Term Outcome after the Kasai Procedure

et al. 2021

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“…Hwang et al (12) reported that TC thickening was only present in 17% of infants with BA younger than 30 days. Interestingly, they (12) is reported to have a higher diagnostic performance in older BA infants (aged older than 60 days), and LSM is highly positively correlated with age in infants with BA (16,25).…”

Section: Discussionmentioning

confidence: 98%

A novel prediction tool based on shear wave elastography, gallbladder ultrasound, and serum biomarkers for the early diagnosis of biliary atresia in infants younger than 60 days old

Yan¹,

Liu²,

Jin³

et al. 2023

Quant Imaging Med Surg

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Background: Early Kasai surgery before 60 days of life results in better clinical outcomes in patients with biliary atresia (BA). We aimed to develop and validate a prediction tool for the early diagnosis of BA in infants younger than 60 days old.Methods: This prospective study recruited consecutive infants younger than 60 days old with conjugated hyperbilirubinemia who were evaluated with an ultrasound (US) scan, including B-mode US with color Doppler flow imaging (CDFI) features and liver two-dimensional shear wave elastography (2D SWE), from March 2017 to July 2021. The reference standard for diagnosis was intraoperative cholangiography, liver biopsy, or the resolution of jaundice. Area under the receiver operating characteristic curve (AUC) analysis, logistic regression analysis, and establishment of a nomogram were performed.Results: A total of 174 patients (mean age, 46 days), including 87 infants with BA and 87 non-BA cholestatic infants, were included in the study. The established nomogram based on gallbladder (GB) abnormality, liver 2D SWE, and serum γ-glutamyl transferase (GGT) and alanine aminotransferase (ALT) had an AUC of 0.99 (95% CI: 0.94-1.00), a sensitivity of 92%, and a specificity of 100%. The nomogram in the validation cohort also had good diagnostic performance in the diagnosis of BA, with an AUC of 0.98 (95% CI: 0.95-1.00). Conclusions:The new prediction tool had a good diagnostic performance in the early prediction of BA in infants younger than 60 days old and will facilitate timely Kasai surgery.

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“…DB and ALB are factors reflecting the excretory and synthetic functions of liver; the results indicate that only patients with excellent comprehensive liver functions can survive with their native liver. Some studies have been reported about predicting NLS for infants after KPE, most focused on factors before jaundice resolution, and some are not routine parameters, [9][10][11][12][13][14][15] the predictive values are not certain.…”

Section: Kpe Remains the First Surgical Choice For Biliary Atresia Co...mentioning

confidence: 99%

Predicting the outcomes of Kasai portoenterostomy for biliary atresia: a cohort study

Qiao

Yan

et al. 2022

Preprint

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Objectives: To identify factors associated with outcomes of Kasai portoenterostomy (KPE), and predictors of 2- and 5- year native liver survival (NLS) for infants achieved jaundice clearance (JC) within 6 months of KPE. Methods: This retrospective cohort study was conducted on 151 patients with type III biliary atresia (BA) who underwent KPE at our center. Univariate analysis and logistic regression analyses were performed to identify factors associated with NLS in infants achieved JC. Kaplan-Meier curves and log-rank tests were used to estimate the NLS, and the Cox proportional hazards regression model identified variables most associated with 2- and 5- year NLS at 6 months post-KPE. A receiver operating characteristic (ROC) curve was used to evaluate the predictive value of these factors. Results: The 2- and 5- year NLS of infants achieved JC at 3 months post-KPE were not different from those achieved JC earlier. Operation age and total bile acid (TBA) were factors associated with JC. For infants who have achieved JC, DB was the only factor associated with 2-year NLS, the AUC was 0.872, the cutoff value was 14 μmol/L; ALB and DB were factors associated with 5-year NLS, the AUCs were 0.894 and 0.95, and the cutoff values were 39 g/L and 14 μmol/L, respectively. Conclusions: NLS should be estimated at 6 months post-KPE. Preoperative factors are not predictive of NLS. For infants cleared jaundice, DB and ALB can predict NLS with good performance.

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The utility of shear wave elastography and serum biomarkers for diagnosing biliary atresia and predicting clinical outcomes

Cited by 16 publications

References 32 publications

Machine Learning Evaluation of Biliary Atresia Patients to Predict Long-Term Outcome after the Kasai Procedure

Machine Learning Evaluation of Biliary Atresia Patients to Predict Long-Term Outcome after the Kasai Procedure

A novel prediction tool based on shear wave elastography, gallbladder ultrasound, and serum biomarkers for the early diagnosis of biliary atresia in infants younger than 60 days old

Predicting the outcomes of Kasai portoenterostomy for biliary atresia: a cohort study

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