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Ultrasonographic Diagnosis of Biliary Atresia Based on a Decision-Making Tree Model.

Lee SM, Cheon JE, Choi YH, Kim WS, Cho HH, Kim IO, You SK - Korean J Radiol (2015)

Bottom Line: Logistic regression analyses were performed to determine the features that would be useful in predicting BA.Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups.Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively).

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Seoul National University College of Medicine, Seoul 03080, Korea.

ABSTRACT

Objective: To assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA).

Materials and methods: From March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups.

Results: Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100).

Conclusion: Abnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology.

No MeSH data available.


Related in: MedlinePlus

62-day-old female infant with neonatal hepatitis.In conditional inference tree analysis, this patient was incorrectly classified into node 5 owing to abnormal gallbladder morphology. A. Gallbladder (arrow) has irregular contour with lack of complete echogenic mucosal lining. Gallbladder length is 3.1 mm. B. Triangular cord thickness (arrowheads) is 2.5 mm. This is regarded as negative triangular cord sign.
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Figure 3: 62-day-old female infant with neonatal hepatitis.In conditional inference tree analysis, this patient was incorrectly classified into node 5 owing to abnormal gallbladder morphology. A. Gallbladder (arrow) has irregular contour with lack of complete echogenic mucosal lining. Gallbladder length is 3.1 mm. B. Triangular cord thickness (arrowheads) is 2.5 mm. This is regarded as negative triangular cord sign.

Mentions: In the conditional inference tree analysis, the two US findings (gallbladder morphology and triangular cord thickness) were identified as significant predictors of the presence or absence of BA (p < 0.001) (Fig. 1). The first split of the tree was made according to the gallbladder morphology. Abnormal gallbladder morphology-regardless of triangular cord thickness-led to node 5, which had 39 (92.9%) patients with BA and 3 (7.1%) patients without BA (Figs. 2, 3). In the other branch, which showed normal gallbladder morphology, the next division was based on the triangular cord thickness. The optimal cutoff value of triangular cord thickness for a diagnosis of BA was automatically selected as 3.4 mm by the statistical method. Normal gallbladder morphology with triangular cord thickness > 3.4 mm led to node 4. All 7 cases in node 4 had BA (Fig. 4). The remaining 51 cases with normal gallbladder morphology and triangular cord thickness ≤ 3.4 mm reached node 3, in which no patients had BA.


Ultrasonographic Diagnosis of Biliary Atresia Based on a Decision-Making Tree Model.

Lee SM, Cheon JE, Choi YH, Kim WS, Cho HH, Kim IO, You SK - Korean J Radiol (2015)

62-day-old female infant with neonatal hepatitis.In conditional inference tree analysis, this patient was incorrectly classified into node 5 owing to abnormal gallbladder morphology. A. Gallbladder (arrow) has irregular contour with lack of complete echogenic mucosal lining. Gallbladder length is 3.1 mm. B. Triangular cord thickness (arrowheads) is 2.5 mm. This is regarded as negative triangular cord sign.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4644760&req=5

Figure 3: 62-day-old female infant with neonatal hepatitis.In conditional inference tree analysis, this patient was incorrectly classified into node 5 owing to abnormal gallbladder morphology. A. Gallbladder (arrow) has irregular contour with lack of complete echogenic mucosal lining. Gallbladder length is 3.1 mm. B. Triangular cord thickness (arrowheads) is 2.5 mm. This is regarded as negative triangular cord sign.
Mentions: In the conditional inference tree analysis, the two US findings (gallbladder morphology and triangular cord thickness) were identified as significant predictors of the presence or absence of BA (p < 0.001) (Fig. 1). The first split of the tree was made according to the gallbladder morphology. Abnormal gallbladder morphology-regardless of triangular cord thickness-led to node 5, which had 39 (92.9%) patients with BA and 3 (7.1%) patients without BA (Figs. 2, 3). In the other branch, which showed normal gallbladder morphology, the next division was based on the triangular cord thickness. The optimal cutoff value of triangular cord thickness for a diagnosis of BA was automatically selected as 3.4 mm by the statistical method. Normal gallbladder morphology with triangular cord thickness > 3.4 mm led to node 4. All 7 cases in node 4 had BA (Fig. 4). The remaining 51 cases with normal gallbladder morphology and triangular cord thickness ≤ 3.4 mm reached node 3, in which no patients had BA.

Bottom Line: Logistic regression analyses were performed to determine the features that would be useful in predicting BA.Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups.Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively).

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Seoul National University College of Medicine, Seoul 03080, Korea.

ABSTRACT

Objective: To assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA).

Materials and methods: From March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups.

Results: Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100).

Conclusion: Abnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology.

No MeSH data available.


Related in: MedlinePlus