MRI-based decision tree model for diagnosis of biliary atresia

Yong Hee Kim, Myung Joon Kim, Hyun Joo Shin, Haesung Yoon, Seok Joo Han, Hong Koh, Yun Ho Roh, MiJung Lee

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Objectives: To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. Methods: We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. Results: A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. Conclusions: MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. Key Points: • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.

Original languageEnglish
Pages (from-to)3422-3431
Number of pages10
JournalEuropean Radiology
Volume28
Issue number8
DOIs
Publication statusPublished - 2018 Aug 1

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Biliary Atresia
Decision Trees
Ultrasonography
Common Bile Duct
Jaundice
Gallbladder
Doppler Ultrasonography
Research Ethics Committees
Cholestasis
Sensitivity and Specificity
Liver

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

Cite this

Kim, Y. H., Kim, M. J., Shin, H. J., Yoon, H., Han, S. J., Koh, H., ... Lee, M. (2018). MRI-based decision tree model for diagnosis of biliary atresia. European Radiology, 28(8), 3422-3431. https://doi.org/10.1007/s00330-018-5327-0
Kim, Yong Hee ; Kim, Myung Joon ; Shin, Hyun Joo ; Yoon, Haesung ; Han, Seok Joo ; Koh, Hong ; Roh, Yun Ho ; Lee, MiJung. / MRI-based decision tree model for diagnosis of biliary atresia. In: European Radiology. 2018 ; Vol. 28, No. 8. pp. 3422-3431.
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abstract = "Objectives: To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. Methods: We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. Results: A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 {\%} sensitivity, 94.8 {\%} specificity and 96.2 {\%} accuracy. Conclusions: MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. Key Points: • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.",
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Kim, YH, Kim, MJ, Shin, HJ, Yoon, H, Han, SJ, Koh, H, Roh, YH & Lee, M 2018, 'MRI-based decision tree model for diagnosis of biliary atresia', European Radiology, vol. 28, no. 8, pp. 3422-3431. https://doi.org/10.1007/s00330-018-5327-0

MRI-based decision tree model for diagnosis of biliary atresia. / Kim, Yong Hee; Kim, Myung Joon; Shin, Hyun Joo; Yoon, Haesung; Han, Seok Joo; Koh, Hong; Roh, Yun Ho; Lee, MiJung.

In: European Radiology, Vol. 28, No. 8, 01.08.2018, p. 3422-3431.

Research output: Contribution to journalArticle

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AU - Kim, Yong Hee

AU - Kim, Myung Joon

AU - Shin, Hyun Joo

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AU - Koh, Hong

AU - Roh, Yun Ho

AU - Lee, MiJung

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N2 - Objectives: To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. Methods: We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. Results: A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. Conclusions: MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. Key Points: • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.

AB - Objectives: To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. Methods: We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. Results: A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. Conclusions: MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. Key Points: • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.

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Kim YH, Kim MJ, Shin HJ, Yoon H, Han SJ, Koh H et al. MRI-based decision tree model for diagnosis of biliary atresia. European Radiology. 2018 Aug 1;28(8):3422-3431. https://doi.org/10.1007/s00330-018-5327-0