Literature DB >> 30415184

A quantitative image analysis using MRI for diagnosis of biliary atresia.

Dao Chen Lin1, Kun Yu Wu2, Fang Ju Sun3, Chun Chao Huang4, Tung Hsin Wu5, Shin Lin Shih6, Pei Shan Tsai7.   

Abstract

PURPOSE: Biliary atresia is a life-threatening disease that needs early diagnosis and management. Recently, MRI images have been used for the diagnosis of biliary atresia with improved accuracy of diagnosis when other imaging modalities such as ultrasonography are equivocal. This study aimed to evaluate the juxta-hilar extrahepatic biliary tree using MRI images to determine a quantitative value for diagnosing biliary atresia.
MATERIALS AND METHODS: This retrospective study was approved by the Ethical Committee at Mackey Memorial Hospital (IRB Number: 15MMHIS149e). Between January 2010 and December 2015, twenty-five patients with surgically confirmed biliary atresia were enrolled (age 18-65 days). Another 25 patients with clinically or surgically diagnosed idiopathic neonatal hepatitis (age 6-64 days) and 20 patients with non-hepatobiliary disease (age 6-65 days) were considered control group and normal subjects, respectively. The diameter of the enlarged, T2-hyperintense structure was measured using MRI images by two radiologists both blinded. The cut-off value for a biliary atresia diagnosis was obtained by area under the curve analysis.
RESULTS: The diameter of the T2-hyperintense structure at porta hepatis in biliary atresia (4.79 ± 1.14 mm) is larger than in idiopathic neonatal hepatitis (1.72 ± 0.42 mm) or in non-hepatobiliary disease (1.72 ± 0.35 mm) (p < 0.05). The optimum cut-off value for diagnosing biliary atresia was 3.1 mm with 98% sensitivity and 98% specificity.
CONCLUSION: The value of the enlarged, T2-hyperintense structure measured on MRI images was significantly increased in biliary atresia and may be useful in diagnosing biliary atresia.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Biliary atresia; Extrahepatic bile duct; Idiopathic neonatal hepatitis; Magnetic resonance imaging

Mesh:

Year:  2018        PMID: 30415184     DOI: 10.1016/j.clinimag.2018.10.001

Source DB:  PubMed          Journal:  Clin Imaging        ISSN: 0899-7071            Impact factor:   1.605


  2 in total

1.  The application of artificial intelligence to support biliary atresia screening by ultrasound images: A study based on deep learning models.

Authors:  Fang-Rong Hsu; Sheng-Tong Dai; Chia-Man Chou; Sheng-Yang Huang
Journal:  PLoS One       Date:  2022-10-19       Impact factor: 3.752

2.  Assessment of Diffusion Tensor Imaging Parameters of Hepatic Parenchyma for Differentiation of Biliary Atresia from Alagille Syndrome.

Authors:  Ahmed Abdel Khalek Abdel Razek; Ahmed Abdalla; Reda Elfar; Germeen Albair Ashmalla; Khadiga Ali; Tarik Barakat
Journal:  Korean J Radiol       Date:  2020-07-27       Impact factor: 3.500

  2 in total

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