Novel 3D morphological characteristics for congenital biliary dilatation diagnosis: A case-control study

Author:

Dou Jiaqi1,Jiang Nan234,Zeng Jianping234,Wang Siyuan234,Tian Song5,Shan Siqiao234,Li Yuze1,Xu Ziming1,Lin Xiaoqi1,Jin Shuo234,Dong Jiahong234,Chen Huijun1

Affiliation:

1. Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China

2. Hepatopancreatobiliary Center, Beijing Tsinghua Changgung Hospital, Key Laboratory of Digital Intelligence Hepatology, Ministry of Education, School of Clinical Medicine, Tsinghua University, Beijing, China

3. Research Unit of Precision Hepatobiliary Surgery Paradigm, Chinese Academy of Medical Sciences, Beijing, China

4. Institute for Precision Medicine, Tsinghua University, Beijing, China

5. Philips Healthcare, Beijing, China

Abstract

Background: Congenital biliary dilatation (CBD) necessitates the timely removal of dilated bile ducts. Accurate differentiation between CBD and secondary biliary dilatation (SBD) is crucial for treatment decisions, and identification of CBD with intrahepatic involvement is vital for surgical planning and supportive care. This study aimed to develop quantitative models based on bile duct morphology to distinguish CBD from SBD and further identify CBD with intrahepatic involvement. Materials and Methods: The retrospective study included 131 CBD and 209 SBD patients between December 2014 and December 2021 for model development, internal validation and testing. A separate cohort of 15 CBD and 34 SBD patients between January 2022 and December 2022 was recruited for temporally-independent validation. Quantitative shape-based (Shape) and diameter-based (Diam) morphological characteristics of bile ducts were extracted to build a CBD diagnosis model to distinguish CBD from SBD and an intrahepatic involvement identification model to classify CBD with/without intrahepatic involvement. The diagnostic performance of the models was compared with that of experienced hepatobiliary surgeons. Results: The CBD diagnosis model using clinical, Shape, and Diam characteristics showed good performance with an AUROC of 0.942 [95% CI: 0.890-0.994], AUPRC of 0.917 [0.855-0.979], accuracy of 0.891, sensitivity of 0.950 and F1-score of 0.864. The model outperformed two experienced surgeons in accuracy, sensitivity, and F1-score. The intrahepatic involvement identification model using clinical, Shape, and Diam characteristics yielded outstanding performance with an AUROC of 0.944 [0.879-1.000], AUPRC of 0.982 [0.947-1.000], accuracy of 0.932, sensitivity of 0.971 and F1-score of 0.957. The models demonstrated generalizable performance on the temporally-independent validation cohort. Conclusions: This study developed two robust quantitative models for distinguishing CBD from SBD and identifying CBD with intrahepatic involvement, respectively, based on morphological characteristics of the bile ducts, showing great potential in risk stratification and surgical planning of CBD.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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