Abstract

Pancreatoscopy plays a significant role in the diagnosis and treatment of pancreatic diseases. However, the risk of pancreatoscopy is remarkably greater than that of other endoscopic procedures, such as gastroscopy and bronchoscopy, owing to its severe invasiveness. In comparison, virtual pancreatoscopy (VP) has shown notable advantages. However, because of the low resolution of current computed tomography (CT) technology and the small diameter of the pancreatic duct, VP has limited clinical use. In this study, an optimal path algorithm and super-resolution technique are investigated for the development of an open-source software platform for VP based on 3D Slicer. The proposed segmentation of the pancreatic duct from the abdominal CT images reached an average Dice coefficient of 0.85 with a standard deviation of 0.04. Owing to the excellent segmentation performance, a fly-through visualization of both the inside and outside of the duct was successfully reconstructed, thereby demonstrating the feasibility of VP. In addition, a quantitative analysis of the wall thickness and topology of the duct provides more insight into pancreatic diseases than a fly-through visualization. The entire VP system developed in this study is available at https://github.com/gaoyi/VirtualEndoscopy.git.

Details

Title
Open-source algorithm and software for computed tomography-based virtual pancreatoscopy and other applications
Author
Huang, Haofan 1 ; Yu, Xiaxia 1 ; Tian, Mu 1 ; He, Weizhen 1 ; Li, Shawn Xiang 1 ; Liang, Zhengrong 2 ; Gao, Yi 3   VIAFID ORCID Logo 

 Health Science Center, Shenzhen University, School of Biomedical Engineering, Shenzhen, China (GRID:grid.263488.3) (ISNI:0000 0001 0472 9649) 
 State University of New York, Laboratory for Imaging Research and Informatics, Stony Brook, USA (GRID:grid.36425.36) (ISNI:0000 0001 2216 9681) 
 Health Science Center, Shenzhen University, School of Biomedical Engineering, Shenzhen, China (GRID:grid.263488.3) (ISNI:0000 0001 0472 9649); Shenzhen Key Laboratory of Precision Medicine for Hematological Malignancies, Shenzhen, China (GRID:grid.263488.3); Marshall Laboratory of Biomedical Engineering, Shenzhen, China (GRID:grid.263488.3); Peng Cheng Laboratory, Shenzhen, China (GRID:grid.508161.b) 
Pages
20
Publication year
2022
Publication date
Dec 2022
Publisher
Springer Nature B.V.
e-ISSN
25244442
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2890052578
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.