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Wen Y, Yang L, Li X, Ma X, Pang Y. Combined percutaneous-endoscopic puncture rendezvous technique for biliary-enteric anastomotic occlusion after pancreaticoduodenectomy. Endoscopy 2024; 56:E364-E365. [PMID: 38657673 PMCID: PMC11042880 DOI: 10.1055/a-2299-1974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Affiliation(s)
- Yi Wen
- General Surgery, Peopleʼs Liberation Army General Hospital of Western Theater Command, Chengdu, China
| | - Lin Yang
- General Surgery, Peopleʼs Liberation Army General Hospital of Western Theater Command, Chengdu, China
- College of Medicine, Southwest Jiaotong University, Chengdu, China
| | - Xiao Li
- General Surgery, Peopleʼs Liberation Army General Hospital of Western Theater Command, Chengdu, China
| | - Xiao Ma
- General Surgery, Peopleʼs Liberation Army General Hospital of Western Theater Command, Chengdu, China
| | - Yong Pang
- General Surgery, Peopleʼs Liberation Army General Hospital of Western Theater Command, Chengdu, China
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Liang H, Wang M, Wen Y, Du F, Jiang L, Geng X, Tang L, Yan H. Predicting acute pancreatitis severity with enhanced computed tomography scans using convolutional neural networks. Sci Rep 2023; 13:17514. [PMID: 37845380 PMCID: PMC10579320 DOI: 10.1038/s41598-023-44828-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 10/12/2023] [Indexed: 10/18/2023] Open
Abstract
This study aimed to evaluate acute pancreatitis (AP) severity using convolutional neural network (CNN) models with enhanced computed tomography (CT) scans. Three-dimensional DenseNet CNN models were developed and trained using the enhanced CT scans labeled with two severity assessment methods: the computed tomography severity index (CTSI) and Atlanta classification. Each labeling method was used independently for model training and validation. Model performance was evaluated using confusion matrices, areas under the receiver operating characteristic curve (AUC-ROC), accuracy, precision, recall, F1 score, and respective macro-average metrics. A total of 1,798 enhanced CT scans met the inclusion criteria were included in this study. The dataset was randomly divided into a training dataset (n = 1618) and a test dataset (n = 180) with a ratio of 9:1. The DenseNet model demonstrated promising predictions for both CTSI and Atlanta classification-labeled CT scans, with accuracy greater than 0.7 and AUC-ROC greater than 0.8. Specifically, when trained with CT scans labeled using CTSI, the DenseNet model achieved good performance, with a macro-average F1 score of 0.835 and a macro-average AUC-ROC of 0.980. The findings of this study affirm the feasibility of employing CNN models to predict the severity of AP using enhanced CT scans.
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Affiliation(s)
- Hongyin Liang
- Department of General Surgery, The General Hospital of Western Theater Command (Chengdu Military General Hospital), Chengdu, 610083, China
- Sichuan Provincial Key Laboratory of Pancreatic Injury and Repair, Chengdu, 610083, China
| | - Meng Wang
- Department of Traditional Chinese Medicine, The General Hospital of Western Theater Command (Chengdu Military General Hospital), Chengdu, 610083, China
| | - Yi Wen
- Department of General Surgery, The General Hospital of Western Theater Command (Chengdu Military General Hospital), Chengdu, 610083, China
- Sichuan Provincial Key Laboratory of Pancreatic Injury and Repair, Chengdu, 610083, China
| | - Feizhou Du
- Department of Radiology, The General Hospital of Western Theater Command (Chengdu Military General Hospital), Chengdu, 610083, China
| | - Li Jiang
- Department of Cardiac Surgery, The General Hospital of Western Theater Command (Chengdu Military General Hospital), Chengdu, 610083, China
| | - Xuelong Geng
- Department of Radiology, The General Hospital of Western Theater Command (Chengdu Military General Hospital), Chengdu, 610083, China
| | - Lijun Tang
- Department of General Surgery, The General Hospital of Western Theater Command (Chengdu Military General Hospital), Chengdu, 610083, China
- Sichuan Provincial Key Laboratory of Pancreatic Injury and Repair, Chengdu, 610083, China
| | - Hongtao Yan
- Department of Liver Transplantation and Hepato-biliary-pancreatic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610016, China.
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