1
|
Guo X, Xu L, Li S, Xu M, Chu Y, Jiang Q. Cascade-EC Network: Recognition of Gastrointestinal Multiple Lesions Based on EfficientNet and CA_stm_Retinanet. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024:10.1007/s10278-024-01096-9. [PMID: 38587768 DOI: 10.1007/s10278-024-01096-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 03/17/2024] [Accepted: 03/20/2024] [Indexed: 04/09/2024]
Abstract
Capsule endoscopy (CE) is non-invasive and painless during gastrointestinal examination. However, capsule endoscopy can increase the workload of image reviewing for clinicians, making it prone to missed and misdiagnosed diagnoses. Current researches primarily concentrated on binary classifiers, multiple classifiers targeting fewer than four abnormality types and detectors within a specific segment of the digestive tract, and segmenters for a single type of anomaly. Due to intra-class variations, the task of creating a unified scheme for detecting multiple gastrointestinal diseases is particularly challenging. A cascade neural network designed in this study, Cascade-EC, can automatically identify and localize four types of gastrointestinal lesions in CE images: angiectasis, bleeding, erosion, and polyp. Cascade-EC consists of EfficientNet for image classification and CA_stm_Retinanet for lesion detection and location. As the first layer of Cascade-EC, the EfficientNet network classifies CE images. CA_stm_Retinanet, as the second layer, performs the target detection and location task on the classified image. CA_stm_Retinanet adopts the general architecture of Retinanet. Its feature extraction module is the CA_stm_Backbone from the stack of CA_stm Block. CA_stm Block adopts the split-transform-merge strategy and introduces the coordinate attention. The dataset in this study is from Shanghai East Hospital, collected by PillCam SB3 and AnKon capsule endoscopes, which contains a total of 7936 images of 317 patients from the years 2017 to 2021. In the testing set, the average precision of Cascade-EC in the multi-lesions classification task was 94.55%, the average recall was 90.60%, and the average F1 score was 92.26%. The mean mAP@ 0.5 of Cascade-EC for detecting the four types of diseases is 85.88%. The experimental results show that compared with a single target detection network, Cascade-EC has better performance and can effectively assist clinicians to classify and detect multiple lesions in CE images.
Collapse
Affiliation(s)
- Xudong Guo
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
| | - Lei Xu
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Shengnan Li
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Meidong Xu
- Endoscopy Center, Department of Gastroenterology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China.
| | - Yuan Chu
- Endoscopy Center, Department of Gastroenterology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Qinfen Jiang
- Department of Information Management, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| |
Collapse
|
2
|
Jiang S, Wang T, Zhang KH. Data-driven decision-making for precision diagnosis of digestive diseases. Biomed Eng Online 2023; 22:87. [PMID: 37658345 PMCID: PMC10472739 DOI: 10.1186/s12938-023-01148-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 08/15/2023] [Indexed: 09/03/2023] Open
Abstract
Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine. However, traditional statistical methods cannot effectively process and utilize such big data. To meet this new challenge, machine learning algorithms have been developed and applied rapidly in recent years, which are capable of reducing dimensionality, extracting features, organizing data and forming automatable data-driven clinical decision systems. Data-driven clinical decision-making have promising applications in precision medicine and has been studied in digestive diseases, including early diagnosis and screening, molecular typing, staging and stratification of digestive malignancies, as well as precise diagnosis of Crohn's disease, auxiliary diagnosis of imaging and endoscopy, differential diagnosis of cystic lesions, etiology discrimination of acute abdominal pain, stratification of upper gastrointestinal bleeding (UGIB), and real-time diagnosis of esophageal motility function, showing good application prospects. Herein, we reviewed the recent progress of data-driven clinical decision making in precision diagnosis of digestive diseases and discussed the limitations of data-driven decision making after a brief introduction of methods for data-driven decision making.
Collapse
Affiliation(s)
- Song Jiang
- Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, No. 17, Yongwai Zheng Street, Nanchang, 330006 China
- Jiangxi Institute of Gastroenterology and Hepatology, Nanchang, 330006 China
| | - Ting Wang
- Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, No. 17, Yongwai Zheng Street, Nanchang, 330006 China
- Jiangxi Institute of Gastroenterology and Hepatology, Nanchang, 330006 China
| | - Kun-He Zhang
- Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, No. 17, Yongwai Zheng Street, Nanchang, 330006 China
- Jiangxi Institute of Gastroenterology and Hepatology, Nanchang, 330006 China
| |
Collapse
|
3
|
Shi Y, Sang J, Sang Y. Analysis of the Influence of Comprehensive Nursing Intervention on Vital Signs and Negative Emotions of Patients with Gastrointestinal Polyps Treated by Digestive Endoscopy. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:5931588. [PMID: 35785053 PMCID: PMC9249447 DOI: 10.1155/2022/5931588] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 05/09/2022] [Accepted: 06/02/2022] [Indexed: 11/18/2022]
Abstract
This research sets out to elucidate the influence of comprehensive nursing intervention (CNI) on vital signs (VSs) and negative emotions (NEs) of patients with gastrointestinal polyps treated by digestive endoscopy. To address this, from January 2020 to February 2021, 92 cases of gastrointestinal polyps treated by digestive endoscopy in the Yuyao People's Hospital of Zhejiang Province were partitioned into two different groups: the control group (CG; n = 46) intervened by routine nursing intervention, and the research group (RG; n = 46) treated by CNI based on routine care. The VSs, NEs, time of first postoperative exhaust and defecation, early food intake, length of stay (LOS), quality of life (QOL), nursing satisfaction, and the incidence of postoperative complications were compared between groups. When entering the operating room, elevated systolic/diastolic (SBP/DBP) was observed in CG compared with RG (P < 0.05) while there was no statistical difference in SBP/DBP in RG before intervention and when entering the operating room (P > 0.05). Statistically, less time of first exhaust and defecation as well as LOS and early food intake were observed in RG (P < 0.05). The HAMA and HAMD scores declined in both arms postintervention, and the decrease was more obvious in RG (P < 0.05). After intervention, the scores of various domains of GQOLI-74 elevated in both arms, and the increase was more obvious in RG (P < 0.05). RG also showed a lower total complication rate and a higher degree of nursing satisfaction than CG (P < 0.05). CNI for patients with gastrointestinal polyps treated by digestive endoscopy can obviously relieve their anxiety and depression, with stable VSs, short LOS, and low incidence of complications.
Collapse
Affiliation(s)
- Yaer Shi
- Department of Gastroenterology, Yuyao People's Hospital, Yuyao 315400, Zhejiang Province, China
| | - Jianzhong Sang
- Department of Gastroenterology, Yuyao People's Hospital, Yuyao 315400, Zhejiang Province, China
| | - Yimao Sang
- Department of Gastroenterology, Yuyao People's Hospital, Yuyao 315400, Zhejiang Province, China
| |
Collapse
|
4
|
Kim HJ, Gong EJ, Bang CS, Lee JJ, Suk KT, Baik GH. Computer-Aided Diagnosis of Gastrointestinal Protruded Lesions Using Wireless Capsule Endoscopy: A Systematic Review and Diagnostic Test Accuracy Meta-Analysis. J Pers Med 2022; 12:jpm12040644. [PMID: 35455760 PMCID: PMC9029411 DOI: 10.3390/jpm12040644] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 04/14/2022] [Accepted: 04/14/2022] [Indexed: 12/13/2022] Open
Abstract
Background: Wireless capsule endoscopy allows the identification of small intestinal protruded lesions, such as polyps, tumors, or venous structures. However, reading wireless capsule endoscopy images or movies is time-consuming, and minute lesions are easy to miss. Computer-aided diagnosis (CAD) has been applied to improve the efficacy of the reading process of wireless capsule endoscopy images or movies. However, there are no studies that systematically determine the performance of CAD models in diagnosing gastrointestinal protruded lesions. Objective: The aim of this study was to evaluate the diagnostic performance of CAD models for gastrointestinal protruded lesions using wireless capsule endoscopic images. Methods: Core databases were searched for studies based on CAD models for the diagnosis of gastrointestinal protruded lesions using wireless capsule endoscopy, and data on diagnostic performance were presented. A systematic review and diagnostic test accuracy meta-analysis were performed. Results: Twelve studies were included. The pooled area under the curve, sensitivity, specificity, and diagnostic odds ratio of CAD models for the diagnosis of protruded lesions were 0.95 (95% confidence interval, 0.93–0.97), 0.89 (0.84–0.92), 0.91 (0.86–0.94), and 74 (43–126), respectively. Subgroup analyses showed robust results. Meta-regression found no source of heterogeneity. Publication bias was not detected. Conclusion: CAD models showed high performance for the optical diagnosis of gastrointestinal protruded lesions based on wireless capsule endoscopy.
Collapse
Affiliation(s)
- Hye Jin Kim
- Department of Internal Medicine, Hallym University College of Medicine, Chuncheon 24253, Korea; (H.J.K.); (E.J.G.); (K.T.S.); (G.H.B.)
- Institute for Liver and Digestive Diseases, Hallym University, Chuncheon 24253, Korea
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24253, Korea;
| | - Eun Jeong Gong
- Department of Internal Medicine, Hallym University College of Medicine, Chuncheon 24253, Korea; (H.J.K.); (E.J.G.); (K.T.S.); (G.H.B.)
- Institute for Liver and Digestive Diseases, Hallym University, Chuncheon 24253, Korea
| | - Chang Seok Bang
- Department of Internal Medicine, Hallym University College of Medicine, Chuncheon 24253, Korea; (H.J.K.); (E.J.G.); (K.T.S.); (G.H.B.)
- Institute for Liver and Digestive Diseases, Hallym University, Chuncheon 24253, Korea
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24253, Korea;
- Division of Big Data and Artificial Intelligence, Chuncheon Sacred Heart Hospital, Chuncheon 24253, Korea
- Correspondence: ; Tel.: +82-33-240-5821; Fax: +82-33-241-8064
| | - Jae Jun Lee
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24253, Korea;
- Division of Big Data and Artificial Intelligence, Chuncheon Sacred Heart Hospital, Chuncheon 24253, Korea
- Department of Anesthesiology and Pain Medicine, Hallym University College of Medicine, Chuncheon 24253, Korea
| | - Ki Tae Suk
- Department of Internal Medicine, Hallym University College of Medicine, Chuncheon 24253, Korea; (H.J.K.); (E.J.G.); (K.T.S.); (G.H.B.)
- Institute for Liver and Digestive Diseases, Hallym University, Chuncheon 24253, Korea
| | - Gwang Ho Baik
- Department of Internal Medicine, Hallym University College of Medicine, Chuncheon 24253, Korea; (H.J.K.); (E.J.G.); (K.T.S.); (G.H.B.)
- Institute for Liver and Digestive Diseases, Hallym University, Chuncheon 24253, Korea
| |
Collapse
|
5
|
Bang CS, Lee JJ, Baik GH. Computer-Aided Diagnosis of Gastrointestinal Ulcer and Hemorrhage Using Wireless Capsule Endoscopy: Systematic Review and Diagnostic Test Accuracy Meta-analysis. J Med Internet Res 2021; 23:e33267. [PMID: 34904949 PMCID: PMC8715364 DOI: 10.2196/33267] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 10/10/2021] [Accepted: 10/13/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Interpretation of capsule endoscopy images or movies is operator-dependent and time-consuming. As a result, computer-aided diagnosis (CAD) has been applied to enhance the efficacy and accuracy of the review process. Two previous meta-analyses reported the diagnostic performance of CAD models for gastrointestinal ulcers or hemorrhage in capsule endoscopy. However, insufficient systematic reviews have been conducted, which cannot determine the real diagnostic validity of CAD models. OBJECTIVE To evaluate the diagnostic test accuracy of CAD models for gastrointestinal ulcers or hemorrhage using wireless capsule endoscopic images. METHODS We conducted core databases searching for studies based on CAD models for the diagnosis of ulcers or hemorrhage using capsule endoscopy and presenting data on diagnostic performance. Systematic review and diagnostic test accuracy meta-analysis were performed. RESULTS Overall, 39 studies were included. The pooled area under the curve, sensitivity, specificity, and diagnostic odds ratio of CAD models for the diagnosis of ulcers (or erosions) were .97 (95% confidence interval, .95-.98), .93 (.89-.95), .92 (.89-.94), and 138 (79-243), respectively. The pooled area under the curve, sensitivity, specificity, and diagnostic odds ratio of CAD models for the diagnosis of hemorrhage (or angioectasia) were .99 (.98-.99), .96 (.94-0.97), .97 (.95-.99), and 888 (343-2303), respectively. Subgroup analyses showed robust results. Meta-regression showed that published year, number of training images, and target disease (ulcers vs erosions, hemorrhage vs angioectasia) was found to be the source of heterogeneity. No publication bias was detected. CONCLUSIONS CAD models showed high performance for the optical diagnosis of gastrointestinal ulcer and hemorrhage in wireless capsule endoscopy.
Collapse
Affiliation(s)
- Chang Seok Bang
- Department of Internal Medicine, Hallym University College of Medicine, Chuncheon, Republic of Korea.,Institute for Liver and Digestive Diseases, Hallym University, Chuncheon, Republic of Korea.,Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon, Republic of Korea.,Division of Big Data and Artificial Intelligence, Chuncheon Sacred Heart Hospital, Chuncheon, Republic of Korea
| | - Jae Jun Lee
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon, Republic of Korea.,Division of Big Data and Artificial Intelligence, Chuncheon Sacred Heart Hospital, Chuncheon, Republic of Korea.,Department of Anesthesiology and Pain Medicine, Hallym University College of Medicine, Chuncheon, Republic of Korea
| | - Gwang Ho Baik
- Department of Internal Medicine, Hallym University College of Medicine, Chuncheon, Republic of Korea.,Institute for Liver and Digestive Diseases, Hallym University, Chuncheon, Republic of Korea
| |
Collapse
|