Back to Search
Start Over
A deep learning model based on magnifying endoscopy with narrow-band imaging to evaluate intestinal metaplasia grading and OLGIM staging: A multicenter study.
- Source :
-
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver [Dig Liver Dis] 2024 Sep; Vol. 56 (9), pp. 1565-1571. Date of Electronic Publication: 2024 Feb 23. - Publication Year :
- 2024
-
Abstract
- Background and Purpose: Patients with stage III or IV of operative link for gastric intestinal metaplasia assessment (OLGIM) are at a higher risk of gastric cancer (GC). We aimed to construct a deep learning (DL) model based on magnifying endoscopy with narrow-band imaging (ME-NBI) to evaluate OLGIM staging.<br />Methods: This study included 4473 ME-NBI images obtained from 803 patients at three endoscopy centres. The endoscopic expert marked intestinal metaplasia (IM) regions on endoscopic images of the target biopsy sites. Faster Region-Convolutional Neural Network model was used to grade IM lesions and predict OLGIM staging.<br />Results: The diagnostic performance of the model for IM grading in internal and external validation sets, as measured by the area under the curve (AUC), was 0.872 and 0.803, respectively. The accuracy of this model in predicting the high-risk stage of OLGIM was 84.0%, which was not statistically different from that of three junior (71.3%, p = 0.148) and three senior endoscopists (75.3%, p = 0.317) specially trained in endoscopic images corresponding to pathological IM grade, but higher than that of three untrained junior endoscopists (64.0%, p = 0.023).<br />Conclusion: This DL model can assist endoscopists in predicting OLGIM staging using ME-NBI without biopsy, thereby facilitating screening high-risk patients for GC.<br />Competing Interests: Conflict of interest The authors declare no conflict of interest for this article.<br /> (Copyright © 2024 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.)
- Subjects :
- Humans
Female
Male
Middle Aged
Aged
Gastroscopy methods
Retrospective Studies
Adult
Precancerous Conditions pathology
Precancerous Conditions diagnostic imaging
Deep Learning
Metaplasia pathology
Metaplasia diagnostic imaging
Narrow Band Imaging
Stomach Neoplasms pathology
Stomach Neoplasms diagnostic imaging
Subjects
Details
- Language :
- English
- ISSN :
- 1878-3562
- Volume :
- 56
- Issue :
- 9
- Database :
- MEDLINE
- Journal :
- Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
- Publication Type :
- Academic Journal
- Accession number :
- 38402085
- Full Text :
- https://doi.org/10.1016/j.dld.2024.02.001