Background: Fundic gland polyps (FGP) of stomach are benign, while some hyperplastic polyps (HP) may harbor dysplasia or malignancy. Conventional white light endoscopy (WLE) cannot reliably distinguish FGP from HP. We investigated the role of image-enhanced endoscopy in differentiating FGP from HP.
Methods: Patients with gastric polyps were recruited prospectively. The characteristics of the polyps were assessed using WLE and magnification narrow band imaging (mNBI). The microsurface, intervening space (IS), and microvascular (V) features of polyps were evaluated on mNBI. The pattern characteristic of FGP and HP were determined. Histopathology of polyps was the gold standard for diagnosis. Finally, in the validation phase, five endoscopists applied the characteristic features identified in this study to predict the type of gastric polyp and their performance was assessed.
Results: Forty-five patients with a total of 70 gastric polyps (HP-46, FGP-24) were included in this study. On mNBI, the pattern characteristic of HP included peripheral curved type of white structures forming large circular/villous loops (microsurface), enlarged intervening space, and microvessels appearing as dark patches in the intervening space (p<0.001 vs. FGP). These were noted in 95.7% HP. In contrast, 95.8% FGP had a pattern characterized by dotted/elliptical/tubular white structures (microsurface), normal width of intervening space, and microvessels surrounding the white structures in a network pattern. This IS-V pattern classification had an accuracy of >90% in the validation phase with intra-class correlation coefficient of 0.95. The accuracy of mNBI was higher than WLE (97.1% vs. 67%) in predicting the type of gastric polyp.
Conclusions: Image-enhanced endoscopy with mNBI (IS-V pattern) performs very well in differentiating HP from FGP.
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http://dx.doi.org/10.1007/s12664-022-01278-9 | DOI Listing |
Ther Adv Gastrointest Endosc
December 2024
Department of Internal Medicine, Hanoi Medical University, Hanoi, Vietnam.
The utilization of artificial intelligence (AI) in gastrointestinal (GI) endoscopy has witnessed significant progress and promising results in recent years worldwide. From 2019 to 2023, the European Society of Gastrointestinal Endoscopy has released multiple guidelines/consensus with recommendations on integrating AI for detecting and classifying lesions in practical endoscopy. In Vietnam, since 2019, several preliminary studies have been conducted to develop AI algorithms for GI endoscopy, focusing on lesion detection.
View Article and Find Full Text PDFClin Endosc
November 2024
Division of Gastroenterology, Department of Internal Medicine, Chung-Ang University College of Medicine, Seoul, Korea.
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View Article and Find Full Text PDFZhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi
December 2024
Department of Otorhinolaryngology, the Second Affiliated Hospital Zhejiang University School of Medicne, Hangzhou310000, China.
To explore and summarize the morphological features of laryngeal tuberculosis under electronic laryngoscopy and image-enhanced endoscopy (i-scan). A retrospective analysis was conducted on the data of 31 patients diagnosed with laryngeal tuberculosis at the Second Affiliated Hospital of Zhejiang University School of Medicine from January 2014 to June 2024, encompassing the morphological features of electronic laryngoscopy and i-scan endoscopy, histopathological features, and supplementary clinical examination results. Descriptive statistical methods were employed for the analysis.
View Article and Find Full Text PDFDig Dis Sci
December 2024
Department of Gastroenterology, National Hospital Organization Hakodate National Hospital, Hakodate, Japan.
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View Article and Find Full Text PDFJ Gastroenterol Hepatol
November 2024
Division of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan.
Background And Aim: Optical diagnosis of superficial nonampullary duodenal epithelial tumors using white-light imaging (WLI) and/or narrow-band imaging with magnifying endoscopy (NBI-ME) is used to guide the treatment strategy and avoid biopsy-induced fibrosis. However, the effectiveness of this approach has not been elucidated. We conducted a systematic review and meta-analysis aiming to investigate the diagnostic yield between Vienna classification category 3 (VCL C3) and categories 4 or 5 (VCL C4/C5) using biopsy, WLI, NBI-ME, and WLI + NBI-ME.
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