Usefulness of Narrow-Band Imaging in Endoscopic Submucosal Dissection of the Stomach

Kim, Jung Wook

doi:10.5946/ce.2018.186

Cited by 15 publications

(16 citation statements)

References 39 publications

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“…Although this new pCLE classification system correlates well with specific histological conditions and has been reproducible by multiple investigators, it is inferior to the Updated Sydney system for the diagnosis of atrophic gastritis. Additional studies have cultivated its use for tumor differential detection in the stomach and esophagus by combination with endoscopic submucosal dissection, and it has demonstrated efficacy for the treatment of neoplasms[ 17 , 18 ]. In our study, we compared the Updated Sydney system and the Kimura-Takemoto visual endoscopic classification system for atrophic gastritis.…”

Section: Discussionmentioning

confidence: 99%

Updated Kimura-Takemoto classification of atrophic gastritis

Kotelevets¹,

Chekh²,

Чуков³

2021

WJCC

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BACKGROUND The Updated Sydney system for visual evaluation of gastric mucosal atrophy via endoscopic observation is subject to sampling error and interobserver variability. The Kimura-Takemoto classification system was developed to overcome these limitations. AIM To compare the morphological classification of atrophic gastritis between the Kimura-Takemoto system and the Updated Sydney system. METHODS A total of 169 patients with atrophic gastritis were selected according to diagnosis by the visual endoscopic Kimura-Takemoto method. Following the Updated Kimura-Takemoto classification system, one antrum biopsy and five gastric corpus biopsies were taken according to the visual stages of the Kimura-Takemoto system. The Updated Kimura-Takemoto classification system was then applied to each and showed 165 to have histological mucosal atrophy; the remaining 4 patients had no histological evidence of atrophy in any biopsy. The Updated Kimura-Takemoto classification was verified as a reference morphological method and applied for the diagnosis of atrophic gastritis. Adding one more biopsy from the antrum to the six biopsies according to the Updated Kimura-Takemoto classification, constitutes the updated combined Kimura-Takemoto classification and Sydney system. RESULTS The sensitivity for degree of mucosal atrophy assessed by the Updated Sydney system was 25% for mild, 36% for moderate, and 42% for severe, when compared with the Updated Kimura-Takemoto classification of atrophic gastritis for morphological diagnosis. Four types of multifocal atrophic gastritis were identified: sequential uniform (type 1; in 28%), sequential non-uniform (type 2; in 7%), diffuse uniform (type 3; in 23%), diffuse non-uniform (type 4; in 24%), and "alternating atrophic – non-atrophic" (type 5; in 18%). The pattern of the spread of atrophy, sequentially from the antrum to the cardiac segment of the stomach, which was described by the Updated Kimura-Takemoto system, was histologically confirmed in 82% of cases evaluated. CONCLUSION The Updated Sydney system is significantly inferior to the Updated Kimura-Takemoto classification for morphological verification of atrophic gastritis.

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Section: Discussionmentioning

confidence: 99%

Updated Kimura-Takemoto classification of atrophic gastritis

Kotelevets¹,

Chekh²,

Чуков³

2021

WJCC

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“…Previous studies on the diagnosis of H pylori infection with WLI showed low sensitivity and poor interobserver agreement [ 11 , 32 - 34 ]. However, studies with IEE commonly showed increased diagnostic accuracy of premalignant or malignant lesions during endoscopic examination [ 11 , 12 ]. Previous studies with IEE also indicated the usefulness of LCI for the diagnosis of H pylori infection [ 35 , 36 ].…”

Section: Discussionmentioning

confidence: 99%

“…Image-enhanced endoscopy (IEE), such as narrow-band imaging (NBI), BLI, or linked color imaging (LCI), with or without magnification, has been developed. Previous studies have indicated increased diagnostic accuracy of gastrointestinal neoplasms with the application of these modalities during endoscopic examination [ 11 , 12 ]. This also requires considerable training and prolonged procedure time.…”

Section: Introductionmentioning

confidence: 99%

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Artificial Intelligence for the Prediction of Helicobacter Pylori Infection in Endoscopic Images: Systematic Review and Meta-Analysis Of Diagnostic Test Accuracy

Seok

2020

J Med Internet Res

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Background Helicobacter pylori plays a central role in the development of gastric cancer, and prediction of H pylori infection by visual inspection of the gastric mucosa is an important function of endoscopy. However, there are currently no established methods of optical diagnosis of H pylori infection using endoscopic images. Definitive diagnosis requires endoscopic biopsy. Artificial intelligence (AI) has been increasingly adopted in clinical practice, especially for image recognition and classification. Objective This study aimed to evaluate the diagnostic test accuracy of AI for the prediction of H pylori infection using endoscopic images. Methods Two independent evaluators searched core databases. The inclusion criteria included studies with endoscopic images of H pylori infection and with application of AI for the prediction of H pylori infection presenting diagnostic performance. Systematic review and diagnostic test accuracy meta-analysis were performed. Results Ultimately, 8 studies were identified. Pooled sensitivity, specificity, diagnostic odds ratio, and area under the curve of AI for the prediction of H pylori infection were 0.87 (95% CI 0.72-0.94), 0.86 (95% CI 0.77-0.92), 40 (95% CI 15-112), and 0.92 (95% CI 0.90-0.94), respectively, in the 1719 patients (385 patients with H pylori infection vs 1334 controls). Meta-regression showed methodological quality and included the number of patients in each study for the purpose of heterogeneity. There was no evidence of publication bias. The accuracy of the AI algorithm reached 82% for discrimination between noninfected images and posteradication images. Conclusions An AI algorithm is a reliable tool for endoscopic diagnosis of H pylori infection. The limitations of lacking external validation performance and being conducted only in Asia should be overcome. Trial Registration PROSPERO CRD42020175957; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=175957

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“…In addition, there are some limitations when using ME‐NBI in clinical practice. First of all, considerable training and experience with endoscope manipulation and interpretation of images are required for optimal performance of ME‐NBI 11,34 . However, the newly developed DF endoscope (GIF‐HQ290; Olympus) compensates for the shortcomings of conventional magnification endoscopes and NBI systems.…”

Section: Discussionmentioning

confidence: 99%

Narrowband imaging with near‐focus magnification for discriminating the gastric tumor margin before endoscopic resection: A prospective randomized multicenter trial

Kim

Jung

Jang

et al. 2020

J of Gastro and Hepatol

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Background and Aim This study investigated the usefulness of near‐focus narrowband imaging (NF‐NBI) for determining gastric tumor margins compared with indigo carmine chromoendoscopy (ICC) before endoscopic submucosal dissection (ESD). Methods This prospective randomized controlled trial was conducted at seven teaching hospitals in Korea. Patients with gastric adenoma or differentiated adenocarcinoma undergoing ESD were enrolled and randomly assigned to the NF‐NBI or ICC group. A marking dot was placed on the most proximal margin of the tumor before ESD. The primary endpoint was delineation accuracy, which was defined as presence of marking dots within 1 mm of the tumor margin under microscopic observation. Results A total of 200 patients in the NF‐NBI group and 195 patients in the ICC group were included. The delineation accuracy rate was 84.5% in the NF‐NBI group and 81.0% in the ICC group (P = 0.44). However, the distance from the marking dot to the margin of the tumor was significantly shorter in the NF‐NBI group than in the ICC group (0.8 ± 0.8 vs 1.2 ± 1.3 mm, P < 0.01). Even after adjustment of other clinicopathological factors that are associated with difficulty of tumor delineation, NF‐NBI did not show significant association with accurate delineation (odds ratio of 0.86, P = 0.60). Conclusions This prospective multicenter study showed that NF‐NBI is not superior to ICC in terms of accurately delineating gastric tumors (NCT02661945).

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Usefulness of Narrow-Band Imaging in Endoscopic Submucosal Dissection of the Stomach

Cited by 15 publications

References 39 publications

Updated Kimura-Takemoto classification of atrophic gastritis

Updated Kimura-Takemoto classification of atrophic gastritis

Artificial Intelligence for the Prediction of Helicobacter Pylori Infection in Endoscopic Images: Systematic Review and Meta-Analysis Of Diagnostic Test Accuracy

Narrowband imaging with near‐focus magnification for discriminating the gastric tumor margin before endoscopic resection: A prospective randomized multicenter trial

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