Article

High-resolution magnification endoscopy can reliably identify normal gastric mucosa, Helicobacter pylori-associated gastritis, and gastric atrophy.

Wolfson Digestive Diseases Centre and Histopathology Department, University Hospital, Queen's Medical Centre, Nottingham, United Kingdom.
Endoscopy (Impact Factor: 5.74). 04/2007; 39(3):202-7. DOI: 10.1055/s-2006-945056
Source: PubMed

ABSTRACT The aims of the study were to describe the magnified endoscopic findings in the gastric body, correlate these with histology, and evaluate their reproducibility in the assessment of the magnified endoscopic patterns seen.
A total of 95 consecutive dyspeptic patients underwent upper gastrointestinal endoscopy with a magnifying endoscope. The endoscopists classified the magnified endoscopic patterns and correlated them with the histological findings. In the second part of the study, 200 images were shown to five endoscopists in order to examine inter- and intraobserver variability in image assessment.
The magnified endoscopic findings in the gastric body were categorized into four types: type 1, honeycomb-type subepithelial capillary network (SECN) with regular arrangement of collecting venules and regular, round pits; type 2, honeycomb-type SECN with regular, round pits, but loss of collecting venules; type 3, loss of normal SECN and collecting venules, with enlarged white pits surrounded by erythema; and type 4, loss of normal SECN and round pits, with irregular arrangement of collecting venules. The sensitivity, specificity, and positive and negative predictive values of the type 1 pattern for predicting normal gastric mucosa were 92.7% (95% confidence interval [CI] 93.2-97.3%), 100% (95% CI 83.9-100%), 100% (95% CI 92.9-100%), and 83.8% (95% CI 65.5-93.9%). The sensitivity, specificity, and positive and negative predictive values of types 2 and 3 patterns for predicting a Helicobacter pylori-infected stomach were 100% (95% CI 83.9-100%), 92.7% (95% CI 93.2-97.3%), 83.8% (95% CI 65.5-93.9%), and 100% (95% CI 92.9-100%). The sensitivity, specificity, and positive and negative predictive values of a type 4 pattern for predicting gastric atrophy were 90% (95% CI 66.8-98.2%), 96% (95% CI 87.9-98.9%), 85.7% (95% CI 62.6-96.2%), and 97.3% (95% CI 89.6-99.5%. The kappa values for inter- and intraobserver agreement in predicting normal gastric mucosa, H. pylori gastritis, and gastric atrophy were 0.864 and 0.913 respectively.
High-resolution magnification endoscopy can reliably identify the normal gastric mucosa, H. pylori-associated gastritis, and gastric atrophy in a Western population.

0 Bookmarks
 · 
142 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: To investigate the difference in magnifying endoscopic findings of gastric epithelial dysplasias (GEDs) according to the morphologic characteristics.
    World journal of gastroenterology : WJG. 11/2014; 20(42):15771-9.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Abstract Objective. Predicting the invasion depth of superficial esophageal squamous cell carcinoma (SESCC) is important when selecting among therapeutic strategies. The aim of this study was to compare magnifying endoscopy with narrow-band imaging (ME-NBI) with endoscopic ultrasonography (EUS) for predicting the depth of tumor invasion in patients with SESCC. Methods. This study enrolled 51 patients with SESCC (52 SESCC lesions) who underwent both ME-NBI and EUS at Pusan National University Hospital during 2010-2013. We reviewed the patients' medical records and compared ME-NBI and EUS findings with histopathological results according to clinicopathological factors. Results. A total of 46 lesions in 45 patients were included in the final analysis. ME-NBI and EUS had overall accuracies of 76.1% and 84.8%, respectively, in distinguishing mucosal from non-mucosal cancers. There were no differences between ME-NBI and EUS in terms of sensitivities and specificities in distinguishing mucosal from non-mucosal cancers (p = 0.500 and p = 0.688, respectively). When both ME-NBI and EUS suggested a mucosal depth of lesion invasion, the frequency of mucosal cancer in the final histopathology was 94%. However, if either ME-NBI or EUS suggested a non-mucosal depth of invasion, the frequency of mucosal cancer was only 21%. Conclusion. ME-NBI and EUS are accurate predictors of SESCC invasion depth. If both methods suggest a mucosal depth of lesion invasion, the accuracy of the prediction is increased. Therefore, when possible, it would be better to evaluate the invasion depth of SESCC using both ME-NBI and EUS before deciding to perform endoscopic resection.
    Scandinavian journal of gastroenterology. 06/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Infection with Helicobacter pylori (H. pylori) is a worldwide problem. Endoscopic observation of H. pylori infection in vivo would be helpful to obtain an immediate diagnosis. The aim of this review is to describe recent advances in endoscopic technology and to review the available literature pertaining to its clinical application in H. pylori infection. Endoscopic visualization of H. pylori infection is not always feasible using conventional endoscopy. Thus, advanced endoscopic techniques have been developed with the aim of providing a precise and ''real-time'' endoscopic diagnosis. Recently, new endoscopic techniques such as magnifying endoscopy, narrow band imaging, I-Scan, endocytoscopy and endomicroscopy help focus examination of the stomach to diagnose disease in a time-efficient manner, and the analysis of mucosal surface details is beginning to resemble histologic examination. The new detailed images have enabled endoscopists to observe microscopic structures, such as gastric pit patterns, microvessels and cell morphology. Accordingly, endoscopic prediction of H. pylori infection is possible by analysis of surface architecture of the mucosa, which influences the clinical management. These endoscopic techniques might lead us to easier diagnosis and treatment of H. pylori-related diseases.
    World journal of gastroenterology : WJG. 07/2014; 20(28):9314-9320.

Full-text

Download
4 Downloads