Clinical significance and influencing factors of linked color imaging technique in real-time diagnosis of active Helicobacter pylori infection

Endoscopic appearances of gastric mucosa in different endoscopic models according to H. pylori infection status

Background

H. pylori infection has been recognized as a type 1 carcinogen of the gastric malignancy; therefore, early diagnosis and treatment are the corner stone of eradication. Recent findings have also shown that atrophy and intestinal metaplasia remain after successful eradication, which moderately increases the risk of gastric cancer compared with those who have never infected, so the evaluation of gastric mucosa during gastroscopy is important.

Aims

We aimed to describe and summarize the reliable literature and proposed features of H. pylori infection status and gastritis in research on newly developed endoscopic models that influence clinical practice. In the result, conventional white light endoscopic, image-enhanced endoscopic models, and studies related to the Kyoto classification of gastritis were searched and reviewed.

Results

Kyoto classification of gastritis and modified Kyoto classification scoring model for gastritis using conventional white light image (CWLI) endoscopy is an effective tool for evaluating current H. pylori infection status, past infections, eradications, noninfections, and pre-cancerous conditions. This model is widely used, low cost, and time-efficient, and is supported by recent findings. Advanced image-enhanced endoscopic models combined with magnifying endoscopy provide more clear endoscopic features for H. pylori infection status and early gastric cancer.

Conclusion

According to H pylori infection status, endoscopic prediction of gastric mucosal surface architecture analysis is possible, which influences clinical management. Endoscopic models might lead us to accurate and early diagnose of H. pylori infection status and may not be effective only for the eradication of H. pylori infection but also in the detection of early gastric cancer status.

Novel endoscopic techniques for the diagnosis of gastric Helicobacter pylori infection: a systematic review and network meta-analysis

Objective

This study aimed to conduct a network meta-analysis to compare the diagnostic efficacy of diverse novel endoscopic techniques for detecting gastric Helicobacter pylori infection.

Methods

From inception to August 2023, literature was systematically searched across Pubmed, Embase, and Web of Science databases. Cochrane's risk of bias tool assessed the methodological quality of the included studies. Data analysis was conducted using the R software, employing a ranking chart to determine the most effective diagnostic method comprehensively. Convergence analysis was performed to assess the stability of the results.

Results

The study encompassed 36 articles comprising 54 observational studies, investigating 14 novel endoscopic techniques and involving 7,230 patients diagnosed with gastric H. pylori infection. Compared with the gold standard, the comprehensive network meta-analysis revealed the superior diagnostic performance of two new endoscopic techniques, Magnifying blue laser imaging endoscopy (M-BLI) and high-definition magnifying endoscopy with i-scan (M-I-SCAN). Specifically, M-BLI demonstrated the highest ranking in both sensitivity (SE) and positive predictive value (PPV), ranking second in negative predictive value (NPV) and fourth in specificity (SP). M-I-SCAN secured the top position in NPV, third in SE and SP, and fifth in PPV.

Conclusion

After thoroughly analyzing the ranking chart, we conclude that M-BLI and M-I-SCAN stand out as the most suitable new endoscopic techniques for diagnosing gastric H. pylori infection.

Systematic review registration

https://inplasy.com/inplasy-2023-11-0051/, identifier INPLASY2023110051.

The Diagnostic Performance of Linked Color Imaging Compared to White Light Imaging in Endoscopic Diagnosis of Helicobacter pylori Infection: A Systematic Review and Meta-Analysis

Background/Aims

Recognizing Helicobacter pylori infection during endoscopy is important because it can lead to the performance of confirmatory testing. Linked color imaging (LCI) is an image enhancement technique that can improve the detection of gastrointestinal lesions. The purpose of this study was to compare LCI to conventional white light imaging (WLI) in the endoscopic diagnosis of H. pylori infection.

Methods

We conducted a comprehensive literature search using PubMed, Embase, and the Cochrane Library. All studies evaluating the diagnostic performance of LCI or WLI in the endoscopic diagnosis of H. pylori were eligible. Studies on magnifying endoscopy, chromoendoscopy, and artificial intelligence were excluded.

Results

Thirty-four studies were included in this meta-analysis, of which 32 reported the performance of WLI and eight reported the performance of LCI in diagnosing H. pylori infection. The pooled sensitivity and specificity of WLI in the diagnosis of H. pylori infection were 0.528 (95% confidence interval [CI], 0.517 to 0.540) and 0.821 (95% CI, 0.811 to 0.830), respectively. The pooled sensitivity and specificity of LCI in the diagnosis of H. pylori were 0.816 (95% CI, 0.790 to 0.841) and 0.868 (95% CI, 0.850 to 0.884), respectively. The pooled diagnostic odds ratios of WLI and LCI were 15.447 (95% CI, 8.225 to 29.013) and 31.838 (95% CI, 15.576 to 65.078), respectively. The areas under the summary receiver operating characteristic curves of WLI and LCI were 0.870 and 0.911, respectively.

Conclusions

LCI showed higher sensitivity in the endoscopic diagnosis of H. pylori infection than standard WLI.

Simultaneous detection of Helicobacter pylori infection comparing between white light and image-enhanced endoscopy

BACKGROUND

Helicobacter pylori (H. pylori) is associated with gastric cancer. Early and accurate diagnosis of H. pylori infection can reduce risk of gastric cancer. Conventional white light imaging (WLI) and image-enhanced endoscopic (IEE) techniques such as narrow-band imaging (NBI), linked color imaging (LCI) and blue laser imaging (BLI) plays pivotal role in H. pylori diagnosis. This study aimed to determine diagnostic performance of real-time endoscopy between WLI and other IEE techniques for diagnosis of H. pylori infection.

METHODS

This prospective study compared endoscopic images by gastroscopy using WLI and IEE techniques (LCI, Magnifying-BLI, and Magnifying-NBI) at Thammasat University Hospital, Thailand between January 2020, and July 2021. All participants underwent gastroscopy. Three biopsies at gastric antrum and two biopsies at body were obtained for H.pylori diagnosis. H. pylori infection was defined as a positive test of either one of the following tests: rapid urease test, histopathology, H. pylori culture.

RESULTS

Of 167 dyspeptic patients undergoing gastroscopy, 100 were enrolled in this study. Overall H. pylori infection was 40%. Patients had the mean age of 59.1 years and 53% were males. Enlarged gastric folds and antral nodularity can predict H. pylori infection with 100% PPV, while fundic gland polyps and red streak provided 100% PPV for exclusion of H. pylori infection on WLI. Sensitivity, specificity, PPV, NPV and accuracy for diagnosis of H. pylori infection for WLI were 80%, 71.7%, 65.3%, 84.3% and 75% respectively, while those for LCI were 90%, 70%, 66.7%, 91.3% and 78% respectively. M-NBI and M-BLI endoscopy demonstrated elongated pits in H. pylori-positive patients. Sensitivity, specificity, PPV, NPV and accuracy for M-BLI were 95%, 80%, 76%, 96% and 86% respectively, whereas those for M-NBI were 92.5%, 86.7%, 82.2%, 94.6% and 89% respectively. Sensitivity of M-BLI was better than WLI, while sensitivities of LCI and M-NBI were also numerically higher than WLI without statistical difference (M-BLI 95%vs.WLI 80%, p = 0.03; M-NBI 92.5%vs.WLI 80%, p = 0.13; LCI 90%vs.WLI 80%, p = 0.22). Sensitivities of all IEE modes were not different from one another (LCI 90%vs.M-BLI 95%, p = 0.50; LCI 90%vs.M-NBI 92.5%, p = 1.00, M-BLI 95%vs.M-NBI 92.5%, p = 1.00).

CONCLUSIONS

M-BLI significantly improved sensitivity of real-time endoscopic diagnosis of H. pylori infection compared with WLI. Enlarged gastric folds and antral nodularity could be reliable predictors for H. pylori infection, while fundic gland polyps and red streak could be important endoscopic findings for H. pylori-negative mucosa.

Clinical usefulness of linked color imaging in identifying Helicobacter pylori infection: A systematic review and meta-analysis

BACKGROUND

Accurate diagnosis of Helicobacter pylori (H. pylori) infection status is a crucial premise for eradication therapy, as well as evaluation of risk for gastric cancer. Recent progress on imaging enhancement endoscopy (IEE) made it possible to not only detect precancerous lesions and early gastrointestinal cancers but also to predict H. pylori infection in real time. As a novel IEE modality, linked color imaging (LCI) has exhibited its value on diagnosis of lesions of gastric mucosa through emphasizing minor differences of color tone.

AIM

To compare the efficacy of LCI for H. pylori active infection vs conventional white light imaging (WLI).

METHODS

PubMed, Embase, Embase and Cochrane Library were searched up to the end of April 11, 2022. The random-effects model was adopted to calculate the diagnostic efficacy of LCI and WLI. The calculation of sensitivity, specificity, and likelihood ratios were performed; symmetric receiver operator characteristic (SROC) curves and the areas under the SROC curves were computed. Quality of the included studies was chosen to assess using the quality assessment of diagnostic accuracy studies-2 tool.

RESULTS

Seven original studies were included in this study. The pooled sensitivity, specificity, positive likelihood rate, and negative likelihood rate of LCI for the diagnosis of H. pylori infection of gastric mucosa were 0.85 [95% confidence interval (CI): 0.76-0.92], 0.82 (95%CI: 0.78-0.85), 4.71 (95%CI: 3.7-5.9), and 0.18 (95%CI: 0.10-0.31) respectively, with diagnostic odds ratio = 26 (95%CI: 13-52), SROC = 0.87 (95%CI: 0.84-0.90), which showed superiority of diagnostic efficacy compared to WLI.

CONCLUSION

Our results showed LCI can improve efficacy of diagnosis on H. pylori infection, which represents a useful endoscopic evaluation modality for clinical practice.

Advances on diagnosis of Helicobacter pylori infections

The association of Helicobacter pylori to several gastric diseases, such as chronic gastritis, peptic ulcer disease, and gastric cancer, and its high prevalence worldwide, raised the necessity to use methods for a proper and fast diagnosis and monitoring the pathogen eradication. Available diagnostic methods can be classified as invasive or non-invasive, and the selection of the best relies on the clinical condition of the patient, as well as on the sensitivity, specificity, and accessibility of the diagnostic test. This review summarises all diagnostic methods currently available, including the invasive methods: endoscopy, histology, culture, and molecular methods, and the rapid urease test (RUT), as well as the non-invasive methods urea breath test (UBT), serological assays, biosensors, and microfluidic devices and the stool antigen test (SAT). Moreover, it lists the diagnostic advantages and limitations, as well as the main advances for each methodology. In the end, research on the development of new diagnostic methods, such as bacteriophage-based H. pylori diagnostic tools, is also discussed.

Linked Color Imaging for Stomach

Image-enhanced endoscopy (IEE) plays an important role in the detection and further examination of gastritis and early gastric cancer (EGC). Linked color imaging (LCI) is also useful for detecting and evaluating gastritis, gastric intestinal metaplasia as a pre-cancerous lesion, and EGC. LCI provides a clear excellent endoscopic view of the atrophic border and the demarcation line under various conditions of gastritis. We could recognize gastritis as the lesions of the diffuse redness to purple color area with LCI. On the other hand, EGCs are recognized as the lesions of the orange-red, orange, or orange-white color area in the lesion of the purple color area, which is the surround atrophic mucosa with LCI. With further prospective randomized studies, we will be able to evaluate the diagnosis ability for EGC by IEE, and it will be necessary to evaluate the role of WLI/IEE and the additional effects of the diagnostic ability by adding IEE to WLI in future.

An explainable artificial intelligence system for diagnosing Helicobacter Pylori infection under endoscopy: a case-control study

Background

Changes in gastric mucosa caused by Helicobacter pylori (H. pylori) infection affect the observation of early gastric cancer under endoscopy. Although previous researches reported that computer-aided diagnosis (CAD) systems have great potential in the diagnosis of H. pylori infection, their explainability remains a challenge.

Objective

We aim to develop an explainable artificial intelligence system for diagnosing H. pylori infection (EADHI) and giving diagnostic basis under endoscopy.

Design

A case-control study.

Methods

We retrospectively obtained 47,239 images from 1826 patients between 1 June 2020 and 31 July 2021 at Renmin Hospital of Wuhan University for the development of EADHI. EADHI was developed based on feature extraction combining ResNet-50 and long short-term memory networks. Nine endoscopic features were used for H. pylori infection. EADHI's performance was evaluated and compared to that of endoscopists. An external test was conducted in Wenzhou Central Hospital to evaluate its robustness. A gradient-boosting decision tree model was used to examine the contributions of different mucosal features for diagnosing H. pylori infection.

Results

The system extracted mucosal features for diagnosing H. pylori infection with an overall accuracy of 78.3% [95% confidence interval (CI): 76.2-80.3]. The accuracy of EADHI for diagnosing H. pylori infection (91.1%, 95% CI: 85.7-94.6) was significantly higher than that of endoscopists (by 15.5%, 95% CI: 9.7-21.3) in internal test. And it showed a good accuracy of 91.9% (95% CI: 85.6-95.7) in external test. Mucosal edema was the most important diagnostic feature for H. pylori positive, while regular arrangement of collecting venules was the most important H. pylori negative feature.

Conclusion

The EADHI discerns H. pylori gastritis with high accuracy and good explainability, which may improve the trust and acceptability of endoscopists on CADs.

Plain language summary

An explainable AI system for Helicobacter pylori with good diagnostic performance Helicobacter pylori (H. pylori) is the main risk factor for gastric cancer (GC), and changes in gastric mucosa caused by H. pylori infection affect the observation of early GC under endoscopy. Therefore, it is necessary to identify H. pylori infection under endoscopy. Although previous research showed that computer-aided diagnosis (CAD) systems have great potential in H. pylori infection diagnosis, their generalization and explainability are still a challenge. Herein, we constructed an explainable artificial intelligence system for diagnosing H. pylori infection (EADHI) using images by case. In this study, we integrated ResNet-50 and long short-term memory (LSTM) networks into the system. Among them, ResNet50 is used for feature extraction, LSTM is used to classify H. pylori infection status based on these features. Furthermore, we added the information of mucosal features in each case when training the system so that EADHI could identify and output which mucosal features are contained in a case. In our study, EADHI achieved good diagnostic performance with an accuracy of 91.1% [95% confidence interval (CI): 85.7-94.6], which was significantly higher than that of endoscopists (by 15.5%, 95% CI: 9.7-21.3%) in internal test. In addition, it showed a good diagnostic accuracy of 91.9% (95% CI: 85.6-95.7) in external tests. The EADHI discerns H. pylori gastritis with high accuracy and good explainability, which may improve the trust and acceptability of endoscopists on CADs. However, we only used data from a single center to develop EADHI, and it was not effective in identifying past H. pylori infection. Future, multicenter, prospective studies are needed to demonstrate the clinical applicability of CADs.

Vitamins and Helicobacter pylori: An Updated Comprehensive Meta-Analysis and Systematic Review

Background

Over recent decades, epidemiological studies have shown relationships between vitamins and Helicobacter pylori (H. pylori) infection and eradication, but the results are controversial.

Methods

A comprehensive meta-analysis and systematic review were conducted to clarify the relationships between common types of vitamins and H. pylori. We applied meta-regression, subgroup analysis and sensitivity analysis to obtain available evidence. Articles published from January 1991 to June 2021 in PubMed, EMBASE, and the Cochrane Library were searched.

Results

In total, we identified 48 studies. The results indicate that H. pylori -positive patients had lower serum vitamin B₁₂ [standardized mean difference (SMD) = −0.30; 95% confidence interval (CI): −0.53 – −0.08], folate (SMD = −0.69; 95% CI: −1.34 – −0.04), vitamin C (SMD = −0.37; 95%CI: −0.57 – −0.18) and vitamin D (SMD = −0.34; 95% CI: −0.49 – −0.18) levels than H. pylori-negative patients. Patients in which H. pylori had been successfully eradicated had higher serum vitamin D levels (SMD = 1.37; 95% CI: 0.37–2.38) than in patients in which eradication had been unsuccessful. The serum vitamin B₁₂ levels of H. pylori-positive patients improved after successful H. pylori eradication therapy (SMD = 1.85; 95% CI: 0.81–2.90), and antioxidant vitamin supplementation to an H. pylori eradication regimen improved the eradication rate (risk ratio = 1.22; 95% CI: 1.02–1.44 for per-protocol analysis; risk ratio = 1.25; 95% CI: 1.06–1.47 for intention-to-treat analysis).

Conclusions

H. pylori infections decrease the serum levels of several types of vitamins, eradication of H. pylori could rescue its adverse effects, and antioxidant vitamin supplementation may improve the H. pylori eradication rate.

Systematic Review Registration

identifier: CRD42021268127.

Diagnosis of Helicobacter pylori Infection and Recent Advances

BACKGROUND

Helicobacter pylori (H. pylori) infects approximately 50% of the world population. Its infection is associated with gastropathies, extra-gastric digestive diseases, and diseases of other systems. There is a canonical process from acute-on-chronic inflammation, chronic atrophic gastritis (CAG), intestinal metaplasia (IM), dysplasia, and intraepithelial neoplasia, eventually to gastric cancer (GC). H. pylori eradication abolishes the inflammatory response and early treatment prevents the progression to preneoplastic lesions.

METHODS

the test-and-treat strategy, endoscopy-based strategy, and screen-and-treat strategy are recommended to prevent GC based on risk stratification, prevalence, and patients' clinical manifestations and conditions. Challenges contain false-negative results, increasing antibiotic resistance, decreasing eradication rate, and poor retesting rate. Present diagnosis methods are mainly based on invasive endoscopy and noninvasive laboratory testing.

RESULTS

to improve the accuracy and effectiveness and reduce the missed diagnosis, some advances were achieved including newer imaging techniques (such as image-enhanced endoscopy (IEE), artificial intelligence (AI) technology, and quantitative real-time polymerase chain reaction (qPCR) and digital PCR (dPCR).

CONCLUSION

in the article, we summarized the diagnosis methods of H. pylori infection and recent advances, further finding out the opportunities in challenges.

What Is New in Helicobacter pylori Diagnosis. An Overview

Helicobacter pylori infection remains one of the most prevalent infections worldwide, especially in low-resource countries, and the major risk factor for peptic ulcer and gastric cancer. The “test-and-treat” strategy is recommended by several guidelines and consensus. The choice of testing method is based on patient age, presence of alarm signs and/or symptoms, use of non-steroidal anti-inflammatory drugs, as well as local availability, test reliability, and cost. Culture is the gold standard to detect H. pylori and, possibly, to perform susceptibility testing, however, it requires upper endoscopy and dedicated labs. Recent advances in molecular biology have provided new strategies in detecting infection and antimicrobial resistance without invasive tests. In this review we attempt to offer a comprehensive panorama on the new diagnostic tools and their potential use in clinical settings, in order to accomplish specific recommendations.

Review: Diagnosis of Helicobacter pylori infection

New imaging techniques are still the topic of many evaluations for both the diagnosis of Helicobacter pylori gastritis and the detection of early gastric cancer. Concerning invasive tests, there were studies on the reuse of the rapid urease test material for other tests, and a novel fluorescent method to be used for histology but with limited sensitivity. Progress occurred essentially in the molecular methods area, especially next-generation sequencing which is applied to detect both H pylori and the mutations associated with antibiotic resistance. For non-invasive tests, a few studies have been published on the validity of breath collection bags, the shortening of the testing time, the performance of different analysers or the added value of citric acid in the protocol. The accuracy of serological immunochromatographic tests is also improving. Multiplex serology detecting antibodies to certain proteins allows confirmation of a current infection. Dried blood spots can be used to collect and store blood without a loss of accuracy. Finally, the serum antibody titer can be useful in predicting the risk of gastric cancer. Several stool antigen tests were evaluated with good results, and a novel test using immunomagnetic beads coated with monoclonal antibodies is potentially interesting. PCR detection in stools can also be effective but needs an efficient DNA extraction method. The use of easyMAG^® (bioMérieux) combined with Amplidiag® H pylori + ClariR (Mobidiag) appears to be powerful.