Systematic review and meta-analysis: Artificial intelligence for the diagnosis of gastric precancerous lesions and Helicobacter pylori infection

The Role of Screening and Early Detection in Upper Gastrointestinal Cancers

Upper gastrointestinal cancers are among the leading causes of cancer deaths worldwide with exceptionally poor prognosis, which is largely attributable to frequently delayed diagnosis. Although effective screening is critical for early detection, the highly variable incidence of upper gastrointestinal cancers presents challenges, rendering universal screening programs suboptimal in most populations globally. Optimal strategies in regions of modest incidence, such as the United States, require a targeted approach, focused on high-risk individuals based on demographic, familial, and clinicopathologic risk factors. Assessment of underlying precancerous lesions has key implications for risk stratification and informing clinical decisions to improve patient outcomes.

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.

RE.GA.IN.: the Real-world Gastritis Initiative-updating the updates

At the end of the last century, a far-sighted 'working party' held in Sydney, Australia addressed the clinicopathological issues related to gastric inflammatory diseases. A few years later, an international conference held in Houston, Texas, USA critically updated the seminal Sydney classification. In line with these initiatives, Kyoto Global Consensus Report, flanked by the Maastricht-Florence conferences, added new clinical evidence to the gastritis clinicopathological puzzle.The most relevant topics related to the gastric inflammatory diseases have been addressed by the Real-world Gastritis Initiative (RE.GA.IN.), from disease definitions to the clinical diagnosis and prognosis. This paper reports the conclusions of the RE.GA.IN. consensus process, which culminated in Venice in November 2022 after more than 8 months of intense global scientific deliberations. A forum of gastritis scholars from five continents participated in the multidisciplinary RE.GA.IN. consensus. After lively debates on the most controversial aspects of the gastritis spectrum, the RE.GA.IN. Faculty amalgamated complementary knowledge to distil patient-centred, evidence-based statements to assist health professionals in their real-world clinical practice. The sections of this report focus on: the epidemiology of gastritis; Helicobacter pylori as dominant aetiology of environmental gastritis and as the most important determinant of the gastric oncogenetic field; the evolving knowledge on gastric autoimmunity; the clinicopathological relevance of gastric microbiota; the new diagnostic horizons of endoscopy; and the clinical priority of histologically reporting gastritis in terms of staging. The ultimate goal of RE.GA.IN. was and remains the promotion of further improvement in the clinical management of patients with gastritis.

The investigation of volatile organic compounds in diagnosing (early) esophageal squamous cell carcinoma and gastric adenocarcinoma

PURPOSE

The diagnosis of upper gastrointestinal cancer (UGIC) and early UGIC is currently based on endoscopy and histopathology. In this study, we aimed to explore whether intraluminal and exhaled volatile organic compounds (VOCs) could be used to diagnose (early) esophageal squamous cell carcinoma (ESCC) and gastric adenocarcinoma (GC).

METHODS

We prospectively recruited 259 patients and first collected intraluminal gas simples directly from upper GI tract via our designed device after passing endoscopic biopsy channel and collected exhaled gas samples in pairs.

RESULTS

509 gas samples were totally collected and VOCs composed by peak compounds detected by gas chromatography-mass spectrometry (GC-MS) were used to train and test Multilayer Perceptron Network (MPN) for discrimination. Intraluminal and exhaled gas had more than 0.95 area under the curve (AUC) to discriminate UGIC (ESCC and GC) and early UGIC from benign control with different VOCs compositions.

CONCLUSION

Both intraluminal and exhaled VOCs had cancer-specific compositions to accurately discriminate early UGIC and UGIC, and the ability of intraluminal VOCs was better than that of exhaled VOCs. These suggested the potential role of VOCs in diagnosing and screening early UGIC and UGIC in the future.

Gastric Intestinal Metaplasia: Challenges and the Opportunity for Precision Prevention

GIM is a persistent, premalignant lesion whereby gastric mucosa is replaced by metaplastic mucosa resembling intestinal tissue, arising in the setting of chronic inflammation, particularly in the context of Helicobacter pylori. While the overall rates of progression to gastric adenocarcinoma are low, estimated at from 0.25 to 2.5%, there are features that confer a much higher risk and warrant follow-up. In this review, we collate and summarise the current knowledge regarding the pathogenesis of GIM, and the clinical, endoscopic and histologic risk factors for cancer. We examine the current state-of-practice with regard to the diagnosis and management of GIM, which varies widely in the published guidelines and in practice. We consider the emerging evidence in population studies, artificial intelligence and molecular markers, which will guide future models of care. The ultimate goal is to increase the detection of early gastric dysplasia/neoplasia that can be cured while avoiding unnecessary surveillance in very low-risk individuals.

Development and validation of a convolutional neural network model for diagnosing Helicobacter pylori infections with endoscopic images: a multicenter study

BACKGROUND AND AIMS

Insufficient validation limits the generalizability of deep learning in diagnosing Helicobacter pylori infection with endoscopic images. The aim of this study was to develop a deep learning model for the diagnosis of H pylori infection using endoscopic images and validate the model with internal and external datasets.

METHODS

A convolutional neural network (CNN) model was developed based on a training dataset comprising 13,403 endoscopic images from 952 patients who underwent endoscopy at Seoul National University Hospital Gangnam Center. Internal validation was performed using a separate dataset comprised of images of 411 individuals of Korean descent and 131 of non-Korean descent. External validation was performed with the images of 160 patients in Gangnam Severance Hospital. Gradient-weighted class activation mapping was performed to visually explain the model.

RESULTS

In predicting H pylori ever-infected status, the sensitivity, specificity, and accuracy of internal validation for people of Korean descent were .96 (95% confidence interval [CI], .93-.98), .90 (95% CI, .85-.95), and .94 (95% CI, .91-.96), respectively. In the internal validation for people of non-Korean descent, the sensitivity, specificity, and accuracy in predicting H pylori ever-infected status were .92 (95% CI, .86-.98), .79 (95% CI, .67-.91), and .88 (95% CI, .82-.93), respectively. In the external validation cohort, sensitivity, specificity, and accuracy were .86 (95% CI, .80-.93), .88 (95% CI, .79-.96), and .87 (95% CI, .82-.92), respectively, when performing 2-group categorization. Gradient-weighted class activation mapping showed that the CNN model captured the characteristic findings of each group.

CONCLUSIONS

This CNN model for diagnosing H pylori infection showed good overall performance in internal and external validation datasets, particularly in categorizing patients into the never- versus ever-infected groups.

Controlling Gastric Cancer in a World of Heterogeneous Risk

Gastric cancer (GC) is a leading cause of global mortality but also a cancer whose footprint is highly unequal. This review aims to define global disease epidemiology, critically appraise strategies of prevention and disease attenuation, and assess how these strategies could be applied to improve outcomes from GC in a world of variable risk and disease burden. Strategies of primary prevention focus on improving the detection and eradication of the main environmental risk factor, Helicobacter pylori. In certain countries of high incidence, endoscopic or radiographic screening of the asymptomatic general population has been adopted as a means of secondary prevention. By contrast, identification and targeted surveillance of individuals with precancerous lesions (such as intestinal metaplasia) is being increasingly embraced in nations of low incidence. This review also highlights existing knowledge gaps in GC prevention as well as the role of emerging technologies for early detection and risk stratification.

Application of artificial intelligence in the endoscopic diagnosis of early gastric cancer, atrophic gastritis, and Helicobacter pylori infection

Gastric cancer (GC) is one of the most serious health problems worldwide. Chronic atrophic gastritis (CAG) is most commonly caused by Helicobacter pylori (H. pylori) infection. Currently, endoscopic detection of early gastric cancer (EGC) and CAG remains challenging for endoscopists, and the diagnostic accuracy of H. pylori infection by endoscopy is approximately 70%. Artificial intelligence (AI) can assist endoscopic diagnosis including detection, prediction of depth of invasion, boundary delineation, and anatomical location of EGC, and has achievable diagnostic ability even comparable to experienced endoscopists. In this review we summarized various AI-assisted systems in the diagnosis of EGC, CAG, and H. pylori infection.

Endoscopic Grading of Gastric Intestinal Metaplasia Using Magnifying and Nonmagnifying Narrow-Band Imaging Endoscopy

Several endoscopic findings obtained by magnifying image-enhanced endoscopy (IEE) are reportedly correlated with gastric intestinal metaplasia (IM); however, the differences between magnifying and nonmagnifying IEE for the diagnosis of gastric IM remain unknown. This study included 100 consecutive patients who underwent narrow-band imaging endoscopy. Four areas of the stomach were evaluated using nonmagnifying and magnifying IEE. Light-blue crest (LBC), white opaque substance (WOS), and endoscopic grading of the gastric IM (EGGIM) were assessed. The concordance rates between nonmagnifying and magnifying IEE were 80.5% for LBC and 93.3% for WOS. The strength of agreement between each observation technique showed good reproducibility, with a kappa value of 0.69 and 0.83 for LBC and WOS, respectively. The individual EGGIM score indicated a good correlation between nonmagnifying and magnifying IEE (concordance rate, 75%; kappa value, 0.67). The prevalence of a high EGGIM score in patients with and without gastric cancer (GC) showed a significant difference both with nonmagnifying IEE (odds ratio (OR), 3.3; 95% confidence interval (CI), 1.2-9.0), and magnifying IEE (OR, 3.1; 95% CI, 1.1-8.9). Nonmagnifying IEE has the potential to stratify the individual risk of GC, similar to magnifying IEE, warranting further investigation with histological assessment.

Detection and Treatment of Helicobacter pylori: Problems and Advances

Helicobacter pylori (H. pylori) infection is chronic and etiologically linked to gastric cancer (GC) derived from gastric epithelium. The potential mechanism is complex, covering chronic inflammation, epithelial senescence, NF-κB activation, the cytotoxin-associated gene A protein translocation, and related abnormal signaling pathways. In clinical practice, the test-and-treat strategy, endoscopy-based strategy, and (family-based) screen-and-treat strategy are recommended to detect H. pylori and prevent GC. It has been demonstrated that the decreasing annual incidence of GC is largely attributable to the management of H. pylori. This study reviews the current clinical practice of H. pylori on the detection and eradication, alternative treatment strategies, and related problems and advances, and hopes to contribute to the better clinical management of H. pylori.

Pernicious Anemia: The Hematological Presentation of a Multifaceted Disorder Caused by Cobalamin Deficiency

Pernicious anemia is still a neglected disorder in many medical contexts and is underdiagnosed in many patients. Pernicious anemia is linked to but different from autoimmune gastritis. Pernicious anemia occurs in a later stage of autoimmune atrophic gastritis when gastric intrinsic factor deficiency and consequent vitamin B₁₂ deficiency may occur. The multifaceted nature of pernicious anemia is related to the important role of cobalamin, which, when deficient, may lead to several dysfunctions, and thus, the proteiform clinical presentations of pernicious anemia. Indeed, pernicious anemia may lead to potentially serious long-term complications related to micronutrient deficiencies and their consequences and the development of gastric cancer and type 1 gastric neuroendocrine tumors. When not recognized in a timely manner or when pernicious anemia is diagnosed with delay, these complications may be potentially life-threatening and sometimes irreversible. The current review aimed to focus on epidemiology, pathogenesis, and clinical presentations of pernicious anemia in an attempt to look beyond borders of medical specialties. It aimed to focus on micronutrient deficiencies besides the well-known vitamin B₁₂ deficiency, the diagnostic approach for pernicious anemia, its long-term complications and optimal clinical management, and endoscopic surveillance of patients with pernicious anemia.