We aimed to conduct a systematic review and meta-analysis to assess the value of image-enhanced endoscopy including blue laser imaging (BLI), linked color imaging, narrow-band imaging (NBI), and texture and color enhancement imaging to detect and diagnose gastric cancer (GC) compared to that of white-light imaging (WLI).

Studies meeting the inclusion criteria were identified through PubMed, Cochrane Library, and Japan Medical Abstracts Society databases searches. The pooled risk ratio for dichotomous variables was calculated using the random-effects model to assess the GC detection between WLI and image-enhanced endoscopy. A random-effects model was used to calculate the overall diagnostic performance of WLI and magnifying image-enhanced endoscopy for GC.

Sixteen studies met the inclusion criteria. The detection rate of GC was significantly improved in linked color imaging compared with that in WLI (risk ratio, 2.20; 95% confidence interval [CI], 1.39-3.25; p < 0.01) with mild heterogeneity. Magnifying endoscopy with NBI (ME-NBI) obtained a pooled sensitivity, specificity, and area under the summary receiver operating curve of 0.84 (95 % CI, 0.80-0.88), 0.96 (95 % CI, 0.94-0.97), and 0.92, respectively. Similarly, ME-BLI showed a pooled sensitivity, specificity, and area under the curve of 0.81 (95 % CI, 0.77-0.85), 0.85 (95 % CI, 0.82-0.88), and 0.95, respectively. The diagnostic efficacy of ME-NBI/BLI for GC was evidently high compared to that of WLI, However, significant heterogeneity among the NBI studies still existed.

Our meta-analysis showed a high detection rate for linked color imaging and a high diagnostic performance of ME-NBI/BLI for GC compared to that with WLI.

At a population level, the European Society of Gastrointestinal Endoscopy (ESGE), the European Helicobacter and Microbiota Study Group (EHMSG), and the European Society of Pathology (ESP) suggest endoscopic screening for gastric cancer (and precancerous conditions) in high-risk regions (age-standardized rate [ASR] > 20 per 100 000 person-years) every 2 to 3 years or, if cost-effectiveness has been proven, in intermediate risk regions (ASR 10-20 per 100 000 person-years) every 5 years, but not in low-risk regions (ASR < 10).ESGE/EHMSG/ESP recommend that irrespective of country of origin, individual gastric risk assessment and stratification of precancerous conditions is recommended for first-time gastroscopy. ESGE/EHMSG/ESP suggest that gastric cancer screening or surveillance in asymptomatic individuals over 80 should be discontinued or not started, and that patients' comorbidities should be considered when treatment of superficial lesions is planned.ESGE/EHMSG/ESP recommend that a high quality endoscopy including the use of virtual chromoendoscopy (VCE), after proper training, is performed for screening, diagnosis, and staging of precancerous conditions (atrophy and intestinal metaplasia) and lesions (dysplasia or cancer), as well as after endoscopic therapy. VCE should be used to guide the sampling site for biopsies in the case of suspected neoplastic lesions as well as to guide biopsies for diagnosis and staging of gastric precancerous conditions, with random biopsies to be taken in the absence of endoscopically suspected changes. When there is a suspected early gastric neoplastic lesion, it should be properly described (location, size, Paris classification, vascular and mucosal pattern), photodocumented, and two targeted biopsies taken.ESGE/EHMSG/ESP do not recommend routine performance of endoscopic ultrasonography (EUS), computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET)-CT prior to endoscopic resection unless there are signs of deep submucosal invasion or if the lesion is not considered suitable for endoscopic resection.ESGE/EHMSG/ESP recommend endoscopic submucosal dissection (ESD) for differentiated gastric lesions clinically staged as dysplastic (low grade and high grade) or as intramucosal carcinoma (of any size if not ulcerated or ≤ 30 mm if ulcerated), with EMR being an alternative for Paris 0-IIa lesions of size ≤ 10 mm with low likelihood of malignancy.ESGE/EHMSG/ESP suggest that a decision about ESD can be considered for malignant lesions clinically staged as having minimal submucosal invasion if differentiated and ≤ 30 mm; or for malignant lesions clinically staged as intramucosal, undifferentiated and ≤ 20 mm; and in both cases with no ulcerative findings.ESGE/EHMSG/ESP recommends patient management based on the following histological risk after endoscopic resection: Curative/very low-risk resection (lymph node metastasis [LNM] risk < 0.5 %-1 %): en bloc R0 resection; dysplastic/pT1a, differentiated lesion, no lymphovascular invasion, independent of size if no ulceration and ≤ 30 mm if ulcerated. No further staging procedure or treatment is recommended.Curative/low-risk resection (LNM risk < 3 %): en bloc R0 resection; lesion with no lymphovascular invasion and: a) pT1b, invasion ≤ 500 µm, differentiated, size ≤ 30 mm; or b) pT1a, undifferentiated, size ≤ 20 mm and no ulceration. Staging should be completed, and further treatment is generally not necessary, but a multidisciplinary discussion is required. Local-risk resection (very low risk of LNM but increased risk of local persistence/recurrence): Piecemeal resection or tumor-positive horizontal margin of a lesion otherwise meeting curative/very low-risk criteria (or meeting low-risk criteria provided that there is no submucosal invasive tumor at the resection margin in the case of piecemeal resection or tumor-positive horizontal margin for pT1b lesions [invasion ≤ 500 µm; well-differentiated; size ≤ 30 mm, and VM0]). Endoscopic surveillance/re-treatment is recommended rather than other additional treatment. High-risk resection (noncurative): Any lesion with any of the following: (a) a positive vertical margin (if carcinoma) or lymphovascular invasion or deep submucosal invasion (> 500 µm from the muscularis mucosae); (b) poorly differentiated lesions if ulceration or size > 20 mm; (c) pT1b differentiated lesions with submucosal invasion ≤ 500 µm with size > 30 mm; or (d) intramucosal ulcerative lesion with size > 30 mm. Complete staging and strong consideration for additional treatments (surgery) in multidisciplinary discussion.ESGE/EHMSG/ESP suggest the use of validated endoscopic classifications of atrophy (e. g. Kimura-Takemoto) or intestinal metaplasia (e. g. endoscopic grading of gastric intestinal metaplasia [EGGIM]) to endoscopically stage precancerous conditions and stratify the risk for gastric cancer.ESGE/EHMSG/ESP recommend that biopsies should be taken from at least two topographic sites (2 biopsies from the antrum/incisura and 2 from the corpus, guided by VCE) in two separate, clearly labeled vials. Additional biopsy from the incisura is optional.ESGE/EHMSG/ESP recommend that patients with extensive endoscopic changes (Kimura C3 + or EGGIM 5 +) or advanced histological stages of atrophic gastritis (severe atrophic changes or intestinal metaplasia, or changes in both antrum and corpus, operative link on gastritis assessment/operative link on gastric intestinal metaplasia [OLGA/OLGIM] III/IV) should be followed up with high quality endoscopy every 3 years, irrespective of the individual's country of origin.ESGE/EHMSG/ESP recommend that no surveillance is proposed for patients with mild to moderate atrophy or intestinal metaplasia restricted to the antrum, in the absence of endoscopic signs of extensive lesions or other risk factors (family history, incomplete intestinal metaplasia, persistent H. pylori infection). This group constitutes most individuals found in clinical practice.ESGE/EHMSG/ESP recommend H. pylori eradication for patients with precancerous conditions and after endoscopic or surgical therapy.ESGE/EHMSG/ESP recommend that patients should be advised to stop smoking and low-dose daily aspirin use may be considered for the prevention of gastric cancer in selected individuals with high risk for cardiovascular events.

Global prevention of gastric cancer needs to increase its level of effectiveness. The prevention strategy should include all stages of primary and secondary prevention. The necessary steps to prevent gastric cancer are the following: Maintaining a healthy lifestyle and diet, avoiding smoking and alcohol; serological screening of Helicobacter pylori infections and eradication; serological screening of atrophic gastritis in the population over 45 years of age and identification of severe atrophic gastritis with a high risk of developing gastric cancer; verification of atrophic gastritis and precancerous changes in the gastric mucosa using modern endoscopic (confocal laser endomicroscopy, narrow-spectrum imaging, and magnifying endoscopy) and morphological methods among patients with severe atrophic gastritis who were identified using serological screening; treatment of patients with atrophic gastritis during diagnosis verification; annual endoscopic and morphological monitoring of patients with atrophic gastritis during permanent treatment; annual serological monitoring of patients with atrophic gastritis who refused endoscopic and morphological monitoring; and radical treatment of patients with verified early gastric cancer. Ways to implement the algorithm for the global strategy for the prevention of gastric cancer (protocol of practical recommendations) are: State, government, and municipal programs; departmental programs of health departments; family doctors for patients who have a contract at the initiative of the doctor; family doctors for patients with a contract at the patient's initiative; and within private healthcare system where both doctors and patients can initiate the implementation of algorithm.

The early detection of gastric neoplasms (GNs) leads to favorable treatment outcomes. The latest endoscopic system, EVIS X1, includes third-generation narrow-band imaging (3G-NBI), texture and color enhancement imaging (TXI), and high-definition white-light imaging (WLI). Therefore, this randomized phase II trial aimed to identify the most promising imaging modality for GN detection using 3G-NBI and TXI.

Patients with scheduled surveillance endoscopy after a history of esophageal cancer or GN or preoperative endoscopy for known esophageal cancer or GN were randomly assigned to the 3G-NBI, TXI, or WLI groups. Endoscopic observations were performed to detect new GN lesions, and all suspected lesions were biopsied. The primary endpoint was the GN detection rate during primary observation. Secondary endpoints were the rate of missed GNs, early gastric cancer detection rate, and positive predictive value for a GN diagnosis. The decision rule had a higher GN detection rate between 3G-NBI and TXI, outperforming WLI by >1.0%.

Finally, 901 patients were enrolled and assigned to the 3G-NBI, TXI, and WLI groups (300, 300, and 301 patients, respectively). GN detection rates in the 3G-NBI, TXI, and WLI groups were 7.3, 5.0, and 5.6%, respectively. The rates of missed GNs were 1.0, 0.7, and 1.0%, the detection rates of early gastric cancer were 5.7, 4.0, and 5.6%, and the positive predictive values for the diagnosis of GN were 36.5, 21.3, and 36.8% in the 3G-NBI, TXI, and WLI groups, respectively.

Compared with TXI and WLI, 3G-NBI is a more promising modality for GN detection.

Texture and color enhancement imaging (TXI) may improve the visibility of gastric tumors and allow their early detection. However, few reports have examined the utility of TXI. Between June 2021 and October 2022, 56 gastric tumors in 51 patients undergoing endoscopic submucosal dissection at Fukuchiyama City Hospital were evaluated preoperatively using conventional white light imaging (WLI), narrow-band imaging (NBI), and TXI modes 1 and 2. The color differences of the tumors and surrounding mucosae were evaluated using the CIE 1976 L*a*b color space, Additionally, the visibility scores were scaled. Of the 56 gastric tumors, 45 were early gastric cancers, and 11 were adenomas. Overall, the color difference in TXI mode 1 was considerably higher compared to WLI (16.36 ± 7.05 vs. 10.84 ± 4.05; p < 0.01). Moreover, the color difference in early gastric cancers was considerably higher in TXI mode 1 compared to WLI, whereas no significant difference was found in adenomas. The visibility score in TXI mode 1 was the highest, and it was significantly higher compared to WLI. Regarding adenomas, the visibility score in TXI mode 1 was also significantly higher compared to that in WLI. TXI may provide improved gastric tumor visibility.

Minute gastric cancers (MGCs) have a favorable prognosis, but they are too small to be detected by endoscopy, with a maximum diameter ≤ 5 mm.

To explore endoscopic detection and diagnostic strategies for MGCs.

This was a real-world observational study. The endoscopic and clinicopathological parameters of 191 MGCs between January 2015 and December 2022 were retrospectively analyzed. Endoscopic discoverable opportunity and typical neoplastic features were emphatically reviewed.

All MGCs in our study were of a single pathological type, 97.38% (186/191) of which were differentiated-type tumors. White light endoscopy (WLE) detected 84.29% (161/191) of MGCs, and the most common morphology of MGCs found by WLE was protruding. Narrow-band imaging (NBI) secondary observation detected 14.14% (27/191) of MGCs, and the most common morphology of MGCs found by NBI was flat. Another three MGCs were detected by indigo carmine third observation. If a well-demarcated border lesion exhibited a typical neoplastic color, such as yellowish-red or whitish under WLE and brownish under NBI, MGCs should be diagnosed. The proportion with high diagnostic confidence by magnifying endoscopy with NBI (ME-NBI) was significantly higher than the proportion with low diagnostic confidence and the only visible groups (94.19% > 56.92% > 32.50%, P < 0.001).

WLE combined with NBI and indigo carmine are helpful for detection of MGCs. A clear demarcation line combined with a typical neoplastic color using nonmagnifying observation is sufficient for diagnosis of MGCs. ME-NBI improves the endoscopic diagnostic confidence of MGCs.

There has been no report on a direct comparison between linked color imaging (LCI) and second-generation narrow-band imaging (2G-NBI) for surveillance of epithelial neoplasms in the upper gastrointestinal tract (UGIT). The aim of this study was to verify the superiority of LCI to 2G-NBI for surveillance esophagogastroduodenoscopy and to clarify how each endoscopic system should be used.

This study was conducted as an open-label, two-arm-parallel (1:1), multicenter, randomized controlled trial at six institutions. Patients aged 20-85 years with a treatment history of epithelial neoplasms in the UGIT were recruited. Patients were assigned to a 2G-NBI group and an LCI group, and esophagogastroduodenoscopy was performed with primary image-enhanced endoscopy followed by white light imaging (WLI). The primary endpoint was the detection rate of one or more epithelial neoplasms in the primary image-enhanced endoscopy. A WLI-detected epithelial neoplasm was defined as a lesion that was detected in only WLI.

A total of 372 patients in the 2G-NBI group and 378 patients in the LCI group were analyzed. Epithelial neoplasms in the UGIT were detected by 2G-NBI in 18 patients (4.6%) and were detected by LCI in 20 patients (5.3%) (P = 0.87). WLI-detected epithelial neoplasms were in 11 patients in the 2G-NBI group (3.0%) and in 1 patient in the LCI group (0.27%) (P = 0.003).

Linked color imaging did not show superiority to 2G-NBI for the detection of epithelial neoplasms. Also, the percentage of WLI-detected epithelial neoplasms in primary NBI was significantly higher than that in primary LCI.

We developed three e-learning systems for endoscopists to acquire the necessary skills to improve the diagnosis of early gastric cancer (EGC) and demonstrated their usefulness using randomized controlled trials. The subjects of the three e-learning systems were "detec-tion", "characterization", and "preoperative assessment". The contents of each e-learning system included "technique", "knowledge", and "obtaining experience". All e-learning systems proved useful for endoscopists to learn how to diagnose EGC. Lecture videos describing "the technique" and "the knowledge" can be beneficial. In addition, repeating 100 self-study cases allows learners to gain "experience" and improve their diagnostic skills further. Web-based e-learning systems have more advantages than other teaching methods because the number of participants is unlimited. Histopathological diagnosis is the gold standard for the diagnosis of gastric cancer. Therefore, we developed a comprehensive diagnostic algorithm to standardize the histopathological diagnosis of gastric cancer. Once we have successfully shown that this algorithm is helpful for the accurate histopathological diagnosis of cancer, we will complete a series of e-learning systems designed to assess EGC accurately.

Gastric cancer is a prevalent malignancy that poses a serious threat to global health. Despite advances in medical technologies, screening methods, and public awareness, gastric cancer remains a significant cause of morbidity and mortality worldwide. Early gastric cancer frequently does not present with characteristic symptoms, while advanced stage disease is characterized by a dismal prognosis. As such, early screening in gastric cancer is of great importance. In recent years, advances have been made globally in both clinical and basic research for the screening of early gastric cancer. The current predominant screening methods for early gastric cancer include imaging screening, endoscopic screening and serum biomarker screening. Imaging screening encompasses upper gastrointestinal barium meal, multidimensional spiral computed tomography (MDCT), Magnetic resonance imaging (MRI), and ultrasonography. Endoscopic screening methods include white light endoscopy, chromoendoscopy, computed virtual chromoendoscopy, and other endoscopic techniques like endocytoscopy, confocal laser endomicroscopy, optical coherence tomography and so on. Biomarkers screening involves the assessment of conventional biomarkers such as CEA, CA19-9 and CA72-4 as well as more emerging biomarkers such as peptides (PG, G-17, GCAA, TAAs and others), DNA (cfDNA, DNA methylation, MSI), noncoding RNA (miRNA, lncRNA, circRNA, and tsRNA) and others. Each screening method has its strengths and limitations. This article systematically summarizes worldwide progress and future development of early gastric cancer screening methods to provide new perspectives and approaches for early diagnostic and treatment advancements in gastric cancer worldwide.

Gastric neoplasm of the fundic gland type (GNFG) is a tumor with a good prognosis. However, since it has not been compared with conventional gastric adenocarcinoma (CGA), it is unknown whether it has a good prognosis or requires surveillance after treatment. The purpose of this study was to determine the prognosis and metachronous gastric tumor rates compared with those of CGA.

We conducted a single-center, retrospective, matched-cohort study using our database from January 2010 to December 2021. We extracted GNFG data from the endoscopic submucosal dissection (ESD) database and matched patients with conventional early gastric cancer as controls in a 1:4 ratio by age and sex. GNFG and CGA were compared for the overall survival (OS), disease-specific survival, progression-free survival, and metachronous gastric tumor rates.

Overall, 43 lesions were GNFG and 164 CGAs were matched. There were three deaths in the GNFG group and 11 deaths in the CGA group. There was no significant difference in the OS between the two groups (P=0.81). The five-year OS rates for the GNFG and CGA groups were 90.9% and 92.9%, respectively. No disease-specific deaths or recurrences were observed in either group. There was no significant difference in the cumulative metachronous gastric tumor rate between the two groups (P=0.17). The cumulative five-year metachronous gastric tumor rates for the GNFG and CGA groups were 6.6% and 2.5%, respectively.

The prognosis for GNFG is good, however, not better than that for CGA. The metachronous gastric tumor rate after ESD in GNFG was not lower than that in CGA. Therefore, after ESD, GNFG may need to be managed in the same way as CGA.

The Japan Gastroenterological Endoscopy Society (JGES) held four serial symposia between 2021 and 2022 on state-of-the-art issues related to advanced diagnostic endoscopy of the upper gastrointestinal tract. This review summarizes the four core sessions and presents them as a conference report. Eleven studies were discussed in the 101st JGES Core Session, which addressed the challenges and prospects of upper gastroenterological endoscopy. Ten studies were also explored in the 102nd JGES Core Session on advanced upper gastrointestinal endoscopic diagnosis for decision-making regarding therapeutic strategies. Moreover, eight studies were presented during the 103rd JGES Core Session on the development and evaluation of endoscopic artificial intelligence in the field of upper gastrointestinal endoscopy. Twelve studies were also discussed in the 104th JGES Core Session, which focused on the evidence and new developments related to the upper gastrointestinal tract. The endoscopic diagnosis of upper gastrointestinal diseases using image-enhanced endoscopy and AI is one of the most recent topics and has received considerable attention. These four core sessions enabled us to grasp the current state-of-the-art in upper gastrointestinal endoscopic diagnostics and identify future challenges. Based on these studies, we hope that an endoscopic diagnostic system useful in clinical practice is established for each field of upper gastrointestinal endoscopy.

Delayed bleeding (DB) is a possible adverse event following gastric endoscopic submucosal dissection (ESD). The BEST-J score was created as a risk prediction model for DB following gastric ESD, but is yet to be validated in Western populations.

We aimed to validate the BEST-J score on a European sample and to perform a subgroup analysis according to histological classification.

Retrospective study of all consecutive patients undergoing gastric ESD on a European Endoscopic Unit. DB was defined as hemorrhage with clinical symptoms and confirmed by emergency endoscopy from the time of completion to 28 days after ESD. BEST-J score was calculated in each patient and confronted with the outcome (DB).

Final sample included 161 patients. From these, 10 (6.2%) presented DB following ESD, with a median time to bleeding of 7 days (IQR 6.8). BEST-J score presented an excellent accuracy predicting DB in our sample, with an AUC = 0.907 (95%CI 0.801-1.000; p < 0.001). Subgroup analysis by histological classification proved that the discriminative power was still excellent for each grade: low-grade dysplasia-AUC = 0.970 (p < 0.001); high-grade dysplasia-AUC = 0.874 (p < 0.001); early gastric cancer-AUC = 0.881 (p < 0.001). The optimal cut-off value to predict DB was a BEST-J score ≥ 3, which matches the cut-off value for high-risk of bleeding in the original investigation.

The BEST-J score still presents excellent accuracy in risk stratification for post-ESD bleeding in European individuals. Thus, this score may help to guide which patients benefit the most from prophylactic therapies following gastric ESD in this setting.

Gastric cancer (GC) is a major global health concern with poor outcomes. Heterogeneous nuclear ribonucleoprotein U (HNRNPU) is a multifunctional protein that participates in pre-mRNA packaging, alternative splicing regulation, and chromatin remodeling. Its potential role in GC remains unclear. In this study, the expression characteristics of HNRNPU were analyzed by The Cancer Genome Atlas data, Gene Expression Omnibus data, and then further identified by real-time quantitative PCR and immunohistochemistry using tissue specimens. From superficial gastritis, atrophic gastritis, and hyperplasia to GC, the in situ expression of HNRNPU protein gradually increased, and the areas under the curve for diagnosis of GC and its precancerous lesions were 0.911 and 0.847, respectively. A nomogram integrating HNRNPU expression, lymph node metastasis, and other prognostic indicators exhibited an area under the curve of 0.785 for predicting survival risk. Knockdown of HNRNPU significantly inhibited GC cell proliferation, migration, and invasion and promoted apoptosis in vitro. In addition, RNA-sequencing analysis showed that HNRNPU could affect alternative splicing events in GC cells, with functional enrichment analysis revealing that HNRNPU may exert malignant biological function in GC progression through alternative splicing regulation. In summary, the increased expression of HNRNPU was significantly associated with the development of GC, with a good performance in diagnosing and predicting the prognostic risk of GC. Functionally, HNRNPU may play an oncogenic role in GC by regulating alternative splicing.

Esophagogastroduodenoscopy (EGD) screening is being implemented in countries with a high incidence of upper gastrointestinal (UGI) cancer. High-quality EGD screening ensures the yield of early diagnosis and prevents suffering from advanced UGI cancer and minimal operational-related discomfort. However, performance varied dramatically among endoscopists, and quality control for EGD screening remains suboptimal. Guidelines have recommended potential measures for endoscopy quality improvement and research has been conducted for evidence. Moreover, artificial intelligence offers a promising solution for computer-aided diagnosis and quality control during EGD examinations. In this review, we summarized the key points for quality assurance in EGD screening based on current guidelines and evidence. We also outline the latest evidence, limitations, and future prospects of the emerging role of artificial intelligence in EGD quality control, aiming to provide a foundation for improving the quality of EGD screening.

Magnifying image-enhanced endoscopy (MIEE) is an advanced endoscopy with image enhancement and magnification used in preoperative examination. However, its impact on the detection rate is unknown.

We conducted an open-label, randomized, parallel (1:1:1), controlled trial in 6 hospitals in China. Patients were recruited between February 14, 2022 and July 30, 2022. Eligible patients were aged ≥18 years and undergoing gastroscopy in outpatient departments. Participants were randomly assigned to the MIEE-only mode (o-MIEE) group, white-light endoscopy-only mode (o-WLE) group, and MIEE when necessary mode (n-MIEE) group (initial WLE followed by switching to another endoscope with MIEE if necessary). Biopsy sampling of suspicious lesions of the lesser curvature of the gastric antrum was performed. Primary and secondary aims were to compare detection rates and positive predictive value (PPV) of early cancer and precancerous lesions in these 3 modes, respectively.

A total of 5100 recruited patients were randomly assigned to the o-MIEE (n = 1700), o-WLE (n = 1700), and n-MIEE (n = 1700) groups. In the o-MIEE, o-WLE, and n-MIEE groups, 29 (1.51%; 95% confidence interval [CI], 1.05-2.16), 4 (.21%; 95% CI, .08-.54), and 8 (.43%; 95% CI, .22-.85) early cancers were found, respectively (P < .001). The PPV for early cancer was higher in the o-MIEE group compared with the o-WLE and n-MIEE groups (63.04%, 33.33%, and 38.1%, respectively; P = .062). The same trend was seen for precancerous lesions (36.67%, 10.00%, and 21.74%, respectively).

The o-MIEE mode resulted in a significant improvement in diagnosing early upper GI cancer and precancerous lesions; thus, it could be used for opportunistic screening. (Clinical trial registration number: ChiCTR2200064174.).

Gastric intestinal metaplasia (GIM), which denotes conversion of gastric mucosa into an intestinal phenotype, can occur in all regions of the stomach, including cardiac, fundic, and pyloric mucosa. Since the earliest description of GIM, its association with gastric cancer of the differentiated (intestinal) type has been a well-recognized concern. Many epidemiologic studies have confirmed GIM to be significantly associated with subsequent gastric cancer development. Helicobacter pylori, the principal etiologic factor for gastric cancer, plays the most important role in predisposing to GIM. Although the role of GIM in the stepwise progression model of gastric carcinogenesis (the so-called "Correa cascade") has come into question recently, we review the scientific evidence that strongly supports this long-standing model and propose a new progression model that builds on the Correa cascade. Eradication of H pylori is the most important method for preventing gastric cancer globally, but the effect of eradication on established GIM, is limited, if any. Endoscopic surveillance for GIM may, therefore, be necessary, especially when there is extensive corpus GIM. Recent advances in image-enhanced endoscopy with integrated artificial intelligence have facilitated the identification of GIM and neoplastic lesions, which will impact preventive strategies in the near future.

Microbiota alterations are linked with gastric cancer (GC). However, the relationship between the oral microbiota (especially oral fungi) and GC is not known. In this study, we aimed to apply 2b-RAD sequencing for Microbiome (2b-RAD-M) to characterize the oral microbiota in patients with GC.

We performed 2b-RAD-M analysis on the saliva and tongue coating of GC patients and healthy controls. We carried out diversity, relative abundance, and composition analyses of saliva and tongue coating bacteria and fungi in the two groups. In addition, indicator analysis, the Gini index, and the mean decrease accuracy were used to identify oral fungal indicators of GC.

In this study, fungal imbalance in the saliva and tongue coating was observed in the GC group. At the species level, enriched Malassezia globosa (M. globosa) and decreased Saccharomyces cerevisiae (S. cerevisiae) were observed in saliva and tongue coating samples of the GC group. Random forest analysis indicated that M. globosa in saliva and tongue coating samples could serve as biomarkers to diagnose GC. The Gini index and mean decreases in accuracy for M. globosa in saliva and tongue coating samples were the largest. In addition, M. globosa in saliva and tongue coating samples classified GC from the control with areas under the receiver operating curve (AUCs) of 0.976 and 0.846, respectively. Further ecological analysis revealed correlations between oral bacteria and fungi.

For the first time, our data suggested that changes in oral fungi between GC patients and controls may help deepen our understanding of the complex spectrum of the different microbiotas involved in GC development. Although the cohort size was small, this study is the first to use 2b-RAD-M to reveal that oral M. globosa can be a fungal biomarker for detecting GC.

Texture and color enhancement imaging (TXI) enhances the changes in endoscopic features caused by gastric neoplasms, such as redness/whiteness and elevation/depression. This study aimed to demonstrate the effectiveness of TXI in improving the visibility of gastric neoplasms compared with white light imaging (WLI) using conventional (CE) and newly developed endoscopes (NE).

We recruited patients who were histologically diagnosed with gastric neoplasms; endoscopy was performed, and gastric neoplasms photographed using three imaging modalities, including WLI, TXI mode 1 (TXI-1) and TXI mode 2 (TXI-2). Two different endoscopes (CE and NE) were used for the same patients. Six endoscopists provided the visibility scale scores ranging from 1 (poor) to 4 (excellent) for gastric neoplasms. The primary outcome was the visibility scale scores based on each modality and endoscope. The secondary outcome was the identification of factors including H. pylori infection, atrophy, location, size, morphology, histological diagnosis and intestinal metaplasia that affect the differences in visibility scale scores between TXI-1/TXI-2 and WLI.

Fifty-two gastric neoplasms were analyzed. The mean visibility scale scores with the NE were 2.79 ± 1.07, 3.23 ± 0.96 and 3.14 ± 0.92 for WLI, TXI-1 and TXI-2, respectively. The mean visibility scales with the CE were 2.53 ± 1.10, 3.04 ± 1.05 and 2.96 ± 1.92 for WLI, TXI-1 and TXI-2, respectively. For both endoscopes, significant differences were observed in visibility scale scores between WLI and TXI-1 (p < 0.001) and between WLI and TXI-2 (p < 0.001). The visibility scale scores of NE were superior to those of CE in all modalities. In the secondary outcome, there was no factor affected the differences of visibility scale scores between TXI-1/TXI-2 and WLI.

This study demonstrated that TXI-1 and TXI-2 enhanced the visibility scale scores of gastric neoplasms compared with that of WLI. Moreover, newly developed endoscope has the potential to improve visibility compared to conventional endoscope.

This study was registered with the University Hospital Medical Information Network (UMIN000042429, 16/11/2020).

We held four upper gastrointestinal tract advanced diagnostic endoscopy sessions from the 89th to the 92nd Congress of the Japan Gastroenterological Endoscopy Society. The most common region addressed was the stomach in 25 presentations, followed by the esophagus in 23, duodenum in five, and other in one. Looking at techniques discussed, the most common image enhancement method discussed was narrowband imaging in 29 presentations, blue laser imaging, and linked color imaging (LCI) in 10 each, dual red imaging in three, and autofluorescence imaging in one. Furthermore, there were presentations of new techniques such as M-Chromo-LCI and acetic acid-indigo carmine mixture LCI. There were also six presentations regarding probe-based confocal laser endomicroscopy, and one of endocytoscopy techniques. We also saw presentations of images of gastric subepithelial tumors within the submucosa, 3D endoscopy, the development of computer-aided detection systems for early cancers, and fluorescent imaging.

Gastric cancer is a leading contributor to cancer incidence and mortality globally. Recently, artificial intelligence approaches, particularly machine learning and deep learning, are rapidly reshaping the full spectrum of clinical management for gastric cancer. Machine learning is formed from computers running repeated iterative models for progressively improving performance on a particular task. Deep learning is a subtype of machine learning on the basis of multilayered neural networks inspired by the human brain. This review summarizes the application of artificial intelligence algorithms to multi-dimensional data including clinical and follow-up information, conventional images (endoscope, histopathology, and computed tomography (CT)), molecular biomarkers, etc. to improve the risk surveillance of gastric cancer with established risk factors; the accuracy of diagnosis, and survival prediction among established gastric cancer patients; and the prediction of treatment outcomes for assisting clinical decision making. Therefore, artificial intelligence makes a profound impact on almost all aspects of gastric cancer from improving diagnosis to precision medicine. Despite this, most established artificial intelligence-based models are in a research-based format and often have limited value in real-world clinical practice. With the increasing adoption of artificial intelligence in clinical use, we anticipate the arrival of artificial intelligence-powered gastric cancer care.

Effective identification of T1a stage cancer is crucial for planning endoscopic resection for early gastric cancers. The present study aimed to determine the diagnostic value of the double-track sign in patients with T1a gastric cancer using computed tomography (CT) imaging. A total of 152 patients diagnosed with pathologically proven T1a gastric cancer at The First Affiliated Hospital of Zhengzhou University (Zhengzhou, China) between July 2011 and August 2021 were retrospectively reviewed. The control group consisted of 2,926 patients with gastritis. Clinical data, including patient characteristics and preoperative CT imaging findings with gastric morphological features, were reviewed and analyzed. Out of 51 patients with T1a gastric cancer finally included, 31 (60.8%) exhibited local double-track enhancement changes of the stomach, referred to as the 'double-track sign', on CT images. In addition, four patients (7.8%) had well-enhanced mucosal thickening of the gastric wall. Of the 2,926 control subjects, none had any double-track sign and six patients (0.2%) had local gastric wall thickening with abnormally strengthened enhancement. In conclusion, a double-track sign on CT images is beneficial in the diagnostic differentiation of T1a gastric cancer.

Gastric cancer (GC) carries significant morbidity and mortality globally. An increasing number of studies have confirmed that circular RNA (circRNA) is tightly associated with the carcinogenesis and development of GC, especially acting as a competing endogenous RNA for miRNAs.

Our study aimed to construct the circRNA-miRNA-mRNA regulatory network and analyze the function and prognostic significance of the network using bioinformatics tools.

We first downloaded the GC expression profile from the Gene Expression Omnibus database and identified differentially expressed genes and differentially expressed circRNAs. Then, we predicted the miRNA-mRNA interaction pairs and constructed the circRNA-miRNA-mRNA regulatory network. Next, we established a protein-protein interaction network and analyzed the function of these networks. Finally, we primarily validated our results by comparison with The Cancer Genome Atlas cohort and by performing qRT-PCR.

We screened the top 15 hub genes and 3 core modules. Functional analysis showed that in the upregulated circRNA network, 15 hub genes were correlated with extracellular matrix organization and interaction. The function of downregulated circRNAs converged on physiological functions, such as protein processing, energy metabolism and gastric acid secretion. We ascertained 3 prognostic and immune infiltration-related genes, COL12A1, COL5A2, and THBS1, and built a nomogram for clinical application. We validated the expression level and diagnostic performance of key prognostic differentially expressed genes.

In conclusion, we constructed two circRNA-miRNA-mRNA regulatory networks and identified 3 prognostic and screening biomarkers, COL12A1, COL5A2, and THBS1. The ceRNA network and these genes could play important roles in GC development, diagnosis and prognosis.

Gastrointestinal (GI) endoscopy has known a great evolution in the last decades. Imaging techniques evolved from imaging with only standard white light endoscopes toward high-definition resolution endoscopes and the use of multiple color enhancement techniques, over to automated endoscopic assessment systems based on artificial intelligence. This narrative literature review aimed to provide a detailed overview on the latest evolutions within the field of advanced GI endoscopy, mainly focusing on the screening, diagnosis, and surveillance of common upper and lower GI pathology.

This review comprises only literature about screening, diagnosis, and surveillance strategies using advanced endoscopic imaging techniques published in (inter)national peer-reviewed journals and written in English. Studies with only adult patients included were selected. A search was performed using MESH terms: dye-based chromoendoscopy, virtual chromoendoscopy, video enhancement technique, upper GI tract, lower GI tract, Barrett's esophagus, esophageal squamous cell carcinoma, gastric cancer, colorectal polyps, inflammatory bowel disease, artificial intelligence. This review does not elaborate on the therapeutic application or impact of advanced GI endoscopy.

Focusing on current and future applications and evolutions in the field of both upper and lower GI advanced endoscopy, this overview is a practical but detailed projection of the latest developments. Within this review, an active leap toward artificial intelligence and its recent developments in GI endoscopy was made. Additionally, the literature is weighted against the current international guidelines and assessed for its potential positive future impact.

Diagnosis of early gastric cancer and its precancerous lesions remains a challenge for great part of western endoscopists. Changes seen in the mucosal pattern are generally subtle and hence difficult to identify. In this article, we will review the usefulness of conventional and virtual chromoendoscopy and magnification endoscopy in the recognition and classification of these lesions.

Endoscopic technologies have recently advanced to optimize the detection and diagnosis of gastric lesions. Endocytoscopy aids in the virtual realization of histology. Herein, we aimed to investigate gastric lesions using single-stain endocytoscopy and compare them using magnifying endoscopy with narrow-band imaging (ME-NBI) in terms of diagnostic yield in vivo.

In the present prospective study, we registered 24 patients with gastric neoplasms and retrospectively reviewed their images. Three endoscopists reviewed the images of gastric neoplasms using white light, ME-NBI, and endocytoscopy. The diagnostic yield of endocytoscopy in early gastric cancer (EGC) was assessed using histopathology as the gold standard.

Endocytoscopy was performed in 24 patients with gastric neoplasms. Of these, 15 patients had adenocarcinomas, while nine patients had low-grade dysplasia. The sensitivity, specificity, and accuracy of endocytoscopy for EGC detection were reported as 80.0% [95% confidence interval (CI), 51.9-95.7], 66.7% (95% CI, 58.4-91.9), and 75.0% (95% CI, 53.3-90.2) by endoscopist A; 80.0% (95% CI, 51.9-95.7), 44.4% (95% CI, 13.7-78.8), and 66.7% (95% CI, 44.7-84.4) by endoscopist B; and 93.3% (95% CI, 68.1-99.8), 55.6% (95% CI, 21.2-86.3), and 79.2% (95% CI, 57.9-92.8) by endoscopist C; these findings were not inferior to NBI. The inter-observer agreement, κ statistic = 0.67 (95% CI, 0.43-0.90) was favorable.

Endocytoscopy aid in the diagnosis of EGC because of its better sensitivity and accuracy compared to NBI or white-light imaging. However, further large-scale studies are required to confirm our findings.

Early-stage gastric cancer (EGC) found after Helicobacter pylori (Hp) eradication is often difficult to diagnose using conventional white light (WL) endoscopy. We aimed to evaluate whether Texture and Color Enhancement Imaging (TXI), a new image-enhanced endoscopy enhances the EGC lesions after Hp eradication. We also compared diagnostic accuracy and lesion detection time between WL and TXI in trainee endoscopists. 58 EGC lesions after successful Hp eradication were enrolled. Using endoscopic images in WLI, TXI mode 1 (TXI1), and TXI mode 2 (TXI2), visibility of EGC was assessed by six expert endoscopists using a subjective score. Mean color differences (ΔE) of four matched adjacent and intra-tumoral points were examined. Using randomly allocated images, diagnostic accuracy and lesion detection time were evaluated in three trainee endoscopists. Visibility score was unchanged (Score 0) in 20.7% (12/58) and 45.6% (26/57), slightly improved (Score 1) in 60.3% (35/58) and 52.6% (30/57), obviously improved (Score 2) in 45.6% (26/58) and 1.8% (1/57), in TXI1 and TXI2 compared to WL, respectively. Mean ΔE ± SEM in TXI1 (22.90 ± 0.96), and TXI2 (15.32 ± 0.71) were higher than that in WL (1.88 ± 0.26, both P < 0.0001). TXI1 presented higher diagnostic accuracy compared to WL, in two of three trainees (94.8% vs. 74.1%, 100% vs. 89.7%, P = 0.003; < 0.005, respectively). Lesion detection time was shorter in TXI1 in two of three trainees (P = 0.006, 0.004, respectively) compared to WL. TXI improves visibility of EGC after Hp eradication that may contribute to correct diagnosis.

Gastroscopy is the reference standard for the diagnosis of gastric cancer, but it is operator-dependent and associated with missed gastric cancer. The proliferation of gastroscopic examinations, increasingly for the screening and detection of subtle premalignant lesions, has motivated scrutiny of quality in gastroscopy. The concept of a high-quality endoscopic examination for the detection of superficial gastric neoplasia has been defined by expert guidelines to improve mucosal visualization, engender a systematic examination process and detect superficial neoplasia. This review discusses the evidence supporting the components of a high-quality diagnostic gastroscopic examination in relation to the detection of gastric cancer, and their potential role as procedural quality indicators to drive a structured improvement in clinically meaningful outcomes.

Overlooking early gastric cancer (EGC) during endoscopy is an issue to be resolved. Image-enhanced endoscopy is expected to improve EGC detection. This study investigated the usefulness of third-generation narrow band imaging (3G-NBI) and texture and color enhancement imaging (TXI) in improving the visibility of EGC using the color difference between EGC and its surrounding gastric mucosa.

In this retrospective observational study, we examined 51 superficial EGCs that underwent endoscopic submucosal dissection and were observed by all three methods: 3G-NBI, TXI, and white light imaging (WLI). The primary endpoint was to compare the color difference of each method. For each EGC, we prepared one non-magnifying image for each method so that the location and size of the lesion in each image were the same. The L*a*b* color space was used to evaluate the color values. When the color values of the cancerous lesion and its surrounding mucosa were (L*c, a*c, b*c) and (L*s, a*s, b*s), respectively, the color difference was defined to be [(L*c-L*s)2+(a*c-a*s)2+(b*c-b*s)2]1/2.

The median color difference was 9.2 (interquartile range, 5.3-15.7) in WLI, 13.5 (interquartile range, 9.4-19.5) in 3G-NBI, and 15.3 (interquartile range, 9.1-22.1) in TXI. Statistically, the color difference was significantly larger in 3G-NBI than in WLI (p < 0.001) and TXI compared with WLI (p < 0.001). However, there was no significant difference between 3G-NBI and TXI (p = 0.330).

Regarding color difference, both 3G-NBI and TXI were estimated to be more useful than WLI in improving the visibility of superficial EGC.

Magnifying endoscopy is advantageous in detecting precancerous lesions. Our study aimed to clarify its ability to detect easily missed neoplastic lesions on the upper gastrointestinal tract. A retrospective analysis of clinical, endoscopic, and pathological data of cases undergoing gastroscopy was performed using magnifying and routine endoscopy. The detection rates of overall lesions, the ability to identify flat-type neoplastic lesions, and the easily missed neoplastic lesions were compared between the two groups. Endoscopic data from 32,367 patients was analyzed in this study. The use of magnifying endoscopy was an independent factor in identifying flat lesions (OR 2.236, 95% CI 1.969-2.540, p < 0.001), particularly type IIb lesions (OR 3.117, 95% CI 2.333-4.165, p < 0.001). For neoplastic lesions, magnifying endoscopy was also identified as having better sensitivity than routine endoscopy (sensitivity, 90.4% vs. 78.9%, p < 0.001). Similarly, magnifying endoscopy was an independent factor for identifying flat lesions (OR 2.927, 95% CI 2.365-3.621, p < 0.001), especially type IIc lesions (OR 4.415, 95% CI 3.076-6.339, p < 0.001). Magnifying endoscopy was also identified as having superior sensitivity (44.7% vs. 13.3%, p = 0.034) for early cancerous lesions. Compared to routine endoscopy, magnification endoscopy is advantageous in detecting and identifying neoplastic lesions in the upper gastrointestinal tract, especially flat neoplastic lesions and early cancers.

During flexible gastroscopy, physicians have extreme difficulties to self-localize. Camera tracking method such as simultaneous localization and mapping (SLAM) has become a research hotspot in recent years, allowing tracking of the endoscope. However, most of the existing solutions have focused on tasks in which sufficient texture information is available, such as laparoscope tracking, and cannot be applied to gastroscope tracking since gastroscopic images have fewer textures than laparoscopic images. This paper proposes a new monocular SLAM framework based on scale-invariant feature transform (SIFT) and narrow-band imaging (NBI), which extracts SIFT features instead of oriented features from accelerated segment test (FAST) and rotated binary robust independent elementary features (BRIEF) features from gastroscopic NBI images, and performs feature retention based on the response sorting strategy for achieving more matches. Experimental results show that the root mean squared error of the proposed algorithm can reach a minimum of 2.074 mm, and the pose accuracy can be improved by up to 25.73% compared with oriented FAST and rotated BRIEF (ORB)-SLAM. SIFT features and response sorting strategy can achieve more accurate matching in gastroscopic NBI images than other features and homogenization strategy, and the proposed algorithm can also run successfully on real clinical gastroscopic data. The proposed algorithm has the potential clinical value to assist physicians in locating the gastroscope during gastroscopy.

As an endoscopic technology for the enhancement of images, linked color imaging (LCI) performs well when used for the early detection and diagnosis of gastrointestinal cancer. However, literature data are lacking for LCI in the detection of high-grade gastric intraepithelial neoplasia. Therefore, the aim of the present study was to investigate the efficacy of LCI compared with traditional white light imaging (WLI) in the detection of high-grade gastric intraepithelial neoplasia via the comparison of detection rates between senior and junior endoscopists using both techniques. Overall, 84 lesions from 81 patients with high-grade gastric intraepithelial neoplasia diagnosed between January 2017 and December 2017 were considered. Following the exclusion of three patients with two lesions, 78 patients who had only one lesion were enrolled. The two types of endoscopy, WLI and LCI, were performed in the same patients under the same conditions. Four senior and four junior endoscopists retrospectively compared the images. The detection rate of high-grade gastric intraepithelial neoplasia was significantly higher with LCI than with WLI when performed by senior and junior endoscopists. With WLI, the detection rate obtained by senior endoscopists was significantly higher than that obtained by junior endoscopists. However, for LCI, the detection rates for junior and senior endoscopists were comparable. Interobserver agreement was good to satisfactory. These findings indicate that LCI is superior to WLI in the detection and identification of gastric cancer and provides highly accurate diagnostic results from endoscopic examinations, regardless of the experience of the endoscopist. LCI may be used to narrow the gap in the detection rate of high-grade gastric intraepithelial neoplasia between junior and senior endoscopists.

This study aimed to estimate the survival rates among Iranian gastric cancer patients and to evaluate if the survival has improved during the last three decades.

Gastric cancer is one of the most common cancers in Iran with high mortality.

A systematic review and meta-analysis of all published studies addressing gastric cancer survival in Iran was performed. International databases of Scopus, Web of Science, PubMed, and Iranian databases were included in the study. The study included databases from their inception till February 2022. Due to the inherent heterogeneity, we used a random effect model to pool the survivals in three categories of one, three, and five-year survivals.

Thirty-three studies with total cases of 17,207 were included in the study. The overall (pooled) one, three, and five-year survivals were estimated as 58.9% (95% CI: 0.52, 0.66), 29.9% (95% CI: 0.25, 0.35), and 18.2% (95% CI: 0.15, 0.23), respectively. Results of subgroup analysis for the calendar years of study showed that the one, three, and five-year survival rates increased during the last three decades but the results were not statistically significant. There was the disparity in survival based on geographic distribution.

The results of our study which has pooled many studies for a long period of time clearly indicate that the survival rates of gastric cancer patients have improved. As the improvement of survival may be due to many factors, more studies is needed to understand the dynamic behind this improvement.

Chromoendoscopy has not been fully integrated into capsule endoscopy. This study aimded to develop and validate a novel intelligent chromo capsule endoscope (ICCE).

The ICCE has two modes: a white-light imaging (WLI) mode and an intelligent chromo imaging (ICI) mode. The performance of the ICCE in observing colors, animal tissues, and early gastrointestinal (GI) neoplastic lesions in humans was evaluated. Images captured by the ICCE were analysed using variance of Laplacian (VoL) values or image contrast evaluation.

For color observation, conventional narrow-band imaging endoscopes and the ICI mode of the ICCE have similar spectral distributions. Compared with the WLI mode, the ICI mode had significantly higher VoL values for animal tissues (2.154 ± 1.044 vs 3.800 ± 1.491, P = 0.003), gastric precancerous lesions and early gastric cancers (2.242 ± 0.162 vs 6.642 ± 0.919, P < 0.001), and colon tumors (3.896 ± 1.430 vs 11.882 ± 7.663, P < 0.001), and significantly higher contrast for differentiating tumor and non-tumor areas (0.069 ± 0.046 vs 0.144 ± 0.076, P = 0.005). More importantly, the sensitivity, specificity, and accuracy of the ICI mode for early GI tumors were 95.83%, 91.67%, and 94.64%, respectively, which were significantly higher than the values of the WLI mode (78.33% [P < 0.001], 77.08% [P = 0.01], and 77.98% [P < 0.001], respectively).

We successfully integrated ICI into the capsule endoscope. The ICCE is an innovative and useful tool for differential diagnosis based on contrast-enhanced images and thus has great potential as a superior diagnostic tool for early GI tumor detection.

White light imaging (WLI) is the most common endoscopic technique used for screening of gastrointestinal diseases. However, despite the advent of a new processor that offers sufficient clear illumination and other advanced developments in endoscopic instrumentation, WLI alone is inadequate for detecting all gastrointestinal diseases with abnormalities in mucosal discoloration and morphological changes to the mucosal surface. The recent development of image-enhanced endoscopy (IEE) has dramatically improved the detection of gastrointestinal diseases. Texture and colour enhancement imaging (TXI) is a new type of IEE that enhances brightness, surface irregularities, such as elevations or depressions, and subtle colour changes. TXI with two modes, namely modes 1 and 2, can selectively enhance brightness in dark areas of an endoscopic image and subtle tissue differences such as slight morphological or colour changes while simultaneously preventing over-enhancement. Several clinical studies have investigated the efficacy of TXI for detecting and visualizing gastrointestinal diseases, including oesophageal squamous cell carcinoma (ESCC), Barret's epithelium, gastric cancer, gastric mucosal atrophy and intestinal metaplasia. Although TXI is often more useful for detecting and visualizing gastrointestinal diseases than WLI, it remains unclear whether TXI outperforms other IEEs, such as narrow-band imaging (NBI), in similar functions, and whether the performance of TXI modes 1 and 2 are comparable. Therefore, large-scale prospective studies are needed to compare the efficacy of TXI to WLI and other IEEs for endoscopic evaluation of patients undergoing screening endoscopy. Here, we review the characteristics and efficacy of TXI for the detection and visualization of gastrointestinal diseases.Key MessagesTXI mode 1 can improve the visibility of gastrointestinal diseases and qualitative diagnosis, especially for diseases associated with colour changes.The enhancement of texture and brightness with TXI mode 2 enables the detection of diseases, and is ideal for use in the first screening of gastrointestinal tract.

The clinical application of GI endoscopy for the diagnosis of multiple diseases using artificial intelligence (AI) has been limited by its high false-positive rates. There is an unmet need to develop a GI endoscopy AI-assisted diagnosis system (GEADS) to improve diagnostic accuracy and clinical utility.

In this retrospective, multicenter study, a convolutional neural network was trained to assess upper GI diseases based on 26,228 endoscopic images from Dazhou Central Hospital that were randomly assigned (3:1:1) to a training dataset, validation dataset, and test dataset, respectively. To validate the model, 6 external independent datasets comprising 51,372 images of upper GI diseases were collected. In addition, 1 prospective dataset comprising 27,975 images was collected. The performance of GEADS was compared with endoscopists with 2 professional degrees of expertise: expert and novice. Eight endoscopists were in the expert group with >5 years of experience, whereas 3 endoscopists were in the novice group with 1 to 5 years of experience.

The GEADS model achieved an accuracy of .918 (95% confidence interval [CI], .914-.922), with an F1 score of .884 (95% CI, .879-.889), recall of .873 (95% CI, .868-.878), and precision of .890 (95% CI, .885-.895) in the internal validation dataset. In the external validation datasets and 1 prospective validation dataset, the diagnostic accuracy of the GEADS ranged from .841 (95% CI, .834-.848) to .949 (95% CI, .935-.963). With the help of the GEADS, the diagnosing accuracies of novice and expert endoscopists were significantly improved (P < .001).

The AI system can assist endoscopists in improving the accuracy of diagnosing upper GI diseases.