Comparison of the diagnostic efficacy of white light endoscopy and magnifying endoscopy with narrow band imaging for early gastric cancer: a meta-analysis

Risk factors of missed early gastric cancer in endoscopic resected population: a retrospective, case-control study

BACKGROUND

Missed early gastric cancer (MEGC) is prevalent during esophagogastroduodenoscopy (EGD), which is the first-line recommended strategy for detecting early gastric cancer (EGC). Hence, we explored the risk factors for MEGC and different types of MEGC, based on the endoscopic resected population.

METHODS

This retrospective, case-control study was conducted at Nanjing Drum Tower Hospital (NJDTH). We included patients who were diagnosed with EGC during screening EGD, underwent endoscopic resection, and were confirmed by postoperative pathology at the NJDTH from January 2014 to December 2021, and classified them into different types according to the different root causes of misses. Univariable, multivariable, subgroup and propensity score analyses were used to explore the risk factors for MEGC and different types of MEGC.

RESULTS

A total of 447 patients, comprising 345 with initially detected early gastric cancer (IDEGC) and 102 with MEGC, were included in this study. Larger size (≥ 1 cm) (OR 0.45, 95% CI 0.27-0.74, P = 0.002) and invasion depth of submucosa (OR 0.26, 95% CI 0.10-0.69, P = 0.007) were negatively associated with MEGC. Use of sedation (OR 0.32, 95% CI 0.20-0.52, P < 0.001) and longer observation time (OR 0.60, 95% CI 0.37-0.96, P = 0.034) exhibited protective effect on MEGC.

CONCLUSIONS

Smaller and more superficial EGC lesions are more susceptible to misdiagnosis. The use of sedation and prolonged observation time during EGD could help reduce the occurrence of MEGC.

Endoscopic Resection of Malignancies in the Upper GI Tract: A Clinical Algorithm

Background

Malignancies in the upper gastrointestinal tract are amenable to endoscopic resection at an early stage. Achieving a curative resection is the most stringent quality criterion, but post-resection risk assessment and aftercare are also part of a comprehensive quality program.

Summary

Various factors influence the achievement of curative resection. These include endoscopic assessment prior to resection using chromoendoscopy and HD technology. If resectability is possible, it is particularly important to delineate the lateral resection margins as precisely as possible before resection. Furthermore, the correct choice of resection technique depending on the lesion must be taken into account. Endoscopic submucosal dissection is the standard for esophageal squamous cell carcinoma and gastric carcinoma. In Western countries, it is becoming increasingly popular to treat Barrett's neoplasia over 2 cm in size and/or with suspected submucosal infiltration with en bloc resection instead of piece meal resection. After resection, risk assessment based on the histopathological resection determines the patient's individual risk of lymph node metastases, particularly in the case of high-risk lesions. This is categorized according to the current literature.

Key Messages

This review presents clinical algorithms for endoscopic resection of esophageal SCC, Barrett's neoplasia, and gastric neoplasia. The algorithms include the pre-resection assessment of the lesion and the resection margins, the adequate resection technique for the respective lesion, as well as the post-resection risk assessment with an evidence-based recommendation for follow-up therapy and surveillance.

Gastric dysplasia in random biopsies: the influence of Helicobacter pylori infection and alcohol consumption in the presence of a lesion

BACKGROUND

Gastric dysplasia in the absence of an endoscopically defined lesion is rare, usually either a false positive diagnosis or a previously unidentified precancerous lesion during esophagogastroduodenoscopy (EGD).

AIMS

Evaluate factors associated with the presence of an endoscopically visible lesion during follow-up in patients with histologic diagnosis of gastric dysplasia in random biopsies.

METHODS

Retrospective cohort study including patients referred to our institution for gastric dysplasia in random biopsies during Index EGD. Endoscopic evaluation was performed with a high-definition endoscope using narrow band imaging (HD EGD-0). If no lesion was detected, endoscopic surveillance (HD EGD-FU) was conducted within 6 months for high grade dysplasia (HGD) or 12 months for low grade (LGD) or indefinite for dysplasia (IFD).

RESULTS

From a total sample of 96 patients, 5 (5.2%) presented with an endoscopically visible lesion during HD EGD-0, while 10 lesions (10.4%) were identified during HD EGD-FU. Patients with Helicobacter pylori infection at Index EDG and with regular alcohol consumption (≥25 g/day) were 8 and 4 times more likely to have an endoscopically visible lesion on HD EGD-FU (p = 0.012 and p = 0.047). In binary logistic regression, both factors were independent predictors of the presence of gastric lesion on HD EGD-FU (OR 9.284, p = 0.009 and OR 5.025, p = 0.033).

CONCLUSIONS

The presence of an endoscopically visible lesion after the histologic diagnosis of gastric dysplasia in random biopsies was more frequent during HD EGD-FU. H. pylori infection at Index EGD and regular alcohol consumption were significant predictors of the presence of gastric lesion on HD EGD-FU.

[Complicated gastric cancer and modern treatment approaches]

Among all patients with gastric cancer, 40% admit to the hospitals due to cancer-related complications. The most common complications of gastric cancer are bleeding (22-80%), malignant gastric outlet obstruction (26-60%), and perforation (less than 5%). The main treatment methods for gastric cancer complicated by bleeding are various forms of endoscopic hemostasis, transarterial embolization and external beam radiotherapy. Surgical treatment is possible in case of ineffective management. However, surgical algorithm is not standardized. Malignant gastric outlet stenosis requires decompression: endoscopic stenting, palliative gastroenterostomy. Surgical treatment is also possible (gastrectomy, proximal or distal resection of the stomach). The main problem for patients with complicated gastric cancer is the lack of standardized algorithms and abundance of potential surgical techniques. The aim of our review is to systematize available data on the treatment of complicated gastric cancer and to standardize existing methods.

Precision endoscopy in the era of climate change and sustainability

Global warming caused by increased greenhouse gas (GHG) emissions has a direct impact on human health. Gastrointestinal (GI) endoscopy contributes significantly to GHG emissions due to energy consumption, reprocessing of endoscopes and accessories, production of equipment, safe disposal of biohazardous waste, and travel by patients. Moreover, GHGs are also generated in histopathology through tissue processing and the production of biopsy specimen bottles. The reduction in unnecessary surveillance endoscopies and biopsies is a practical approach to decrease GHG emissions without affecting disease outcomes. This narrative review explores the role of precision medicine in GI endoscopy, such as image-enhanced endoscopy and artificial intelligence, with a focus on decreasing unnecessary endoscopic procedures and biopsies in the surveillance and diagnosis of premalignant lesions in the esophagus, stomach, and colon. This review offers strategies to minimize unnecessary endoscopic procedures and biopsies, decrease GHG emissions, and maintain high-quality patient care, thereby contributing to sustainable healthcare practices.

Magnifying image-enhanced endoscopy-only mode boosted early cancer diagnostic efficiency: a multicenter randomized controlled trial

BACKGROUND AND AIMS

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.

METHODS

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.

RESULTS

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).

CONCLUSIONS

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.).

Differences of clinical features and outcomes between male and female elderly patients in gastric cancer

Although the average life span differs between males and females, little is known about differences in clinical features and short and long-term outcomes between elderly male and female gastric cancer patients. This study was designed to clarify these issues to identify the possibility for sex-based treatment strategies in elderly gastric cancer patients. This study included 295 consecutive elderly gastric cancer patients (75 years or older) who underwent curative gastrectomy between 1997 and 2016. We defined postoperative complications as Clavien-Dindo classification grade II or higher. Comorbidities were present in 67% of all patients. Males tended to have more comorbidities than females (P = 0.077). Male patients had significantly more upper gastric cancers (P = 0.001), a higher incidence of postoperative complications (P = 0.045), and poorer prognoses than females (P = 0.003). Multivariate analysis revealed that being male was an independent risk factor for postoperative complications (Odds ratio 2.5, P = 0.045) and a poor prognostic factor (Hazard ratio 1.81, P = 0.008). Patients who underwent limited surgery without postoperative complications tended to have a better prognosis than patients receiving standard surgery with postoperative complications (3-year overall survival: 78% vs. 55%, P = 0.156). Male was an independent risk factor for postoperative complications and an independent poor prognostic factor in elderly gastric cancer patients. To avoid postoperative complications, the limited surgery might be justified for high-risk elderly male patients.

The Pink Zone Pattern (PP) sign: A novel simple marker for early gastric cancer

BACKGROUND

We previously found a pink-colored change in early gastric cancer (EGC) lesions under magnifying endoscopy with narrow-band imaging (ME-NBI) and named it the "Pink Zoon Pattern" (PP) sign, which appeared independent of microvascular and microstructural changes. The aim of this study was to further investigate the characteristics of the PP sign in EGC.

METHODS

The consecutive patients with suspicious gastric lesions detected by ME-NBI and confirmed by pathology at Zhejiang Cancer Hospital between November 2020 and December 2021 were enrolled in the study. The suspicious lesions were observed and assessed by the "VS" system and the PP sign respectively.

RESULTS

We found that in the PP-positive group, 238 lesions (96.0%) were diagnosed as malignant. The overall accuracy, sensitivity, and specificity were 84.7%, 85.3%, and 81.8%. Among 164 EGC lesions diagnosed with low confidence (Grades 2, 3, and 4) using the VS system, the overall accuracy of PP to discriminate tumor from normal was 82.3%. The sensitivity and specificity were 82.7% and 81.5% respectively.

CONCLUSIONS

The PP sign could be a new simple sign for the diagnosis of EGC and as an effective supplement to VS system when using ME-NBI.

Histopathological Evaluation of Gastric Mucosal Atrophy for Predicting Gastric Cancer Risk: Problems and Solutions

Patients suffering from chronic gastritis and developing gastric mucosa atrophy are at increased risk of the development of gastric cancer. The diagnosis of chronic atrophic gastritis (CAG) is a complex procedure involving a detailed history taking, a thorough physical examination and the use of laboratory and instrumental diagnostic methods among which the endoscopy of the upper digestive tract is the cornerstone because it allows the assessment of the topography of gastritis and identification of erosions and areas of intestinal metaplasia with the use of NBI endoscopy. However, the diagnosis of CAG requires morphological examination of the gastric mucosa. So, in addition to assessing macroscopic changes in the gastric mucosa, it is necessary to take biopsy specimens in accordance with the protocols for their morphological and immunohistochemical examination. In the absence of specific diagnostic stigmas of CAG, close cooperation between a clinician, endoscopist and pathologist is necessary. The article presents systematized data on the histopathological assessment of the gastric mucosa atrophy to predict the risk of gastric cancer.

Obesity paradox as a new insight from postoperative complications in gastric cancer

The obesity paradox is reported to exist in various diseases. However, obesity is a pivotal issue in gastric cancer (GC) patients because of the surgical difficulty related to postoperative abdominal infectious complications (PAIC). This study clarified the existence of the obesity paradox in GC. Between 1997 and 2015, 1536 consecutive patients underwent curative gastrectomy. Of all patients, 18.6% (285/1536) were obese and tended to have a better prognosis (P = 0.073). In patients without PAIC, obesity was a significant prognostic factor for 5-year overall survival (P = 0.017). PAIC was an independent poor prognostic factor in both obese and non-obese patients (P < 0.001; hazard ratio [HR] 4.22 and 1.82). In pStage II-III patients, there was a large and significant prognostic difference between non-PAIC and PAIC obese patients (P = 0.006; 5-year overall survival: 69.7% vs. 43.8%) related to the higher incidence of peritoneal recurrence in PAIC obese patients (P = 0.035; 31% vs. 10%). Whereas, there was a small prognostic difference between non-PAIC and PAIC non-obese patients (P = 0.102; 5-year overall survival: 56.5% vs. 51.9%). Although the obesity paradox is present in GC, PAIC had a more negative prognostic impact through peritoneal recurrence in obese GC patients.

Toward next-generation endoscopes integrating biomimetic video systems, nonlinear optical microscopy, and deep learning

According to the World Health Organization, the proportion of the world's population over 60 years will approximately double by 2050. This progressive increase in the elderly population will lead to a dramatic growth of age-related diseases, resulting in tremendous pressure on the sustainability of healthcare systems globally. In this context, finding more efficient ways to address cancers, a set of diseases whose incidence is correlated with age, is of utmost importance. Prevention of cancers to decrease morbidity relies on the identification of precursor lesions before the onset of the disease, or at least diagnosis at an early stage. In this article, after briefly discussing some of the most prominent endoscopic approaches for gastric cancer diagnostics, we review relevant progress in three emerging technologies that have significant potential to play pivotal roles in next-generation endoscopy systems: biomimetic vision (with special focus on compound eye cameras), non-linear optical microscopies, and Deep Learning. Such systems are urgently needed to enhance the three major steps required for the successful diagnostics of gastrointestinal cancers: detection, characterization, and confirmation of suspicious lesions. In the final part, we discuss challenges that lie en route to translating these technologies to next-generation endoscopes that could enhance gastrointestinal imaging, and depict a possible configuration of a system capable of (i) biomimetic endoscopic vision enabling easier detection of lesions, (ii) label-free in vivo tissue characterization, and (iii) intelligently automated gastrointestinal cancer diagnostic.

Recent advances in endoscopic management of gastric neoplasms

The development and clinical application of new diagnostic endoscopic technologies such as endoscopic ultrasonography with biopsy, magnification endoscopy, and narrow-band imaging, more recently supplemented by artificial intelligence, have enabled wider recognition and detection of various gastric neoplasms including early gastric cancer (EGC) and subepithelial tumors, such as gastrointestinal stromal tumors and neuroendocrine tumors. Over the last decade, the evolution of novel advanced therapeutic endoscopic techniques, such as endoscopic mucosal resection, endoscopic submucosal dissection, endoscopic full-thickness resection, and submucosal tunneling endoscopic resection, along with the advent of a broad array of endoscopic accessories, has provided a promising and yet less invasive strategy for treating gastric neoplasms with the advantage of a reduced need for gastric surgery. Thus, the management algorithms of various gastric tumors in a defined subset of the patient population at low risk of lymph node metastasis and amenable to endoscopic resection, may require revision considering upcoming data given the high success rate of en bloc resection by experienced endoscopists. Moreover, endoscopic surveillance protocols for precancerous gastric lesions will continue to be refined by systematic reviews and meta-analyses of further research. However, the lack of familiarity with subtle endoscopic changes associated with EGC, as well as longer procedural time, evolving resection techniques and tools, a steep learning curve of such high-risk procedures, and lack of coding are issues that do not appeal to many gastroenterologists in the field. This review summarizes recent advances in the endoscopic management of gastric neoplasms, with special emphasis on diagnostic and therapeutic methods and their future prospects.

The effectiveness of a computer-aided system in improving the detection rate of gastric neoplasm and early gastric cancer: study protocol for a multi-centre, randomized controlled trial

BACKGROUND

This protocol is for a multi-centre randomised controlled trial to determine whether the computer-aided system ENDOANGEL-GC improves the detection rates of gastric neoplasms and early gastric cancer (EGC) in routine oesophagogastroduodenoscopy (EGD).

METHODS

Study design: Prospective, single-blind, parallel-group, multi-centre randomised controlled trial.

SETTINGS

The computer-aided system ENDOANGEL-GC was used to monitor blind spots, detect gastric abnormalities, and identify gastric neoplasms during EGD.

PARTICIPANTS

Adults who underwent screening, diagnosis, or surveillance EGD. Randomisation groups: 1. Experiment group, EGD examinations with the assistance of the ENDOANGEL-GC; 2. Control group, EGD examinations without the assistance of the ENDOANGEL-GC.

RANDOMISATION

Block randomisation, stratified by centre.

PRIMARY OUTCOMES

Detection rates of gastric neoplasms and EGC.

SECONDARY OUTCOMES

Detection rate of premalignant gastric lesions, biopsy rate, observation time, and number of blind spots on EGD.

BLINDING

Outcomes are undertaken by blinded assessors.

SAMPLE SIZE

Based on the previously published findings and our pilot study, the detection rate of gastric neoplasms in the control group is estimated to be 2.5%, and that of the experimental group is expected to be 4.0%. With a two-sided α level of 0.05 and power of 80%, allowing for a 10% drop-out rate, the sample size is calculated as 4858. The detection rate of EGC in the control group is estimated to be 20%, and that of the experiment group is expected to be 35%. With a two-sided α level of 0.05 and power of 80%, a total of 270 cases of gastric cancer are needed. Assuming the proportion of gastric cancer to be 1% in patients undergoing EGD and allowing for a 10% dropout rate, the sample size is calculated as 30,000. Considering the larger sample size calculated from the two primary endpoints, the required sample size is determined to be 30,000.

DISCUSSION

The results of this trial will help determine the effectiveness of the ENDOANGEL-GC in clinical settings.

TRIAL REGISTRATION

ChiCTR (Chinese Clinical Trial Registry), ChiCTR2100054449, registered 17 December 2021.

Image-enhanced endoscopy in the diagnosis of gastric premalignant conditions and gastric cancer

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.

Magnifying endoscopy is superior at detecting easy-missed neoplastic lesions on the upper gastrointestinal tract

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.

A deep-learning based system using multi-modal data for diagnosing gastric neoplasms in real-time (with video)

BACKGROUND

White light (WL) and weak-magnifying (WM) endoscopy are both important methods for diagnosing gastric neoplasms. This study constructed a deep-learning system named ENDOANGEL-MM (multi-modal) aimed at real-time diagnosing gastric neoplasms using WL and WM data.

METHODS

WL and WM images of a same lesion were combined into image-pairs. A total of 4201 images, 7436 image-pairs, and 162 videos were used for model construction and validation. Models 1-5 including two single-modal models (WL, WM) and three multi-modal models (data fusion on task-level, feature-level, and input-level) were constructed. The models were tested on three levels including images, videos, and prospective patients. The best model was selected for constructing ENDOANGEL-MM. We compared the performance between the models and endoscopists and conducted a diagnostic study to explore the ENDOANGEL-MM's assistance ability.

RESULTS

Model 4 (ENDOANGEL-MM) showed the best performance among five models. Model 2 performed better in single-modal models. The accuracy of ENDOANGEL-MM was higher than that of Model 2 in still images, real-time videos, and prospective patients. (86.54 vs 78.85%, P = 0.134; 90.00 vs 85.00%, P = 0.179; 93.55 vs 70.97%, P < 0.001). Model 2 and ENDOANGEL-MM outperformed endoscopists on WM data (85.00 vs 71.67%, P = 0.002) and multi-modal data (90.00 vs 76.17%, P = 0.002), significantly. With the assistance of ENDOANGEL-MM, the accuracy of non-experts improved significantly (85.75 vs 70.75%, P = 0.020), and performed no significant difference from experts (85.75 vs 89.00%, P = 0.159).

CONCLUSIONS

The multi-modal model constructed by feature-level fusion showed the best performance. ENDOANGEL-MM identified gastric neoplasms with good accuracy and has a potential role in real-clinic.

A monocular SLAM system based on SIFT features for gastroscope tracking

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.

Diagnostic accuracy of linked colour imaging versus white light imaging for early gastric cancers: a prospective, multicentre, randomized controlled trial study

BACKGROUND

Linked colour imaging (LCI) is a novel new image-enhanced endoscopy (IEE) technology that produces bright and vivid images. The aim of this study was to assess the ability of LCI to improve the diagnostic accuracy of early gastric cancer (EGC) relative to white light imaging (WLI).

MATERIALS AND METHODS

We performed this study on patients undergoing screening endoscopy from 12 medical institutions in China. Patients were randomly assigned to receive WLI followed by LCI or LCI followed by WLI. The primary outcome was to compared the diagnostic accuracy between LCI and WLI for EGC/high-grade intraepithelial neoplasms. Secondary outcomes included the numbers of suspicious lesions, neoplastic lesions and examination time by using LCI detected versus using WLI.

RESULTS

A total of 1924 patients were randomly selected, and 1828 were included in the analysis. The diagnostic accuracy for EGC, which was 78.8% by using LCI and 68.4% by using WLI (p < .0001). More suspicious lesions were detected by LCI than by WLI (n = 1235 vs. 1036, p = .031), especially among differentiated EGC (p = .013). LCI greatly shortened the examination time compared with WLI (p = .019).

CONCLUSIONS

LCI has better accuracy and shorter examination time in diagnosing EGC than WLI (Clinical trial registration: NCT03092414).Key messagesCompared with white light imaging (WLI), the diagnostic accuracy, sensitivity and specificity increased by using LCI.More lesions were detected by LCI alone than by WLI alone, especially among differentiated EGC.LCI may be used as a screening tool for routine clinical observation.

Automatic detection of early gastric cancer in endoscopy based on Mask region-based convolutional neural networks (Mask R-CNN)(with video)

The artificial intelligence (AI)-assisted endoscopic detection of early gastric cancer (EGC) has been preliminarily developed. The currently used algorithms still exhibit limitations of large calculation and low-precision expression. The present study aimed to develop an endoscopic automatic detection system in EGC based on a mask region-based convolutional neural network (Mask R-CNN) and to evaluate the performance in controlled trials. For this purpose, a total of 4,471 white light images (WLIs) and 2,662 narrow band images (NBIs) of EGC were obtained for training and testing. In total, 10 of the WLIs (videos) were obtained prospectively to examine the performance of the RCNN system. Furthermore, 400 WLIs were randomly selected for comparison between the Mask R-CNN system and doctors. The evaluation criteria included accuracy, sensitivity, specificity, positive predictive value and negative predictive value. The results revealed that there were no significant differences between the pathological diagnosis with the Mask R-CNN system in the WLI test (χ² = 0.189, P=0.664; accuracy, 90.25%; sensitivity, 91.06%; specificity, 89.01%) and in the NBI test (χ² = 0.063, P=0.802; accuracy, 95.12%; sensitivity, 97.59%). Among 10 WLI real-time videos, the speed of the test videos was up to 35 frames/sec, with an accuracy of 90.27%. In a controlled experiment of 400 WLIs, the sensitivity of the Mask R-CNN system was significantly higher than that of experts (χ² = 7.059, P=0.000; 93.00% VS 80.20%), and the specificity was higher than that of the juniors (χ² = 9.955, P=0.000, 82.67% VS 71.87%), and the overall accuracy rate was higher than that of the seniors (χ² = 7.009, P=0.000, 85.25% VS 78.00%). On the whole, the present study demonstrates that the Mask R-CNN system exhibited an excellent performance status for the detection of EGC, particularly for the real-time analysis of WLIs. It may thus be effectively applied to clinical settings.

Kyoto international consensus report on anatomy, pathophysiology and clinical significance of the gastro-oesophageal junction

OBJECTIVE

An international meeting was organised to develop consensus on (1) the landmarks to define the gastro-oesophageal junction (GOJ), (2) the occurrence and pathophysiological significance of the cardiac gland, (3) the definition of the gastro-oesophageal junctional zone (GOJZ) and (4) the causes of inflammation, metaplasia and neoplasia occurring in the GOJZ.

DESIGN

Clinical questions relevant to the afore-mentioned major issues were drafted for which expert panels formulated relevant statements and textural explanations.A Delphi method using an anonymous system was employed to develop the consensus, the level of which was predefined as ≥80% of agreement. Two rounds of voting and amendments were completed before the meeting at which clinical questions and consensus were finalised.

RESULTS

Twenty eight clinical questions and statements were finalised after extensive amendments. Critical consensus was achieved: (1) definition for the GOJ, (2) definition of the GOJZ spanning 1 cm proximal and distal to the GOJ as defined by the end of palisade vessels was accepted based on the anatomical distribution of cardiac type gland, (3) chemical and bacterial (Helicobacter pylori) factors as the primary causes of inflammation, metaplasia and neoplasia occurring in the GOJZ, (4) a new definition of Barrett's oesophagus (BO).

CONCLUSIONS

This international consensus on the new definitions of BO, GOJ and the GOJZ will be instrumental in future studies aiming to resolve many issues on this important anatomic area and hopefully will lead to better classification and management of the diseases surrounding the GOJ.

Artificial Intelligence-Assisted Endoscopic Diagnosis of Early Upper Gastrointestinal Cancer: A Systematic Review and Meta-Analysis

Objective

The aim of this study was to assess the diagnostic ability of artificial intelligence (AI) in the detection of early upper gastrointestinal cancer (EUGIC) using endoscopic images.

Methods

Databases were searched for studies on AI-assisted diagnosis of EUGIC using endoscopic images. The pooled area under the curve (AUC), sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) with 95% confidence interval (CI) were calculated.

Results

Overall, 34 studies were included in our final analysis. Among the 17 image-based studies investigating early esophageal cancer (EEC) detection, the pooled AUC, sensitivity, specificity, PLR, NLR, and DOR were 0.98, 0.95 (95% CI, 0.95–0.96), 0.95 (95% CI, 0.94–0.95), 10.76 (95% CI, 7.33–15.79), 0.07 (95% CI, 0.04–0.11), and 173.93 (95% CI, 81.79–369.83), respectively. Among the seven patient-based studies investigating EEC detection, the pooled AUC, sensitivity, specificity, PLR, NLR, and DOR were 0.98, 0.94 (95% CI, 0.91–0.96), 0.90 (95% CI, 0.88–0.92), 6.14 (95% CI, 2.06–18.30), 0.07 (95% CI, 0.04–0.11), and 69.13 (95% CI, 14.73–324.45), respectively. Among the 15 image-based studies investigating early gastric cancer (EGC) detection, the pooled AUC, sensitivity, specificity, PLR, NLR, and DOR were 0.94, 0.87 (95% CI, 0.87–0.88), 0.88 (95% CI, 0.87–0.88), 7.20 (95% CI, 4.32–12.00), 0.14 (95% CI, 0.09–0.23), and 48.77 (95% CI, 24.98–95.19), respectively.

Conclusions

On the basis of our meta-analysis, AI exhibited high accuracy in diagnosis of EUGIC.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier PROSPERO (CRD42021270443).

The Accuracy of Artificial Intelligence in the Endoscopic Diagnosis of Early Gastric Cancer: Pooled Analysis Study

BACKGROUND

Artificial intelligence (AI) for gastric cancer diagnosis has been discussed in recent years. The role of AI in early gastric cancer is more important than in advanced gastric cancer since early gastric cancer is not easily identified in clinical practice. However, to our knowledge, past syntheses appear to have limited focus on the populations with early gastric cancer.

OBJECTIVE

The purpose of this study is to evaluate the diagnostic accuracy of AI in the diagnosis of early gastric cancer from endoscopic images.

METHODS

We conducted a systematic review from database inception to June 2020 of all studies assessing the performance of AI in the endoscopic diagnosis of early gastric cancer. Studies not concerning early gastric cancer were excluded. The outcome of interest was the diagnostic accuracy (comprising sensitivity, specificity, and accuracy) of AI systems. Study quality was assessed on the basis of the revised Quality Assessment of Diagnostic Accuracy Studies. Meta-analysis was primarily based on a bivariate mixed-effects model. A summary receiver operating curve and a hierarchical summary receiver operating curve were constructed, and the area under the curve was computed.

RESULTS

We analyzed 12 retrospective case control studies (n=11,685) in which AI identified early gastric cancer from endoscopic images. The pooled sensitivity and specificity of AI for early gastric cancer diagnosis were 0.86 (95% CI 0.75-0.92) and 0.90 (95% CI 0.84-0.93), respectively. The area under the curve was 0.94. Sensitivity analysis of studies using support vector machines and narrow-band imaging demonstrated more consistent results.

CONCLUSIONS

For early gastric cancer, to our knowledge, this was the first synthesis study on the use of endoscopic images in AI in diagnosis. AI may support the diagnosis of early gastric cancer. However, the collocation of imaging techniques and optimal algorithms remain unclear. Competing models of AI for the diagnosis of early gastric cancer are worthy of future investigation.

TRIAL REGISTRATION

PROSPERO CRD42020193223; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=193223.

Deep learning system compared with expert endoscopists in predicting early gastric cancer and its invasion depth and differentiation status (with videos)

BACKGROUND AND AIMS

We aimed to develop and validate a deep learning-based system that covers various aspects of early gastric cancer (EGC) diagnosis, including detecting gastric neoplasm, identifying EGC, and predicting EGC invasion depth and differentiation status. Herein, we provide a state-of-the-art comparison of the system with endoscopists using real-time videos in a nationwide human-machine competition.

METHODS

This multicenter, prospective, real-time, competitive comparative, diagnostic study enrolled consecutive patients who received magnifying narrow-band imaging endoscopy at the Peking University Cancer Hospital from June 9, 2020 to November 17, 2020. The offline competition was conducted in Wuhan, China, and the endoscopists and the system simultaneously read patients' videos and made diagnoses. The primary outcomes were sensitivity in detecting neoplasms and diagnosing EGCs.

RESULTS

One hundred videos, including 37 EGCs and 63 noncancerous lesions, were enrolled; 46 endoscopists from 44 hospitals in 19 provinces in China participated in the competition. The sensitivity rates of the system for detecting neoplasms and diagnosing EGCs were 87.81% and 100%, respectively, significantly higher than those of endoscopists (83.51% [95% confidence interval [CI], 81.23-85.79] and 87.13% [95% CI, 83.75-90.51], respectively). Accuracy rates of the system for predicting EGC invasion depth and differentiation status were 78.57% and 71.43%, respectively, slightly higher than those of endoscopists (63.75% [95% CI, 61.12-66.39] and 64.41% [95% CI, 60.65-68.16], respectively).

CONCLUSIONS

The system outperformed endoscopists in identifying EGCs and was comparable with endoscopists in predicting EGC invasion depth and differentiation status in videos. This deep learning-based system could be a powerful tool to assist endoscopists in EGC diagnosis in clinical practice.

Endoscopic diagnosis and treatment of gastric dysplasia and early cancer: Current evidence and what the future may hold

Gastric cancer accounts for a significant proportion of worldwide cancer-related morbidity and mortality. The well documented precancerous cascade provides an opportunity for clinicians to detect and treat gastric cancers at an endoscopically curable stage. In high prevalence regions such as Japan and Korea, this has led to the implementation of population screening programs. However, guidelines remain ambiguous in lower prevalence regions. In recent years, there have been many advances in the endoscopic diagnosis and treatment of early gastric cancer and precancerous lesions. More advanced endoscopic imaging has led to improved detection and characterization of gastric lesions as well as superior accuracy for delineation of margins prior to resection. In addition, promising early data on artificial intelligence in gastroscopy suggests a future role for this technology in maximizing the yield of advanced endoscopic imaging. Data on endoscopic resection (ER) are particularly robust in Japan and Korea, with high rates of curative ER and markedly reduced procedural morbidity. However, there is a shortage of data in other regions to support the applicability of protocols from these high prevalence countries. Future advances in endoscopic therapeutics will likely lead to further expansion of the current indications for ER, as both technology and proceduralist expertise continue to grow.

Effect of a deep learning-based system on the miss rate of gastric neoplasms during upper gastrointestinal endoscopy: a single-centre, tandem, randomised controlled trial

BACKGROUND

White light endoscopy is a pivotal first-line tool for the detection of gastric neoplasms. However, gastric neoplasms can be missed during upper gastrointestinal endoscopy due to the subtle nature of these lesions and varying skill among endoscopists. Here, we aimed to evaluate the effect of an artificial intelligence (AI) system designed to detect focal lesions and diagnose gastric neoplasms on reducing the miss rate of gastric neoplasms in clinical practice.

METHODS

This single-centre, randomised controlled, tandem trial was done at Renmin Hospital of Wuhan University, China. We recruited consecutive patients (≥18 years old) undergoing routine upper gastrointestinal endoscopy for screening, surveillance, or investigation of symptoms. Same-day tandem upper gastrointestinal endoscopy was done where patients first underwent either AI-assisted (AI-first) or routine (routine-first) white light endoscopy, followed immediately by the other procedure, with targeted biopsies for all detected lesions taken at the end of the second examination. Patients were randomly assigned (1:1) to the AI-first or routine-first group using a computer-generated random numerical series and block randomisation (block size of four). Endoscopists were not blinded to randomisation status, whereas patients and pathologists were. The primary endpoint was the miss rate of gastric neoplasms and the analysis was done per protocol. This trial is registered with the Chinese Clinical Trial Registry, ChiCTR2000034453, and has been completed.

FINDINGS

Between July 6, 2020, and Dec 11, 2020, 907 patients were randomly assigned to the AI-first group and 905 to the routine-first group. The gastric neoplasm miss rate was significantly lower in the AI-first group than in the routine-first group (6·1%, 95% CI 1·6-17·9 [3/49] vs 27·3%, 15·5-43·0 [12/44]; relative risk 0·224, 95% CI 0·068-0·744; p=0·015). The only reported adverse event was bleeding from a target lesion after biopsy.

INTERPRETATION

The use of an AI system during upper gastrointestinal endoscopy significantly reduced the gastric neoplasm miss rate. AI-assisted endoscopy has the potential to improve the yield of gastric neoplasms by endoscopists.

FUNDING

The Project of Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision and the Hubei Province Major Science and Technology Innovation Project.

Endoscopic Advances for Gastric Neoplasia Detection

This article explores advances in endoscopic neoplasia detection with supporting clinical evidence and future aims. The ability to detect early gastric neoplastic lesions amenable to curative endoscopic submucosal dissection provides the opportunity to decrease gastric cancer mortality rates. Newer imaging techniques offer enhanced views of mucosal and microvascular structures and show promise in differentiating benign from malignant lesions and improving targeted biopsies. Conventional chromoendoscopy is well studied and validated. Narrow band imaging demonstrates superiority over magnified white light. Autofluorescence imaging, i-scan, flexible spectral imaging color enhancement, and bright image enhanced endoscopy show promise but insufficient evidence to change current clinical practice.

Comparison of the diagnostic efficacy of blue laser imaging with narrow band imaging for gastric cancer and precancerous lesions: a meta-analysis

BACKGROUND AND AIMS

novel endoscopic techniques including narrowband imaging (NBI) and blue laser imaging (BLI) have led to the improved detection of early stage gastric cancer and precancerous lesions. However, these techniques are not generally thought to be equivalent at present and BLI is generally considered as superior to NBI. Therefore, this comprehensive meta-analysis aimed to definitively compare the diagnostic efficacy of NBI and BLI for the diagnosis of gastric cancer and precancerous lesions.

METHODS

relevant articles were identified via searches of the PubMed, Web of Science, Embase and Cochrane Library databases from their inception until October 2019. In total, 28 relevant studies were identified and incorporated into the meta-analysis. RevMan5.3 was used to assess the relative diagnostic efficacy of these two imaging modalities in these studies. The threshold was assessed using Meta-DiSc 1.4 and STATA 14.0 for bivariate regression modeling of pooled studies.

RESULTS

the pooled sensitivity of BLI for gastric cancer was 0.89 (0.80, 0.95) and the specificity was 0.92 (0.76, 0.98). The pooled sensitivity of NBI for gastric cancer was 0.83 (0.75, 0.89) and the specificity was 0.95 (0.91, 0.97). The pooled sensitivity of BLI for precancerous lesions was 0.81 (0.71, 0.87) and the specificity was 0.90 (0.80, 0.96). The pooled sensitivity of NBI for precancerous lesions was 0.80 (0.75, 0.85) and the specificity was 0.88 (0.77, 0.94).

CONCLUSIONS

this study showed that both BLI and NBI have a very high diagnostic efficacy for the detection of gastric cancer and precancerous lesions, the sensitivity and specificity of these two approaches were similar.

Systematic Review on Optical Diagnosis of Early Gastrointestinal Neoplasia

BACKGROUND

Meticulous endoscopic characterization of gastrointestinal neoplasias (GN) is crucial to the clinical outcome. Hereby the indication and type of resection (endoscopically, en-bloc or piece-meal, or surgical resection) are determined. By means of established image-enhanced (IEE) and magnification endoscopy (ME) GN can be characterized in terms of malignancy and invasion depth. In this context, the statistical evidence and accuracy of these diagnostic procedures should be elucidated. Here, we present a systematic review of the literature.

RESULTS

21 Studies could be found which met the inclusion criteria. In clinical prospective trials and meta-analyses, the diagnostic accuracy of >90% for characterization of malignant neoplasms could be documented, if ME with IEE was used in squamous cell esophageal cancer, stomach, or colonic GN.

CONCLUSIONS

Currently, by means of optical diagnosis, today's gastrointestinal endoscopy is capable of determining the histological subtype, exact lateral spread, and depth of invasion of a lesion. The prerequisites for this are an exact knowledge of the anatomical structures, the endoscopic classifications based on them, and a systematic learning process, which can be supported by training courses. More prospective clinical studies are required, especially in the field of Barrett's esophagus and duodenal neoplasia.

Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study

BACKGROUND AND AIMS

Narrow-band imaging with magnifying endoscopy (ME-NBI) has shown advantages in the diagnosis of early gastric cancer (EGC). However, proficiency in diagnostic algorithms requires substantial expertise and experience. In this study, we aimed to develop a computer-aided diagnostic model for EGM (EGCM) to analyze and assist in the diagnosis of EGC under ME-NBI.

METHODS

A total of 1777 ME-NBI images from 295 cases were collected from 3 centers. These cases were randomly divided into a training cohort (n = 170), an internal test cohort (ITC, n = 73), and an external test cohort (ETC, n = 52). EGCM based on VGG-19 architecture (Visual Geometry Group [VGG], Oxford University, Oxford, UK) with a single fully connected 2-classification layer was developed through fine-tuning and validated on all cohorts. Furthermore, we compared the model with 8 endoscopists with varying experience. Primary comparison measures included accuracy, area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

EGCM acquired AUCs of .808 in the ITC and .813 in the ETC. Moreover, EGCM achieved similar predictive performance as the senior endoscopists (accuracy: .770 vs .755, P = .355; sensitivity: .792 vs .767, P = .183; specificity: .745 vs .742, P = .931) but better than the junior endoscopists (accuracy: .770 vs .728, P < .05). After referring to the results of EGCM, the average diagnostic ability of the endoscopists was significantly improved in terms of accuracy, sensitivity, PPV, and NPV (P < .05).

CONCLUSIONS

EGCM exhibited comparable performance with senior endoscopists in the diagnosis of EGC and showed the potential value in aiding and improving the diagnosis of EGC by endoscopists.

Markers of gastric intestinal metaplasia under digital chromoendoscopy: systematic review and meta-analysis

Diagnosis of gastric intestinal metaplasia (GIM) under digital chromoendoscopy presents various markers. The diagnostic yield of each marker has shown variable results. A systematic review and meta-analysis were performed to evaluate the following markers: light blue crest (LBC), marginal turbid band (MTB), groove type (GT), white opaque substance (WOS). Discussion of their joint diagnosis, reliability, assessment of local GIM severity and influencing factors was also provided. PubMed, EMBASE, Cochrane Library and Web of science were searched. The Meta-DiSc and Stata software were used to analyze the data. Fourteen studies were included with a total of 3081 lesions. There were 12 studies for LBC, six for GT, four for MTB and one for WOS, respectively. The pooled results showed that the diagnostic sensitivity and specificity of LBC were 0.79 [95% confidence interval (CI) 0.76-0.81] and 0.95 (95% CI 0.94-0.96). The sensitivity of GT and MTB were 0.49 (95% CI 0.43-0.54) and 0.47 (95% CI 0.40-0.53), and the specificity were 0.92 (95% CI 0.89-0.94) and 0.92 (95% CI 0.89-0.95). The area under the summary receiver operating characteristic curve was 0.9532, 0.7791 and 0.9553 for LBC, GT and MTB, respectively. LBC resulted the most classic marker. Proper combined diagnosis can improve the diagnostic efficiency. Reliability of these markers was acceptable. These markers can help endoscopic to assess the severity of local GIM. Besides intestinal metaplasia, many factors can potentially interfere with the diagnosis.

Current Evidence and Future Perspective of Accuracy of Artificial Intelligence Application for Early Gastric Cancer Diagnosis With Endoscopy: A Systematic and Meta-Analysis

Background & Aims: Gastric cancer is the common malignancies from cancer worldwide. Endoscopy is currently the most effective method to detect early gastric cancer (EGC). However, endoscopy is not infallible and EGC can be missed during endoscopy. Artificial intelligence (AI)-assisted endoscopic diagnosis is a recent hot spot of research. We aimed to quantify the diagnostic value of AI-assisted endoscopy in diagnosing EGC.

Method: The PubMed, MEDLINE, Embase and the Cochrane Library Databases were searched for articles on AI-assisted endoscopy application in EGC diagnosis. The pooled sensitivity, specificity, and area under the curve (AUC) were calculated, and the endoscopists' diagnostic value was evaluated for comparison. The subgroup was set according to endoscopy modality, and number of training images. A funnel plot was delineated to estimate the publication bias.

Result: 16 studies were included in this study. We indicated that the application of AI in endoscopic detection of EGC achieved an AUC of 0.96 (95% CI, 0.94–0.97), a sensitivity of 86% (95% CI, 77–92%), and a specificity of 93% (95% CI, 89–96%). In AI-assisted EGC depth diagnosis, the AUC was 0.82(95% CI, 0.78–0.85), and the pooled sensitivity and specificity was 0.72(95% CI, 0.58–0.82) and 0.79(95% CI, 0.56–0.92). The funnel plot showed no publication bias.

Conclusion: The AI applications for EGC diagnosis seemed to be more accurate than the endoscopists. AI assisted EGC diagnosis was more accurate than experts. More prospective studies are needed to make AI-aided EGC diagnosis universal in clinical practice.

Gastric cancer- endoscopic treatment of early lesions, the West learns from the East

Gastric cancer still has one of the highest incidence rates worldwide. Screening programs have been established in high incidence regions, especially in Asia, but in the West, screening for gastric cancer is not generally recommended. Gastroscopy is the gold standard for diagnosing gastric cancer. For the treatment of early gastric cancer, endoscopic resection is the method of choice. With the ESD technique, larger lesions can be resected en-bloc. Guideline and extended guideline criteria for the choice of lesions for ESD have been evaluated extensively, initially in Asia and later in the West as well. For lesions which are out of indication, a surgical approach must be recommended. To detect early recurrence or metachronous lesions, follow-up should be performed after ER.

Quality in diagnostic upper gastrointestinal endoscopy for the detection and surveillance of gastric cancer precursor lesions: Position paper of AEG, SEED and SEAP

This position paper, sponsored by the Asociación Española de Gastroenterología [Spanish Association of Gastroenterology], the Sociedad Española de Endoscopia Digestiva [Spanish Gastrointestinal Endoscopy Society] and the Sociedad Española de Anatomía Patológica [Spanish Anatomical Pathology Society], aims to establish recommendations for performing an high quality upper gastrointestinal endoscopy for the screening of gastric cancer precursor lesions (GCPL) in low-incidence populations, such as the Spanish population. To establish the quality of the evidence and the levels of recommendation, we used the methodology based on the GRADE system (Grading of Recommendations Assessment, Development and Evaluation). We obtained a consensus among experts using a Delphi method. The document evaluates different measures to improve the quality of upper gastrointestinal endoscopy in this setting and makes recommendations on how to evaluate and treat the identified lesions. We recommend that upper gastrointestinal endoscopy for surveillance of GCPL should be performed by endoscopists with adequate training, administering oral premedication and use of sedation. To improve the identification of GCPL, we recommend the use of high definition endoscopes and conventional or digital chromoendoscopy and, for biopsies, NBI should be used to target the most suspicious areas of intestinal metaplasia. Regarding the evaluation of visible lesions, the risk of submucosal invasion should be evaluated with magnifying endoscopes and endoscopic ultrasound should be reserved for those with suspected deep invasion. In lesions amenable to endoscopic resection, submucosal endoscopic dissection is considered the technique of choice.

Magnifying endoscopy in detecting early gastric cancer: A network meta-analysis of prospective studies

BACKGROUND

Conventional white-light imaging endoscopy (C-WLI) had a significant number of misdiagnosis in early gastric cancer (EGC), and magnifying endoscopy (ME) combined with different optical imaging was more accurate in the diagnosis of EGC. This study aimed to evaluate the accuracy of ME and compare the accuracy of ME with different optical imaging in detecting EGC.

METHODS

A comprehensive literature search was conducted to identify all relevant studies. Pair-wise meta-analysis was conducted to evaluate the accuracy of ME, and Bayesian network meta-analysis was performed to combine direct and indirect evidence and estimate the relative effects.

RESULTS

Eight prospective studies were identified with a total of 5948 patients and 3 optical imaging in ME (ME with WLI (M-WLI), ME with narrow-band imaging (M-NBI), and ME with blue laser imaging (M-BLI)). Pair-wise meta-analysis showed a higher accuracy of ME than C-WLI (OR: 2.97, 95% CI: 1.68∼5.25). In network meta-analysis, both M-NBI and M-BLI were more accurate than M-WLI (OR: 2.56, 95% CI: 2.13∼3.13; OR: 3.13, 95% CI: 1.85∼5.71). There was no significant difference between M-NBI and M-BLI.

CONCLUSION

ME was effective in improving the detecting rate of EGC, especially with NBI or BLI.

Controversies in EUS: Do we need miniprobes?

This is the fifth in a series of papers entitled "Controversies in EUS." In the current paper, we deal with high-resolution catheter probes, otherwise known as EUS miniprobes (EUS-MPs). The application of miniprobes for early carcinomas in the entire intestinal tract, for subepithelial lesions, and for findings in the bile duct and pancreatic duct as well as endobronchial use is critically discussed. Submucous lesions, especially in the colon, but also early carcinomas in special cases are considered the most important indications. The argument is illustrated by numerous examples.

Near-focus magnification and second-generation narrow-band imaging for early gastric cancer in a randomized trial

BACKGROUND

Magnifying endoscopy with narrow-band imaging (NBI) is effective for the diagnosis of early gastric cancer (EGC). However, magnifying endoscopy is not yet popular globally because of the required level of skill and lack of availability. To overcome these problems, dual-focus endoscopy (standard- and near-focus (NF) modes) has been developed. In this study, we evaluated the diagnostic performance of NF with second-generation (2G)-NBI (NF-NBI) for the diagnosis of EGC.

METHODS

This was a secondary analysis of a multicenter randomized controlled trial of 4523 high-risk patients who underwent gastroscopies at 13 institutions in Japan. Patients were randomly assigned to white-light imaging (WLI) followed by 2G-NBI or to 2G-NBI followed by WLI. Lesions suspicious for EGC, newly detected by non-magnifying WLI or 2G-NBI, were subsequently observed with NF-NBI. All detected lesions were biopsied or resected. The diagnostic performance of NF-NBI was compared with the final histology.

RESULTS

A total of 870 detected lesions (145 EGC, 725 non-EGC) were analyzed. Overall diagnostic performance for EGC using NF-NBI was accuracy 87.7%, sensitivity 60.7%, specificity 93.1%, positive predictive value 63.8%, and negative predictive value 92.2%. There were no significant differences in diagnostic performance between lesions detected by WLI or 2G-NBI. For lesions diagnosed with high (333 lesions) and low (537 lesions) confidences, accuracy was 92.2% and 84.9%, sensitivity was 64.7% and 58.5%, and specificity was 90.5% and 88.8%, respectively.

CONCLUSION

The diagnostic performance of NF-NBI is good and acceptable for diagnosis of EGC in combination with either WLI or 2G-NBI.

Development and validation of a real-time artificial intelligence-assisted system for detecting early gastric cancer: A multicentre retrospective diagnostic study

Background

We aimed to develop and validate a real-time deep convolutional neural networks (DCNNs) system for detecting early gastric cancer (EGC).

Methods

All 45,240 endoscopic images from 1364 patients were divided into a training dataset (35823 images from 1085 patients) and a validation dataset (9417 images from 279 patients). Another 1514 images from three other hospitals were used as external validation. We compared the diagnostic performance of the DCNN system with endoscopists, and then evaluated the performance of endoscopists with or without referring to the system. Thereafter, we evaluated the diagnostic ability of the DCNN system in video streams. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value and Cohen's kappa coefficient were measured to assess the detection performance.

Finding

The DCNN system showed good performance in EGC detection in validation datasets, with accuracy (85.1%–91.2%), sensitivity (85.9%–95.5%), specificity (81.7%–90.3%), and AUC (0.887–0.940). The DCNN system showed better diagnostic performance than endoscopists and improved the performance of endoscopists. The DCNN system was able to process oesophagogastroduodenoscopy (OGD) video streams to detect EGC lesions in real time.

Interpretation

We developed a real-time DCNN system for EGC detection with high accuracy and stability. Multicentre prospective validation is needed to acquire high-level evidence for its clinical application.

Funding

This work was supported by the National Natural Science Foundation of China (grant nos. 81672935 and 81871947), Jiangsu Clinical Medical Center of Digestive System Diseases and Gastrointestinal Cancer (grant no. YXZXB2016002), and Nanjing Science and Technology Development Foundation (grant no. 2017sb332019).

Early gastric cancer and Artificial Intelligence: Is it time for population screening?

Gastric cancer is a common cause of death worldwide and its early detection is crucial to improve its prognosis. Its incidence varies throughout countries, and screening has been found to be cost-effective at least in high-incidence regions. Identification of individuals harbouring preneoplastic lesions and their surveillance or of those with early gastric cancer are extremely important processes and endoscopy play a key role for this purpose. Unfortunately, also quality and accuracy for endoscopic detection varies among centres and endoscopists. Recent studies about Artificial Intelligence applied to endoscopic imaging show that these technologies perform very well and could be extremely useful for endoscopists to achieve the accuracy needed for gastric cancer screening. Nonetheless, as its introduction in this field is very recent, most studies are carried out offline and its results in clinical practice need to be further validated namely by incorporating all the components/dimensions of endoscopy from pre to post-assessment.

Diagnosis of early gastric cancer using image enhanced endoscopy: a systematic approach

This paper provides an overview of the principles of a vessel plus surface (VS) classification system to explain the diagnostic system of early gastric cancer using image-enhanced magnifying endoscopy. Furthermore, this paper introduces the magnifying endoscopy simple diagnostic algorithm for gastric cancer (MEADA-G) developed according to the VS classification system, with a description of the procedures performed for diagnosis. In addition to the diagnostic system, white opaque substance (WOS), light blue crest (LBC), white globe appearance (WGA), and vessels within epithelial circle (VEC) patterns, which are representative findings that can be observed in the gastric mucosa by image-enhanced magnifying endoscopy, are also described. Image-enhanced magnifying endoscopy is particularly useful in the diagnosis of differentiated-type early gastric cancer. It is important to use the appropriate clinical strategies based on a comprehensive understanding of the usefulness and limitations of the diagnostic system described in this paper.

A protocol of systematic review and meta-analysis of narrow band imaging endoscopy in detection of early gastric cancer

BACKGROUND

Early gastric cancer is the fifth common malignancy and the third leading cause of cancer death throughout the world. However, it is not clear how endoscopic screening for early gastric cancer affects incidence or mortality. We performed a systematic review and meta-analysis to evaluate the relationship between endoscopic screening for the mortality and incidence of early gastric cancer.

MATERIALS AND METHODS

This protocol established in this study has been reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. Web of Science, PubMed, EMBASE, and the Cochrane Library were searched for cohort and case-control studies in cases without early gastric cancer until March 31, 2020. We will use a combination of Medical Subject Heading and free-text terms with various synonyms to search based on the Eligibility criteria. Two investigators independently reviewed the included studies and extracted relevant data. The relative risk and 95% confidence intervals were used as effect estimate. I-square test, substantial heterogeneity, sensitivity analysis, and publication bias assessment will be performed accordingly. Stata 15.0 and Review Manger 5.3 are used for meta-analysis and systematic review.

RESULTS

The results will be published in a peer-reviewed journal.

CONCLUSION

The results of this review will be widely disseminated through peer-reviewed publications and conference presentations. This evidence may also provide helpful evidence of whether endoscopic screening would reduce the mortality and incidence of early gastric cancer.

PROSPERO REGISTRATION NUMBER

CRD42020171053.

Recent advances in the detection and management of early gastric cancer and its precursors

Despite declines in incidence, gastric cancer remains a disease with a poor prognosis and limited treatment options due to its often late stage of diagnosis. In contrast, early gastric cancer has a good to excellent prognosis, with 5-year survival rates as high as 92.6% after endoscopic resection. There remains an East-West divide for this disease, with high incidence countries such as Japan seeing earlier diagnoses and reduced mortality, in part thanks to the success of a national screening programme. With missed cancers still prevalent at upper endoscopy in the West, and variable approaches to assessment of the high-risk stomach, the quality of endoscopy we provide must be a focus for improvement, with particular attention paid to the minority of patients at increased cancer risk. High-definition endoscopy with virtual chromoendoscopy is superior to white light endoscopy alone. These enhanced imaging modalities allow the experienced endoscopist to accurately and robustly detect high-risk lesions in the stomach. An endoscopy-led staging strategy would mean biopsies could be targeted to histologically confirm the endoscopic impression of premalignant lesions including atrophic gastritis, gastric intestinal metaplasia, dysplasia and early cancer. This approach to quality improvement will reduce missed diagnoses and, combined with the latest endoscopic resection techniques performed at expert centres, will improve early detection and ultimately patient outcomes. In this review, we outline the latest evidence relating to diagnosis, staging and treatment of early gastric cancer and its precursor lesions.

Guidelines for endoscopic diagnosis of early gastric cancer

The Japan Gastroenterological Endoscopy Society developed the Guideline for Endoscopic Diagnosis of Early Gastric Cancer based on scientific methods. Endoscopy for the diagnosis of early gastric cancer has been acknowledged as a useful and highly precise examination, and its use has become increasingly more common in recent years. However, the level of evidence in this field is low, and it is often necessary to determine recommendations based on expert consensus only. This clinical practice guideline consists of the following sections to provide the current guideline: [I] Risk stratification of gastric cancer before endoscopic examination, [II] Detection of early gastric cancer, [III] Qualitative diagnosis of early gastric cancer, [IV] Diagnosis to choose the therapeutic strategy for gastric cancer, [V] Risk stratification after endoscopic examination, and [VI] Surveillance of early gastric cancer.

Narrow band imaging characteristics of gastric polypoid lesions: a single-center prospective pilot study

INTRODUCTION

Gastric polypoid lesions (GPL) are endoscopic findings whose histological nature is difficult to determine with white-light endoscopy. Hyperplastic polyps (HP), type-1 gastric carcinoids (T1-GC) and adenomas are the most frequent GPL needing different management. Narrow-band imaging (NBI) has high accuracy for gastric malignant lesions but few studies assessed whether GPL display specific NBI characteristics. We aimed to investigate the endoscopic NBI appearances of GPL.

MATERIALS AND METHODS

During gastroscopies, images of GPL were recorded, and lesions were removed for histological evaluation. Two endoscopists blindly reviewed the digital images and registered the endoscopic NBI appearances on a specific check-list. GPL were categorized in HP, adenomas and T1-GC using histology as gold standard.

RESULTS

Overall 52 GPL, observed in 40 patients [F55%; age 63 (36-85) years], were included: 29 (55.8%) HP; 18 (34.6%) T1-GC; 5 (9.6%) adenomas. The median size was seven (2-35) mm. A regular circular mucosal pattern was more frequently observed in HP and T1-GC compared to adenomas (P < 0.001). T1-GC showed a central erosion in 77.8% (P < 0.001 versus HP) with a clear demarcation line in 33.3%. Adenomas had tubule-villous mucosal pattern in 80% (P = 0.01 versus other lesions).

CONCLUSION

NBI analysis of the mucosal pattern seems to be effective to endoscopically discriminate between adenomas and HP while the main characteristic of T1-GC seems to be the presence of a central erosion, sometimes with demarcation line. The endoscopic NBI characterization of GPL may contribute to optimize the management of these lesions.

Recent advances in diagnostic upper endoscopy

BACKGROUND

Esophageo-gastro-duodenoscopy (EGD) is an important procedure used for detection and diagnosis of esophago-gastric lesions. There exists no consensus on the technique of examination.

AIM

To identify recent advances in diagnostic EGDs to improve diagnostic yield.

METHODS

We queried the PubMed database for relevant articles published between January 2001 and August 2019 as well as hand searched references from recently published endoscopy guidelines. Keywords used included free text and MeSH terms addressing quality indicators and technological innovations in EGDs. Factors affecting diagnostic yield and EGD quality were identified and divided into the follow segments: Pre endoscopy preparation, sedation, examination schema, examination time, routine biopsy, image enhanced endoscopy and future developments.

RESULTS

We identified 120 relevant abstracts of which we utilized 67 of these studies in our review. Adequate pre-endoscopy preparation with simethicone and pronase increases gastric visibility. Proper sedation, especially with propofol, increases patient satisfaction after procedure and may improve detection of superficial gastrointestinal lesions. There is a movement towards mandatory picture documentation during EGD as well as dedicating sufficient time for examination improves diagnostic yield. The use of image enhanced endoscopy and magnifying endoscopy improves detection of squamous cell carcinoma and gastric neoplasm. The magnifying endoscopy simple diagnostic algorithm is useful for diagnosis of early gastric cancer.

CONCLUSION

There is a steady momentum in the past decade towards improving diagnostic yield, quality and reporting in EGDs. Other interesting innovations, such as Raman spectroscopy, endocytoscopy and artificial intelligence may have widespread endoscopic applications in the near future.

Convolutional neural network for the diagnosis of early gastric cancer based on magnifying narrow band imaging

BACKGROUND

Magnifying endoscopy with narrow band imaging (M-NBI) has been applied to examine early gastric cancer by observing microvascular architecture and microsurface structure of gastric mucosal lesions. However, the diagnostic efficacy of non-experts in differentiating early gastric cancer from non-cancerous lesions by M-NBI remained far from satisfactory. In this study, we developed a new system based on convolutional neural network (CNN) to analyze gastric mucosal lesions observed by M-NBI.

METHODS

A total of 386 images of non-cancerous lesions and 1702 images of early gastric cancer were collected to train and establish a CNN model (Inception-v3). Then a total of 341 endoscopic images (171 non-cancerous lesions and 170 early gastric cancer) were selected to evaluate the diagnostic capabilities of CNN and endoscopists. Primary outcome measures included diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value.

RESULTS

The sensitivity, specificity, and accuracy of CNN system in the diagnosis of early gastric cancer were 91.18%, 90.64%, and 90.91%, respectively. No significant difference was spotted in the specificity and accuracy of diagnosis between CNN and experts. However, the diagnostic sensitivity of CNN was significantly higher than that of the experts. Furthermore, the diagnostic sensitivity, specificity and accuracy of CNN were significantly higher than those of the non-experts.

CONCLUSIONS

Our CNN system showed high accuracy, sensitivity and specificity in the diagnosis of early gastric cancer. It is anticipated that more progress will be made in optimization of the CNN diagnostic system and further development of artificial intelligence in the medical field.

British Society of Gastroenterology guidelines on the diagnosis and management of patients at risk of gastric adenocarcinoma

Gastric adenocarcinoma carries a poor prognosis, in part due to the late stage of diagnosis. Risk factors include Helicobacter pylori infection, family history of gastric cancer-in particular, hereditary diffuse gastric cancer and pernicious anaemia. The stages in the progression to cancer include chronic gastritis, gastric atrophy (GA), gastric intestinal metaplasia (GIM) and dysplasia. The key to early detection of cancer and improved survival is to non-invasively identify those at risk before endoscopy. However, although biomarkers may help in the detection of patients with chronic atrophic gastritis, there is insufficient evidence to support their use for population screening. High-quality endoscopy with full mucosal visualisation is an important part of improving early detection. Image-enhanced endoscopy combined with biopsy sampling for histopathology is the best approach to detect and accurately risk-stratify GA and GIM. Biopsies following the Sydney protocol from the antrum, incisura, lesser and greater curvature allow both diagnostic confirmation and risk stratification for progression to cancer. Ideally biopsies should be directed to areas of GA or GIM visualised by high-quality endoscopy. There is insufficient evidence to support screening in a low-risk population (undergoing routine diagnostic oesophagogastroduodenoscopy) such as the UK, but endoscopic surveillance every 3 years should be offered to patients with extensive GA or GIM. Endoscopic mucosal resection or endoscopic submucosal dissection of visible gastric dysplasia and early cancer has been shown to be efficacious with a high success rate and low rate of recurrence, providing that specific quality criteria are met.

An Asian consensus on standards of diagnostic upper endoscopy for neoplasia

BACKGROUND

This is a consensus developed by a group of expert endoscopists aiming to standardise the preparation, process and endoscopic procedural steps for diagnosis of early upper gastrointestinal (GI) cancers.

METHOD

The Delphi method was used to develop consensus statements through identification of clinical questions on diagnostic endoscopy. Three consensus meetings were conducted to consolidate the statements and voting. We conducted a systematic literature search on evidence for each statement. The statements were presented in the second consensus meeting and revised according to comments. The final voting was conducted at the third consensus meeting on the level of evidence and agreement.

RESULTS

Risk stratification should be conducted before endoscopy and high risk endoscopic findings should raise an index of suspicion. The presence of premalignant mucosal changes should be documented and use of sedation is recommended to enhance detection of superficial upper GI neoplasms. The use of antispasmodics and mucolytics enhanced visualisation of the upper GI tract, and systematic endoscopic mapping should be conducted to improve detection. Sufficient examination time and structured training on diagnosis improves detection. Image enhanced endoscopy in addition to white light imaging improves detection of superficial upper GI cancer. Magnifying endoscopy with narrow-band imaging is recommended for characterisation of upper GI superficial neoplasms. Endoscopic characterisation can avoid unnecessary biopsy.

CONCLUSION

This consensus provides guidance for the performance of endoscopic diagnosis and characterisation for early gastric and oesophageal neoplasia based on the evidence. This will enhance the quality of endoscopic diagnosis and improve detection of early upper GI cancers.

Presence of blood in gastric juice: A sensitive marker for gastric cancer screening in a poor resource setting

BACKGROUND

Gastric cancer survival rates in Africa are low as many cases are diagnosed late. Currently, there are no inexpensive, non-invasive and simple techniques that can be employed in poor resource settings for early case detection. In this study, we explored the possibility using blood in gastric juice as a screening tool to identify patients requiring referral for endoscopy.

METHODS

The study was conducted at the University Teaching Hospital endoscopy unit in Lusaka, Zambia. During esophagogastroduodenoscopy, gastric juice was aspirated and the pH determined using pH paper test strips. The presence of blood was tested using urinalysis reagent strips.

RESULTS

We enrolled 276 patients; 147(53%) were female and median age was 49 years (IQR 40-64 years). The presence of blood was associated with mucosal lesions, [OR 2.1; 95% CI 1.2-3.7, P = 0.004]. It was also associated with gastric cancer, [OR 6.7; 95% CI 2-35, P = 0.0005], even at 1:10 and 1:100 dilutions, [OR 5.4; 95% CI 2.3-13.8, P<0.0001] and [OR 9.1; 95% CI 3.5-23, P<0.0001] respectively. The sensitivity for gastric cancer detection using blood in gastric juice was 91% and the specificity was 41%. Analysis using the intensity of blood in gastric juice yielded an area under the receiver operating characteristic curve of 0.78; 95% CI 0.71-0.86 with a sensitivity of 79% and a specificity of 77%.

CONCLUSIONS

The presence of blood in gastric juice is associated with gastric mucosal lesions. It has a high sensitivity but low specificity for gastric cancer detection.