Diagnostic performance of conventional endoscopy in the identification of submucosal invasion by early gastric cancer: the "non-extension sign" as a simple diagnostic marker

Machine learning models to predict submucosal invasion in early gastric cancer based on endoscopy features and standardized color metrics

Conventional endoscopy is widely used in the diagnosis of early gastric cancers (EGCs), but the graphical features were loosely defined and dependent on endoscopists' experience. We aim to establish a more accurate predictive model for infiltration depth of early gastric cancer including a standardized colorimetric system, which demonstrates promising clinical implication. A retrospective study of 718 EGC cases was performed. Clinical and pathological characteristics were included, and Commission Internationale de l'Eclariage (CIE) standard colorimetric system was used to evaluate the chromaticity of lesions. The predicting models were established in the derivation set using multivariate backward stepwise logistic regression, decision tree model, and random forest model. Logistic regression shows location, macroscopic type, length, marked margin elevation, WLI color difference and histological type are factors significantly independently associated with infiltration depth. In the decision tree model, margin elevation, lesion located in the lower 1/3 part, WLI a*color value, b*color value, and abnormal thickness in enhanced CT were selected, which achieved an AUROC of 0.810. A random forest model was established presenting the importance of each feature with an accuracy of 0.80, and an AUROC of 0.844. Quantified color metrics can improve the diagnostic precision in the invasion depth of EGC. We have developed a nomogram model using logistic regression and machine learning algorithms were also explored, which turned out to be helpful in decision-making progress.

E-learning system to improve the endoscopic diagnosis of early gastric cancer

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.

Coexistence of early gastric cancer and benign submucosal lesions mimic invasive cancer: a retrospective multicenter experience

OBJECTIVE

To present a study to identify the characteristics of coexisting early gastric cancer (EGC) and benign submucosal lesions, with the aim of reducing the adverse consequences of overdiagnosis and overtreatment.

METHODS

In this retrospective study, we searched the endoscopic databases of three tertiary centers. We screened of patients suspected of early gastric cancer submucosal infiltration by conventional endoscopy and ultimately selected for endoscopic submucosal dissection treatment after endoscopic ultrasonography and magnifying endoscopy with narrow-band imaging examination. Patients with coexisting EGC and benign submucosal lesions in histological sections were included. Clinical data and endoscopic images were reviewed. To evaluate the precision of endoscopists' diagnoses for this type of lesion, eight endoscopists with different experiences were recruited to judge the infiltration depth of these lesions and analyze the accuracy rate.

RESULTS

We screened 520 patients and retrospectively identified 18 EGC patients with an invasive cancer-like morphology. The most common lesion site was the cardia (12/18, 66.67%). The coexisting submucosal lesions could be divided into solid (5/18, 27.78%) and cystic (13/18, 72.22%). The most common type of submucosal lesion was gastritis cystica profunda (12/18, 66.67%), whereas leiomyoma was the predominant submucosal solid lesion (3/18, 16.67%). Ten (55.56%) patients < underwent endoscopic ultrasonography; submucosal lesions were definitively diagnosed in 6 patients (60.00%). The accuracy of judgement of the infiltration depth was significantly lower in cases of coexistence of EGC with benign submucosal lesions (EGC-SML) than in EGC (38.50% versus 65.60%, P = 0.0167). The rate of over-diagnosis was significantly higher within the EGC-SML group compared to the EGC group (59.17% versus 10.83%, P < 0.0001).

CONCLUSIONS

We should be aware of the coexistence of EGC and benign submucosal lesions, the most common of which is early cardiac-differentiated cancer with gastritis cystica profunda.

Absence of the Nonextension Sign as a Marker for Endoscopic Submucosal Dissection Suitability

Early gastric cancer is defined as gastric cancer confined to the mucosa or submucosa, irrespective of lymph node metastasis. Endoscopic submucosal dissection is a standard treatment of early gastric cancer. The nonextension sign consists of a protrusion of the surrounding mucosa into the lumen, resembling a trapezoidal shape. This phenomenon occurs when massive submucosal invasion by a cancer increases the thickness and rigidity of the gastric wall and may be useful to differentiate between mucosal or microinvasive submucosal and invasive submucosal cancers. Our case demonstrates the usefulness of the absence of the conventional endoscopic nonextension sign as a marker to decide the adequate approach for mucosal lesions.

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.

Intensive Systematic "Train-the-Trainer" Course as an Effective Strategy to Improve Detection of Early Gastric Cancer: A Multicenter Retrospective Study

BACKGROUND

To improve the diagnosis of early gastric cancer (EGC), a train-the-trainer (TTT) course was developed. This trial aimed to investigate whether TTT courses from trained trainers could improve trainees' EGC detection.

METHODS

In this multi-center, retrospective study, the training was carried out 8 times in one year. Clinical records one year before ("2016"), during ("2017"), and after ("2018") the course were collected. The primary endpoint was the improvement of EGC detection rate after TTT courses.

RESULTS

Twenty-four trainees from 17 hospitals were included in this study. A total of 123,416 esophagogastroduodenoscopy and 65,570 colonoscopy procedures were analyzed. The early gastric cancer detection rate (EDR) was 0.101% in 2016, which significantly increased to 0.338% in 2018 (p = 0.015). The early gastric cancer ratio (ECR, ratio of newly detected EGCs to all newly detected gastric cancers) in 2016 was 8.440%, which consistently increased to 11.853% and 19.778% in 2017 and 2018 (p = 0.006), respectively. In contrast, the advanced gastric cancer detection rate (ADR) was similar before, during, or after the course (p = 0.987). The 3-year EDR, ECR, and ADR in esophageal and colorectal cancer were not significantly different.

CONCLUSIONS

The systematic training course can improve EGC detection rate and may be an effective educational strategy to reduce gastrointestinal cancers mortality.

Endoscopic diagnosis and treatment in gastric cancer: Current evidence and new perspectives

Gastric cancer is the fifth most common cause of cancer related deaths worldwide. Despite advancement in endoscopic techniques, the majority of the cases are diagnosed at late stage, when the curative treatment options are very limited. The early gastric cancer (EGC) on the other side is potentially curable, and in selected cases endoscopic resection techniques offer similar survival rates then surgical resection. The detection of EGC is endoscopically challenging and requires high quality examination. Recent data show that close to 10% of the gastric cancer cases had a previous negative endoscopy. This highlights the urgent need to improve the quality of the endoscopy services, what can be achieved by increasing the awareness of gastroenterologists and continuously monitoring the key performance indicators of upper gastrointestinal endoscopy. Newer endoscopic imaging techniques are also becoming commonly available to aid the detection of gastric premalignant lesions and EGC. High-definition endoscopy with image enhancement techniques is preferred over white light endoscopy to recognize these lesions, and they are also useful to determine the invasion depth of EGC. The endoscopic optical characterization of lesions is necessary for the selection of proper resection method and decide whether endoscopic resection techniques can be considered. Artificial intelligence systems aid the detection of EGC and can help to determine the depth of invasion. Endoscopic mucosal resection and endoscopic submucosal dissection requires centralized care and tertiary referral centers with appropriate expertise to ensure proper patient selection, high success rate and low adverse event rate. Appropriately scheduled endoscopic surveillance of high-risk patients, premalignant lesions and after resection of EGC is also important in the early detection and successful treatment of gastric cancer.

Cooperation between artificial intelligence and endoscopists for diagnosing invasion depth of early gastric cancer

BACKGROUND AND STUDY AIMS

The diagnostic ability of endoscopists to determine invasion depth of early gastric cancer is not favorable. We designed an artificial intelligence (AI) classifier for differentiating intramucosal and submucosal gastric cancers and examined it to establish a diagnostic method based on cooperation between AI and endoscopists.

PATIENTS AND METHODS

We prepared 500 training images using cases of mainly depressed-type early gastric cancer from 250 intramucosal cancers and 250 submucosal cancers. We also prepared 200 test images each of 100 cancers from another institution. We designed an AI classifier to differentiate between intramucosal and submucosal cancers by deep learning. We examined the performance of the AI classifier and the majority vote of the endoscopists as high confidence and low confidence diagnostic probability, respectively, and cooperatively combined them to establish a diagnostic method providing high accuracy.

RESULTS

Internal evaluation of the training images showed that accuracy, sensitivity, specificity, and F1 measure by the AI classifier were 77%, 76%, 78%, and 0.768, and those of the majority vote of the endoscopists were 72.6%, 53.6%, 91.6%, and 0.662, respectively. A diagnostic method based on cooperation between AI and the endoscopists showed that the respective values were 78.0%, 76.0%, 80.0%, and 0.776 for the test images. The value of F1 measure was especially higher than those by AI or the endoscopists alone.

CONCLUSIONS

Cooperation between AI and endoscopists improved the diagnostic ability to determine invasion depth of early gastric cancer.

Diagnostic value of endoscopic ultrasonography for the depth of gastric cancer suspected of submucosal invasion: a multicenter prospective study

BACKGROUND

Although the combination of conventional endoscopy (CE) and endoscopic ultrasonography (EUS) is useful for predicting the depth of early gastric cancer (EGC), the diagnostic value of EUS for submucosal (SM) invasive cancer has not been fully investigated.

METHODS

We conducted a multicenter prospective study from May 2017 to January 2021 to evaluate the validity of a diagnostic strategy combining CE and EUS and to clarify the additional value of EUS for EGC suspected of SM invasion. In each case, the diagnosis was first made using CE, followed by EUS, and finally confirmed using a combination algorithm.

RESULTS

A total of 180 patients with EGC were enrolled from 10 institutions, of which 175 were analyzed. The histopathological depths were M, SM1, SM2, and ≥ MP in 72, 16, 64, and 23 lesions, respectively. Treatment included 92 endoscopic submucosal dissection cases and 83 surgical cases. The overall diagnostic accuracy classified by M-SM1 or SM2-MP was 58.3% for CE, 75.7% for EUS, and 78.9% for the combination of CE and EUS; the latter two were significantly higher than that of CE alone (P < 0.001). The CE, EUS, and combination accuracy rates in 108 differentiated-type lesions were 51.9%, 77.4%, and 79.6%, respectively; the latter two were significantly higher than CE alone (P < 0.001). A significant additive effect of EUS was observed in CE-SM2 low-confidence lesions but not in CE-M-SM1 lesions or in CE-SM2 high-confidence lesions. Among the nine CE findings, irregular surface, submucosal tumor-like elevation, and non-extension signs were significant independent markers of pSM2-MP. Poorly delineated EUS lesions were misdiagnosed.

CONCLUSIONS

EUS provides additional value for differentiated-type and CE-SM2 low-confidence EGCs in diagnosing invasion depth.

CLINICAL REGISTRATION NUMBER

UMIN000025862.

Current Status of Artificial Intelligence-Based Computer-Assisted Diagnosis Systems for Gastric Cancer in Endoscopy

Artificial intelligence (AI) is gradually being utilized in various fields as its performance has been improving with the development of deep learning methods, availability of big data, and the progression of computer processing units. In the field of medicine, AI is mainly implemented in image recognition, such as in radiographic and pathologic diagnoses. In the realm of gastrointestinal endoscopy, although AI-based computer-assisted detection/diagnosis (CAD) systems have been applied in some areas, such as colorectal polyp detection and diagnosis, so far, their implementation in real-world clinical settings is limited. The accurate detection or diagnosis of gastric cancer (GC) is one of the challenges in which performance varies greatly depending on the endoscopist's skill. The diagnosis of early GC is especially challenging, partly because early GC mimics atrophic gastritis in the background mucosa. Therefore, several CAD systems for GC are being actively developed. The development of a CAD system for GC is considered challenging because it requires a large number of GC images. In particular, early stage GC images are rarely available, partly because it is difficult to diagnose gastric cancer during the early stages. Additionally, the training image data should be of a sufficiently high quality to conduct proper CAD training. Recently, several AI systems for GC that exhibit a robust performance, owing to being trained on a large number of high-quality images, have been reported. This review outlines the current status and prospects of AI use in esophagogastroduodenoscopy (EGDS), focusing on the diagnosis of GC.

Clinical factors associated with noncurative endoscopic submucosal dissection for the expanded indication of intestinal-type early gastric cancer: Post hoc analysis of a multi-institutional, single-arm, confirmatory trial (JCOG0607)

OBJECTIVES

The multi-institutional, single-arm, confirmatory trial JCOG0607 showed excellent efficacy of endoscopic submucosal dissection (ESD) for the expanded indication of intramucosal intestinal-type early gastric cancer (EGC), which consists of two groups: lesions >2 cm if clinical finding of ulcer (cUL)-negative, or those ≤3 cm if cUL-positive because of the expected low risk of lymph node metastasis. However, the proportion of noncurative resections (NCR) requiring additional surgery was high (32.4%). This post hoc analysis aimed to explore the clinical factors associated with NCR.

METHODS

As the expanded indication includes two different groups, we explored the clinical factors associated with NCR separately in cUL-negative (>2 cm) and cUL-positive (≤3 cm) groups using the log-linear model.

RESULTS

Two hundred and sixty cUL-negative and 206 cUL-positive EGCs were analyzed. The proportions of NCR were 33.8% in the cUL-negative group and 29.6% in the cUL-positive group. A multivariable analysis demonstrated that moderately differentiated predominant histology diagnosed in pretreatment biopsy (risk ratio [RR] 1.93, 95% confidence interval [CI] 1.34-2.77, P < 0.001) and lesion in the upper stomach (RR 1.75, 95% CI 1.03-2.96, P = 0.038) in the cUL-negative EGCs, and tumor size >2 cm (RR 1.78, 95% CI 1.22-2.58, P = 0.003) and female sex (RR 1.62, 95% CI 1.07-2.44, P = 0.021) in the cUL-positive EGCs were independent factors associated with NCR.

CONCLUSIONS

Clinical risk factors associated with NCR were different between cUL-negative and cUL-positive EGCs. To avoid NCR, we need to take these factors into account when deciding expanded indications for ESD.

Endoscopic Treatment of Superficial Gastric Cancer: Present Status and Future

Although the mortality rates of gastric cancer (GC) are gradually declining, gastric cancer is still the fourth leading cause of cancer-related death worldwide. This may be due to the high rate of patients who are diagnosed with GC at advanced stages. However, in countries such as Japan with endoscopic screening systems, more than half of GCs are discovered at an early stage, enabling endoscopic resection (ER). Especially after the introduction of endoscopic submucosal dissection (ESD) in Japan around 2000, a high en bloc resection rate allowing pathological assessment of margin and depth has become possible. While ER is a diagnostic method of treatment and may not always be curative, it is widely accepted as standard treatment because it is less invasive than surgery and can provide an accurate diagnosis for deciding whether additional surgery is necessary. The curability of ER is currently assessed by the completeness of primary tumor removal and the possibility of lymph node metastasis. This review introduces methods, indications, and curability criteria for ER of EGC. Despite recent advances, several problems remain unsolved. This review will also outline the latest evidence concerning future issues.

Application of convolutional neural networks for evaluating the depth of invasion of early gastric cancer based on endoscopic images

BACKGROUND AND AIM

Recently, artificial intelligence (AI) has been used in endoscopic examination and is expected to help in endoscopic diagnosis. We evaluated the feasibility of AI using convolutional neural network (CNN) systems for evaluating the depth of invasion of early gastric cancer (EGC), based on endoscopic images.

METHODS

This study used a deep CNN model, ResNet152. From patients who underwent treatment for EGC at our hospital between January 2012 and December 2016, we selected 100 consecutive patients with mucosal (M) cancers and 100 consecutive patients with cancers invading the submucosa (SM cancers). A total of 3508 non-magnifying endoscopic images of EGCs, including white-light imaging, linked color imaging, blue laser imaging-bright, and indigo-carmine dye contrast imaging, were included in this study. A total of 2288 images from 132 patients served as the development dataset, and 1220 images from 68 patients served as the testing dataset. Invasion depth was evaluated for each image and lesion. The majority vote was applied to lesion-based evaluation.

RESULTS

The sensitivity, specificity, and accuracy for diagnosing M cancer were 84.9% (95% confidence interval [CI] 82.3%-87.5%), 70.7% (95% CI 66.8%-74.6%), and 78.9% (95% CI 76.6%-81.2%), respectively, for image-based evaluation, and 85.3% (95% CI 73.4%-97.2%), 82.4% (95% CI 69.5%-95.2%), and 83.8% (95% CI 75.1%-92.6%), respectively, for lesion-based evaluation.

CONCLUSIONS

The application of AI using CNN to evaluate the depth of invasion of EGCs based on endoscopic images is feasible, and it is worth investing more effort to put this new technology into practical use.

Predicting the depth of superficial adenocarcinoma of the esophagogastric junction

BACKGROUND AND AIM

Preoperative determination of the invasion depth of superficial adenocarcinoma of the esophagogastric junction is important for appropriate endoscopic or surgical resection. There are no objective criteria regarding this; therefore, we investigated the factors associated with the invasion depth of superficial adenocarcinoma of the esophagogastric junction.

METHODS

This retrospective study evaluated patients with superficial adenocarcinoma of the esophagogastric junction who had undergone endoscopic or surgical resection at a Japanese tertiary cancer center between April 2004 and December 2017. We analyzed endoscopic features of intramucosal to slight submucosal (M-SM1; < 500 μm) and deep submucosal (SM2; ≥ 500 μm) adenocarcinoma of the esophagogastric junction and extracted significant factors associated with and assessed the diagnostic performance of endoscopic features for SM2 lesion.

RESULTS

A total of 106 cases were included in this study. Multivariate analysis indicated that depressed or protruded type (odds ratio [OR], 11.1), lesion size ≥ 15 mm (OR, 3.11), uneven surface (OR, 6.31), and subsquamous extension (OR, 5.41) were significantly associated with SM2 adenocarcinomas of the esophagogastric junction. When the macroscopic type was depressed or protruded, high sensitivity (97%) but fair specificity (46%) were observed for SM2 adenocarcinoma of the esophagogastric junction, whereas uneven surface and subsquamous extension showed high specificity (96% and 87%) but fair sensitivity (36% and 46%).

CONCLUSIONS

Depressed or protruded type, lesion size ≥ 15 mm, uneven surface, and subsquamous extension were significantly associated with the invasion depth of superficial adenocarcinoma of the esophagogastric junction. These endoscopic features are useful in determining the treatment method preoperatively.

Clinical TNM staging for esophageal, gastric, and colorectal cancers in the era of neoadjuvant therapy: A systematic review of the literature

AIM

Clinical staging is vital for selecting appropriate candidates and designing neoadjuvant treatment strategies for advanced tumors. The aim of this review was to evaluate diagnostic abilities of clinical TNM staging for gastrointestinal, gastrointestinal cancers.

METHODS

We conducted a systematic review of recent publications to evaluate the accuracy of diagnostic modalities on gastrointestinal cancers. A systematic literature search was performed in PubMed/MEDLINE using the keywords "TNM staging," "T4 staging," "distant metastases," "esophageal cancer," "gastric cancer," and "colorectal cancer," and the search terms used in Cochrane Reviews between January 2005 to July 2020. Articles focusing on preoperative diagnosis of: (a) depth of invasion; (b) lymph node metastases; and (c) distant metastases were selected.

RESULTS

After a full-text search, a final set of 55 studies (17 esophageal cancer studies, 26 gastric cancer studies, and 12 colorectal cancer studies) were used to evaluate the accuracy of clinical TNM staging. Positron emission tomography-computed tomography (PET-CT) and/or magnetic resonance imaging (MRI) were the best modalities to assess distant metastases. Fat and fiber mode of CT may be useful for T4 staging of esophageal cancer, CT was a partially reliable modality for lymph node staging in gastric cancer, and CT combined with MRI was the most reliable modality for liver metastases from colorectal cancer.

CONCLUSION

The most reliable diagnostic modality differed among gastrointestinal cancers depending on the type of cancer. Therefore, we propose diagnostic algorithms for clinical staging for each type of cancer.

Application of artificial intelligence-driven endoscopic screening and diagnosis of gastric cancer

The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques become available. The advent of image-enhanced and magnifying endoscopies has highlighted the step toward perfecting endoscopic screening and diagnosis of gastric lesions. Simultaneously, with the development of convolutional neural network, artificial intelligence (AI) has made unprecedented breakthroughs in medical imaging, including the ongoing trials of computer-aided detection of colorectal polyps and gastrointestinal bleeding. In the past demi-decade, applications of AI systems in gastric cancer have also emerged. With AI’s efficient computational power and learning capacities, endoscopists can improve their diagnostic accuracies and avoid the missing or mischaracterization of gastric neoplastic changes. So far, several AI systems that incorporated both traditional and novel endoscopy technologies have been developed for various purposes, with most systems achieving an accuracy of more than 80%. However, their feasibility, effectiveness, and safety in clinical practice remain to be seen as there have been no clinical trials yet. Nonetheless, AI-assisted endoscopies shed light on more accurate and sensitive ways for early detection, treatment guidance and prognosis prediction of gastric lesions. This review summarizes the current status of various AI applications in gastric cancer and pinpoints directions for future research and clinical practice implementation from a clinical perspective.

Discrepancy between endoscopic and pathological ulcerative findings in clinical intramucosal early gastric cancer

BACKGROUND

Ulcerative finding (UL) is one of the factors that define the indication and curability of endoscopic resection (ER) in early gastric cancer (EGC). Discrepancies between endoscopic UL (cUL) and pathological UL (pUL) sometimes occur in clinical practice. The aim of this study was to investigate the discrepancy rate in UL diagnosis and the risk factors associated with such discrepancies.

METHODS

Patients with clinical intramucosal (cT1a) EGC who underwent ER or surgery between September 2002 and December 2017 were analyzed. The proportion of cUL-negative (cUL0) lesions that were identified as pUL-positive (pUL1) and that of cUL-positive (cUL1) lesions that were identified as pUL-negative (pUL0) were calculated. Logistic regression analysis was performed to estimate the associations between discrepancy in UL diagnosis and clinical variables of the lesion, such as the size, histology, location, and macroscopic type.

RESULTS

In total, 5382 lesions were evaluated; 5.5% of cUL0 lesions (256/4619) were identified as pUL1, while 38.7% of cUL1 lesions (295/763) were pUL0. Multivariate analysis indicated that in cUL1 lesions, tumor location in the lower third of the stomach (odds ratio 3.11, 95% confidence interval 1.90-5.08) was identified as an independent risk factor for overestimation.

CONCLUSIONS

Endoscopic diagnosis of UL in cT1a EGC was overestimated in 38.7% of lesions, especially for lesions located in the lower third of the stomach. This discrepancy should be considered in the management of cT1a EGC with UL.

Measurement of intragastric pressure: an objective method to ascertain whether gastric wall extension is sufficient for assessment of the non-extension sign

Background and study aims  The optimal intragastric pressure (IP) for strong gastric wall extension is unclear. We aimed to develop an accurate method to measure IP using endoscopy and determine the pressure required for strong gastric wall extension. Methods  An in vitro experiment using an endoscope with a rubber attached at its tip was conducted. The process of inserting the pressure measurement probe into the forceps channel was skipped, and the tube of the pressure measurement device was directly connected to the forceps channel. In vivo, the pressure in 51 consecutive patients at the time of strong gastric wall extension was measured. Strong extension of the gastric wall was defined as when the folds in the greater curvature were flattened as a result of sufficient extension of the gastric wall by insufflated air during upper gastrointestinal endoscopy. The IP at that time was measured. Results  In vitr o , 20 mL of tap water was injected once into the forceps channel and then aspirated for 10 seconds. Pressure measurement after irrigation of the forceps channel as well as the measurement by inserting the probe procedure were accurately performed. In vivo, among the 51 included patients, the mean IP (range) was 14.7 mmHg (10-23). Strong extension of the gastric wall was obtained in 96.1 % of patients when the IP was 20 mmHg. Conclusions  We developed an accurate method to measure IP using upper gastrointestinal endoscopy. Strong extension of the gastric wall was obtained in almost all patients when the IP was 20 mmHg.

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.

Mixed histology poses a greater risk for noncurative endoscopic resection in early gastric cancers regardless of the predominant histologic types

OBJECTIVES

Clinicopathologic characteristics and treatment outcomes of mixed-histological-type (MT) early gastric cancers (EGCs) treated with endoscopic submucosal dissection (ESD) have not been sufficiently elucidated. We aimed to clarify them in comparison with pure-histological-type EGCs.

METHODS

We used 3022 consecutive EGCs in 2281 patients treated with ESD from our prospectively maintained database. Cases were stratified into four groups according to the final diagnosis of the resected specimen are as follows: 2780 pure differentiated-type (DT), 127 DT-predominant MT (D-MT), 87 pure undifferentiated-type (UDT), and 28 UDT-predominant MT (U-MT). Clinicopathologic characteristics and treatment outcome were compared between pure DT and D-MT, and between pure UDT and U-MT separately. Risk factors for deep submucosal invasion, lymphovascular invasion, and a final diagnosis of MT were identified using multivariate analysis.

RESULTS

Both D-MT (41.7 vs. 92.0%; P < 0.0001) and U-MT (35.7 vs. 75.9%; P = 0.0002) showed a significantly lower curative resection rate than their pure histologic counterparts. Multivariate analysis revealed that MT was an independent risk factor for deep submucosal (OR 6.55; 95% CI, 4.18-10.14) and lymphovascular (OR 4.74; 95% CI, 2.72-8.29) invasion. Preoperative biopsy results that did not show well-differentiated tubular adenocarcinoma (OR 28.2; 95% CI, 18.9-42.9) were an independent risk factor for a final diagnosis of MT.

CONCLUSIONS

MT poses a greater risk for noncurative resection regardless of the predominant histologic types, reflecting more aggressive malignant potential. Although a biopsy examination rarely shows MT, clinicians should consider the possibility of MT when a biopsy examination does not show well-differentiated tubular adenocarcinoma.

Clinical significance of endoscopic ultrasonography in diagnosing invasion depth of early gastric cancer prior to endoscopic submucosal dissection

BACKGROUND AND AIM

Endoscopic ultrasonography is a reliable diagnostic modality for determining indications of endoscopic submucosal dissection for early gastric cancer. We aimed to clarify the clinical significance of endoscopic ultrasonography in the invasion depth diagnosis of early gastric cancer.

METHODS

We retrospectively assessed 1598 consecutive patients with 2001 early gastric cancers who underwent EUS before ESD or surgery between October 2010 and April 2019 at our institution. Lesions were classified according to endoscopic ultrasonography-determined invasion depth as EUS-M/SM1 (lesions confined to sonographic layers 1 and 2 or lesions with changes in sonographic layer 3; depth, < 1 mm) and EUS-SM2 (lesions with changes in sonographic layer 3; depth, ≥ 1 mm). We evaluated the invasion depth determination accuracy of endoscopic ultrasonography and analyzed the clinicopathological features of misdiagnosed early gastric cancer cases.

RESULTS

The invasion depth determination accuracy was as follows: EUS-M/SM1: pathological T1a/T1b1 early gastric cancer, 97%; EUS-SM2: pathological T1b2 early gastric cancer, 79%. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 95%, 98%, 69%, 97%, and 79%, respectively. In EUS-M/SM1 early gastric cancer, tumor size of ≥ 15 mm, presence of ulceration, and undifferentiated histological type were significantly associated with endoscopic ultrasonography accuracy. In EUS-SM2 early gastric cancer, tumor size of ≥ 30 mm was significantly associated with endoscopic ultrasonography accuracy.

CONCLUSIONS

Endoscopic ultrasonography is a useful modality in accurately determining the invasion depth of early gastric cancer before endoscopic submucosal dissection.

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.

Highly accurate artificial intelligence systems to predict the invasion depth of gastric cancer: efficacy of conventional white-light imaging, nonmagnifying narrow-band imaging, and indigo-carmine dye contrast imaging

BACKGROUND AND AIMS

Diagnosing the invasion depth of gastric cancer (GC) is necessary to determine the optimal method of treatment. Although the efficacy of evaluating macroscopic features and EUS has been reported, there is a need for more accurate and objective methods. The primary aim of this study was to test the efficacy of novel artificial intelligence (AI) systems in predicting the invasion depth of GC.

METHODS

A total of 16,557 images from 1084 cases of GC for which endoscopic resection or surgery was performed between January 2013 and June 2019 were extracted. Cases were randomly assigned to training and test datasets at a ratio of 4:1. Through transfer learning leveraging a convolutional neural network architecture, ResNet50, 3 independent AI systems were developed. Each system was trained to predict the invasion depth of GC using conventional white-light imaging (WLI), nonmagnifying narrow-band imaging (NBI), and indigo-carmine dye contrast imaging (Indigo).

RESULTS

The area under the curve of the WLI AI system was .9590. The lesion-based sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the WLI AI system were 84.4%, 99.4%, 94.5%, 98.5%, and 92.9%, respectively. The lesion-based accuracies of the WLI, NBI, and Indigo AI systems were 94.5%, 94.3%, and 95.5%, respectively, with no significant difference.

CONCLUSIONS

These new AI systems trained with multiple images from different angles and distances could predict the invasion depth of GC with high accuracy. The lesion-based accuracy of the WLI, NBI, and Indigo AI systems was not significantly different.

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.

Early gastric cancer involving a pure enteroblastic differentiation component that was curatively resected via endoscopic submucosal dissection

Gastric adenocarcinoma with enteroblastic differentiation (GAED) is a very rare variant of alpha-fetoprotein-producing gastric cancer (AFPGC). GAED is histologically characterized by cuboidal or columnar cells, which resemble those found in the primitive gut and have clear cytoplasm. In previously reported cases, GAED exhibit more aggressive behavior, as well as AFPGC, than conventional gastric cancer, such as marked lymphovascular invasion, lymph node metastasis, and liver metastasis. And also GAED was usually located in a deep mucosal layer and was covered by a conventional adenocarcinoma (CA) component. Based on these findings, GAED is considered to develop from CA during the process of tumor invasion and proliferation. We present a very rare case of early-stage GAED achieved curatively resected via endoscopic submucosal dissection, in which the lesion was composed of a pure enteroblastic differentiation component without a CA component.

Gastric endoscopic submucosal dissection: a systematic review and meta-analysis on risk factors for poor short-term outcomes

OBJECTIVE

Endoscopic submucosal dissection (ESD) is now established as the first option to manage early gastric neoplasms, but its efficacy may vary according to diverse factors. We aimed to systematically identify risk factors for poor short-term outcomes of gastric ESD with the purpose to improve patients' selection and management.

METHODS

Three online databases (MEDLINE, ISI Web of Knowledge and Scopus) were searched (last search on June 2018) for poor outcomes of gastric ESD (deep submucosal invasion, piecemeal/incomplete resection, noncurative resection and local recurrence).

RESULTS

One hundred five studies were included referring to 52.126 ESDs. Undifferentiated histology and upper location (vs lower) were associated with submucosal invasion [odds ratio (OR) = 2.42 [95% confidence interval (CI), 1.62-3.61] and OR = 3.20 (1.04-9.86), respectively] and deep submucosal invasion [OR = 2.98 (2.02-4.39) and OR = 2.35 (1.45-3.81), respectively]. Lesion size greater than 30 mm and ulceration were associated with piecemeal resection [OR = 2.78 (1.17-6.60) and OR = 2.76 (1.23, 6.20), respectively]. Lesion size greater than 30 mm, ulceration, upper location and fibrosis were risk factors for incomplete resection [OR = 3.83 (2.68-5.49), OR = 4.06 (1.62-10.16), OR = 3.71 (2.49-5.54) and OR = 4.46 (1.66-11.96), respectively]. A noncurative resection was more often observed for lesions located in the upper third of the stomach [OR = 1.49 (1.24-1.79)], depressed morphology [OR = 1.49 (1.04-2.12)] and those outside standard criteria [OR = 3.56 (2.31-5.48)]. Older age was significantly linked with local recurrence rates [OR = 3.08 (1.13-5.02)].

CONCLUSION

Several risk factors influence poor efficacy short-term outcomes of gastric ESD that may be used to inform both patients and health providers about the expected efficacy.

Self-study of the non-extension sign in an e-learning program improves diagnostic accuracy of invasion depth of early gastric cancer

Background and study aims  We developed an e-learning program for endoscopic diagnosis of invasion depth of early gastric cancer (EGC) using a simple diagnostic criterion called non-extension sign, and the contribution of self-study quizzes to improvement of diagnostic accuracy was evaluated. Methods  We conducted a prospective randomized controlled study that recruited endoscopists throughout Japan. After completing a pretest, the participants watched video lectures and undertook post-test 1. The participants were then randomly allocated to either the self-study or non-self-study group, and participants in the first group completed the self-study program that comprised 100-case quizzes. Finally, participants in both groups undertook post-test 2. The primary endpoint was the difference in post-test 2 scores between the groups. The perfect score for the tests was set as 100 points. Results  A total of 423 endoscopists completed the pretest and were enrolled. Post-test 1 was completed by 415 endoscopists and 208 were allocated to the self-study group and 207 to the non-self-study group. Two hundred and four in the self-study group and 205 in the non-self-study group were included in the analysis. Video lectures improved the mean score of post-test 1 from 72 to 77 points. Participants who completed the self-study quizzes showed significantly better post-test 2 scores compared with the non-self-study group (80 vs. 76 points, respectively, P  < 0.0001). Conclusions  Our e-learning program showed that self-study quizzes consolidated knowledge of the non-extension sign and improved diagnostic ability of endoscopists for invasion depth of EGC.

Endoscopic diagnosis and treatment of esophageal adenocarcinoma: introduction of Japan Esophageal Society classification of Barrett's esophagus

Endoscopic surveillance of Barrett's esophagus has become a foundation of the management of esophageal adenocarcinoma (EAC). Surveillance for Barrett's esophagus commonly involves periodic upper endoscopy with biopsies of suspicious areas and random four-quadrant biopsies. However, targeted biopsies using narrow-band imaging can detect more dysplastic areas and thus reduce the number of biopsies required. Several specific mucosal and vascular patterns characteristic of Barrett's esophagus have been described, but the proposed criteria are complex and diverse. Simpler classifications have recently been developed focusing on the differentiation between dysplasia and non-dysplasia. These include the Japan Esophageal Society classification, which defines regular and irregular patterns in terms of mucosal and vascular shapes. Cancer invasion depth is diagnosed by endoscopic ultrasonography (EUS); however, a meta-analysis of EUS staging of superficial EAC showed favorable pooled values for mucosal cancer staging, but unsatisfactory diagnostic results for EAC at the esophagogastric junction. Endoscopic resection has recently been suggested as a more accurate staging modality for superficial gastrointestinal cancers than EUS. Following endoscopic resection for gastrointestinal cancers, the risk of metastasis can be evaluated based on the histology of the resected specimen. European guidelines describe endoscopic resection as curative for well- or moderately differentiated mucosal cancers without lymphovascular invasion, and these criteria might be extended to lesions invading the submucosa (≤ 500 μm), i.e., to low-risk, well- or moderately differentiated tumors without lymphovascular involvement, and < 3 cm. These criteria were confirmed by a recent study in Japan.

Morphologic pattern analysis of submucosal deformities identified by endoscopic ultrasonography for predicting the depth of invasion in early gastric cancer

BACKGROUND

The aims of this study are to evaluate the usefulness of submucosal deformity pattern analysis with endoscopic ultrasonography (EUS) for predicting the depth of invasion in early gastric cancer (EGC) and the treatment results of endoscopic submucosal dissection (ESD).

METHODS

The endoscopic and EUS parameters of 345 patients with endoscopically suspected EGC who underwent endoscopic or surgical resection between July 2012 and May 2017 were retrospectively reviewed. All patients were classified into three categories as follows according to the morphologic type of submucosal deformity identified by EUS: (1) no submucosal deformity, (2) wedge-shaped deformity, and (3) arch-shaped deformity. The presence of an arch-shaped submucosal deformity on EUS and an active endoscopic ulcer or surrounding mucosal fold convergence/clubbing on conventional endoscopy were defined as suggestive of deep submucosal cancer invasion (SCI).

RESULTS

Upper location (p = 0.034) and the presence of an arch-shaped submucosal deformity on EUS (p < 0.001) were significant predictors of deep submucosal invasion, with the presence of an arch-shaped submucosal deformity showing the highest predictive value (odds ratio of 26.27). The overall diagnostic accuracy of EUS for predicting deep SCI was 83.5%, with a sensitivity of 84.0% and a specificity of 83.3%, which were significantly higher than those of conventional endoscopy. A larger lesion size and the presence of an arch-shaped submucosal deformity were significant factors associated with noncurative resection after ESD.

CONCLUSIONS

Submucosal deformity pattern analysis with EUS can provide more accurate information than conventional endoscopy for predicting deep SCI. The presence of an arch-shaped submucosal deformity on EUS was an effective predictor of deep SCI and noncurative resection.

Clinical predictors of histologic type of gastric cancer

BACKGROUND AND AIMS

Gastric cancer is classified into differentiated and undifferentiated types according to the degree of glandular differentiation. Undifferentiated-type early gastric cancer (EGC) carries a higher risk of lymph-node metastasis than differentiated type, and therefore the indication criteria for endoscopic resection differ. This study aimed to clarify the ability of clinical predictors to distinguish between differentiated-type and undifferentiated-type EGCs.

METHODS

This was a post hoc study of a multicenter prospective trial carried out in 5 Japanese hospitals, including 343 patients with cT1 EGC of ≥10 mm. According to the protocol, age, sex, and endoscopic findings of cancer (diameter, location, macroscopic type, and invasion depth) were evaluated, and the final diagnosis was confirmed from resected specimens. We evaluated the associations between these clinical factors and the histologic type of cancer and calculated the ability of the factors to diagnose differentiated-type EGC. The diagnostic ability of forceps biopsy was also calculated as a reference.

RESULTS

Multivariate analysis identified older age (≥72 years), male sex, larger tumor size (>30 mm), elevated type, and shallower invasion depth (cT1a) as independent significant predictors for differentiated-type EGC, with elevated type showing the highest positive likelihood ratio. The sensitivity, specificity, accuracy, and positive and negative likelihood ratios of elevated type for differentiated-type EGC were 24%, 99%, 38%, 15.7, and 0.77, respectively, compared with 96%, 86%, 95%, 7.0, and 0.04 for forceps biopsy.

CONCLUSIONS

Endoscopic elevated type is a significant predictor for differentiated-type EGC and may exclude undifferentiated-type EGC without the need for forceps biopsy.

Validity of conventional endoscopy using "non-extension sign" for optical diagnosis of colorectal deep submucosal invasive cancer

BACKGROUND AND STUDY AIMS

 The non-extension sign relates to a localized increase in thickness and rigidity due to deep submucosal invasive (SM-d: depth of 1000 μm or more) cancer. The present study aimed to evaluate the efficacy of the non-extension sign in assessing the optical diagnosis of colorectal SM-d cancer.

PATIENTS AND METHODS

 We retrospectively analyzed 309 patients with 315 early colorectal cancers that had been endoscopically or surgically resected. The non-extension sign was judged from chromoendoscopy (CE) using conventional white-light imaging with indigo carmine, and is taken to be positive when any one of the findings of rigidity of a circular arc, trapezoid elevation, or converging mucosal folds are seen. We assessed comparing the accuracy of CE, magnifying chromoendoscopy (M-CE), and magnifying narrow-band imaging (M-NBI) for the optical diagnosis of colorectal SM-d cancer.

RESULTS

Sensitivity, specificity, and accuracy for the diagnosis of SM-d cancer were 66.0 %, 95.8 %, and 86.3 % for CE; 80 %, 90.7 %, and 87.3 % for M-CE; and 65.0 %, 94.4 %, and 85.1 % for M-NBI, respectively. The specificity of CE was significantly higher than that of M-CE ( P  = 0.034). The sensitivity of M-CE was significantly higher than that of CE ( P  = 0.026). In a comparison of positive and negative groups for the non-extension sign in SM-d cancer, SM invasion was significantly deeper in the positive group than in the negative group (3012.5 μm vs 2002.4 μm, respectively; P  < 0.0001) and the rate of lymphovascular invasion was significantly higher in the positive group than in the negative group (63.6 % vs 41.2 %, respectively; P  = 0.032).

CONCLUSIONS

 The non-extension sign offers high diagnostic specificity for SM-d cancer, and surgery should be considered in patients with a positive non-extension sign.

Polish Consensus on Treatment of Gastric Cancer; update 2017

The "Polish Research on Gastric Cancer" project has been continued since 1986. The main aim of this project, which is a multicenter and interdisciplinary research, is enhancing the treatment results of gastric cancer patients by developing and promoting the use of optimal methods for diagnosis and treatment, both surgical as well as combined. One of the more important achievements of the project is the development and publication of a document named "Polish Consensus on Treatment of Patients with Gastric Cancer", whose first version was published in 1998. Following versions were updated adequately to changing trends in the proceedings in patients with gastric cancer. A scientific symposium on "Polish Consensus on Treatment of Gastric Cancer - update 2016" was held in 3-4 June 2016 in Cracow. During the symposium a panel session was held during which all authors publicly presented the Consensus assumptions to be discussed further. Moreover, the already mentioned session was preceded by a correspondence as well as a working meeting in order to consolidate the position. It has to be underlined that the directions and guidelines included in the Consensus are not the arbitrarily assumed rules of conduct in a legal aspect and as such every doctor/team of doctors is entitled to make different decisions as long as they are beneficial to a patient with gastric cancer. The Consensus discusses as follows: a) recommended qualifications (stage of advancement, pathological, lymph node topography and the extent of lymphadenectomy, division of cancer of the gastroesophageal junction), b) rules for diagnostics including recommendations regarding endoscopic examination and clinical evaluation of the advancement stage, c) recommendations regarding surgical treatment (extent of resection, extent of lymphadenectomy, tactics of proceedings in cancer of the gastroesophageal junction), d) recommendations regarding combined treatment with chemotherapy or radiotherapy, e) place of endoscopic and less invasive surgery in the treatment of gastric cancer. This publication is a summary of the arrangements made in the panel session during the abovementioned scientific symposium in Cracow in 2016.

Gastric ESD may be useful as accurate staging and decision of future therapeutic strategy

Background and study aims We sometimes perform gastric endoscopic submucosal dissection (ESD) for total pathologic diagnosis when preoperative diagnosis is difficult. In the present study we analyzed the treatment outcomes and adverse events of diagnostic ESD for early gastric cancer (EGC). Patients and methods We conducted a retrospective analysis of 18 consecutive cases of EGC in 18 patients with a suspected out-of-indication diagnosis who underwent diagnostic ESD, between June 2010 and November 2014. The following parameters were examined: the average length of the longer axis of the lesion; the procedure time; the rates of en bloc resection (ER), complete en bloc resection (CER), and curative resection (CR) as treatment outcomes; and the rates of perforation, delayed bleeding, aspiration pneumonia, disease-related death, and emergency surgery as adverse events. Results The treatment outcomes were as follows: average length of the longer axis of the lesion, 27.4 ± 10.0 mm; procedure time, 87.0 ± 43.1 minutes; ER rate, 18/18 (100.0 %); CER rate, 13/18 (72.2 %); CR rate, 4/18 (22.2 %). CR rate was achieved 37.5 % for the lesions which preoperative diagnosis was more than 30 mm (> 30 mm) in diameter differentiated type with mucosal layer/submucosal layer 1 invasion and ulceration positive. The adverse events (AEs) were perforation in 1 of 18 (5.5 %) patients and delayed bleeding in 1 of 18 (5.5 %). There were no other AEs. Conclusions Diagnostic ESD may be acceptable for future therapeutic strategy when we unconfirmed the pre ESD diagnosis because of lower rate of adverse events and high rate of ER.