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Most gastric neuroendocrine tumors (NETs) develop from enterochromaffin-like (ECL) cells. ECL-cell NETs are classically categorized into three types according to their etiology. A 50-year-old woman presented with submucosal tumor-like lesions in the stomach, which were identified via esophagogastroduodenoscopy. Although esophagogastroduodenoscopy and pathological findings of biopsy specimens showed an absence of mucosal atrophy in the body of the stomach, sticky, adherent, dense mucus was observed. All lesions were diagnosed as ECL-cell NETs based on histological examination findings; however, ECL-cell NETs did not apply to any of the classic types I-III categorization based on laboratory, computed tomography, and 24-h intragastric pH monitoring test findings. Endoscopic submucosal dissection of the tumor was performed. Pathological findings of the excised specimen indicated that parietal cell hyperplasia with a protrusion, dilated fundic glands, and endocrine cell hyperplasia in the background mucosa, and parietal cells were not immunostained for the α-subunits of H

The risk factors for lymph node metastasis (LNM) of duodenal neuroendocrine tumors (DNETs) are not well identified, and a definitive standard of treatment for DNETs has not been established. In this study, we aimed to identify the risk factors for LNM and establish the indication of local resection for DNETs.We retrospectively reviewed 55 patients with 60 non-ampullary and nonfunctional DNETs. We evaluated the risk factors for LNM and compared the outcomes between endoscopic resection (ER) for DNETs5 mm and laparoscopy and endoscopy cooperative surgery (LECS) for DNETs ≥5 mm.LNM was present in four (8.7%) patients. Univariate analysis revealed that tumor size ≥10 mm, positive lymphovascular invasion (LVI), and 0-Is morphology were significantly associated with LNM (Tumor size ≥10 mm, positive LVI, and 0-Is morphology were significant risk factors for LNM. We demonstrated that ER is feasible and could be safely applied for DNETs5 mm, and LECS could be applied for DNETs 5-10 mm in size.

Introduction: Although endocytoscopy (EC) with narrow-band imaging (NBI) is effective in diagnosing gastric cancer, no diagnostic system has been validated. We explored a specific diagnostic system for gastric cancer using EC with NBI. Methods: Equal numbers of images from cancerous and noncancerous areas (114 images each) were assessed by endoscopists with (development group: 33) and without (validation group: 28) specific training in magnifying endoscopy with NBI. Microvascular and microsurface patterns (MS) in each image were evaluated. Lesions were diagnosed as cancerous when patterns were deemed “irregular.” The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of a diagnosis according to patterns on EC with NBI (microvascular pattern [MV] alone, MS alone, and both) were evaluated and compared between groups to determine the diagnostic performance. Results: In the development and validation groups, diagnoses based on the MV alone had significantly higher accuracy (91.7% vs. 76.3%, p < 0.0001 and 92.5% vs. 67.5%, p < 0.0001, respectively) and sensitivity (88.6% vs. 68.3%, p < 0.0001 and 89.5% vs. 38.6%, p < 0.0001, respectively) than those based on the MS alone. In both groups, there were no significant differences in diagnostic accuracy between using the MV alone and both patterns. Discussion/Conclusion: Evaluation of the MV alone is a simple and accurate diagnostic method for gastric cancer. This system could find widespread applications in clinical practice.

Background An association between specific endoscopic findings and high-grade dysplasia/carcinoma in superficial nonampullary duodenal epithelial tumors ≤ 5 mm in size has not been reported. We sought to identify the endoscopic findings associated with high-grade dysplasia/carcinoma in patients with superficial nonampullary duodenal epithelial tumors ≤ 5 mm. Methods We retrospectively assessed the data of 84 patients (88 lesions; low-grade dysplasia: n = 35, high-grade dysplasia/carcinoma: n = 53) with superficial nonampullary duodenal epithelial tumors who underwent initial treatment at a single center (from July 2009 to April 2021). All the patients had lesions sized ≤ 5 mm. We assumed that the endoscopic findings were independently associated with high-grade dysplasia/carcinoma and determined the accuracy, sensitivity, and specificity of a combination of independent factors for diagnosing high-grade dysplasia/carcinoma and low-grade dysplasia. Results Multivariate logistic regression of significant factors in the univariate analysis revealed that lesions with depressed morphology (odds ratio: 23.9, 95% confidence interval: 2.8-204.2; p = 0.0037) and a reddish color (odds ratio: 175.7, 95% confidence interval: 11.4-2697.1; p = 0.0002) were independently associated with high-grade dysplasia/carcinoma. McNemar's test revealed that combining the macroscopic type and color provided significantly higher sensitivity for diagnosing high-grade dysplasia/carcinoma than color alone (98.1%, 95% confidence interval: 90.1-99.7 vs. 71.7%, 95% confidence interval: 58.4-82.0; p = 0.0002). Conclusions Reddish and depressed-type lesions before treatment were associated with high-grade dysplasia/carcinoma. Combining the macroscopic type and color can help detect high-grade dysplasia/carcinoma. These findings could help clinicians determine the best therapeutic strategy for patients with smaller (≤ 5 mm) superficial nonampullary duodenal epithelial tumors in clinical settings.

OBJECTIVES Endoscopic resection (ER) is indicated for a wide range of superficial esophageal squamous cell carcinomas (ESCCs). We examined the long-term outcomes in patients with pathological (p) invasion of ESCC into the T1a-muscularis mucosae (MM) and T1b-submucosa (SM) after ER, for which data on prognosis are limited. METHODS Of the 1217 patients with superficial ESCC who underwent ER, 225 patients with a pathological diagnosis of ESCC invasion into the MM, minute submucosal invasion ≤200 µm (SM1), or massive submucosal invasion (SM2) were included. In patients with lymphovascular invasion, droplet infiltration, or SM2 invasion, additional treatments, including chemoradiation (CRT) or esophagectomy with two- to three-field lymph node dissection, were recommended. The median observation period was 66 months (interquartile range 48-91 months). RESULTS In total, there were 151, 28, and 46 pT1a-MM, pT1b-SM1, and pT1b-SM2 cases, respectively. Metastatic recurrence was observed in 1.3%, 10.7%, and 6.5% patients with pT1a-MM, pT1b-SM1, and pT1b-SM2 ESCCs, respectively. Of the eight patients with metastatic recurrence, six were successfully treated, and two died of ESCC. The 5-year overall survival rates were 84.1%, 71.4%, and 67.4%, the 5-year relapse-free survival rates were 82.8%, 64.3%, and 65.2%, and the 5-year disease-specific survival rates were 100%, 96.4%, and 99.1% in patients with pT1a-MM, pT1b-SM1, and pT1b-SM2 ESCCs, respectively. Multivariate analysis showed that additional CRT and esophagectomy, and T1b-SM2 were positively and negatively associated with overall survival, respectively. CONCLUSIONS Endoscopic resection preceding appropriate additional treatments resulted in favorable outcomes. Many cases of metastatic recurrence in this cohort could be successfully treated.

Aims To compare endoscopy gastric cancer images diagnosis rate between artificial intelligence (AI) and expert endoscopists. Patients and methods We used the retrospective data of 500 patients, including 100 with gastric cancer, matched 1:1 to diagnosis by AI or expert endoscopists. We retrospectively evaluated the noninferiority (prespecified margin 5 %) of the per-patient rate of gastric cancer diagnosis by AI and compared the per-image rate of gastric cancer diagnosis. Results Gastric cancer was diagnosed in 49 of 49 patients (100 %) in the AI group and 48 of 51 patients (94.12 %) in the expert endoscopist group (difference 5.88, 95 % confidence interval: −0.58 to 12.3). The per-image rate of gastric cancer diagnosis was higher in the AI group (99.87 %, 747 /748 images) than in the expert endoscopist group (88.17 %, 693 /786 images) (difference 11.7 %). Conclusions Noninferiority of the rate of gastric cancer diagnosis by AI was demonstrated but superiority was not demonstrated.

Radiation-induced hemorrhagic gastritis is a relatively uncommon complication of irradiation that can be severe. However, appropriate treatment guidelines have not yet been established because of the small number of known cases. At our hospital, we encountered nine cases of radiation-induced hemorrhagic gastritis between July 2005 and July 2018. All patients initially underwent argon plasma coagulation (APC) for hemostasis. The treatment was highly effective, and hemostasis was successfully achieved in eight of the cases. Hemostasis could not be achieved in one case treated with APC; therefore, surgical resection was required. This patient had risk factors, such as liver cirrhosis and a history of abdominal surgery. Our case series suggests that APC is an effective hemostatic method that should be considered as the initial treatment option for radiation-induced hemorrhagic gastritis; however, surgical resection may be considered when the patient is at high risk for rebleeding.

Whether antithrombotic drugs increase the risk of post-esophageal endoscopic resection bleeding is unknown. This study examined the effect of antithrombotic drugs, aspirin, thienopyridine, direct oral anticoagulants (DOAC), and warfarin, on post-esophageal endoscopic resection bleeding.We enrolled 957 patients (1202 esophageal tumors) treated with endoscopic resection and classified them based on antithrombotic drug use as no use, aspirin, thienopyridine, DOAC, and warfarin. Patients using antiplatelet drugs (i.e. aspirin and thienopyridine) were further sub-classified based on their continued or discontinued use before endoscopic resection. The bleeding rates were compared between these groups to assess the effects of antithrombotic drug use and interruption of antiplatelet therapy on post-esophageal endoscopic resection bleeding.The post-endoscopic resection bleeding rate was 0.3% (95% CI, 0.1-1) in the group without antithrombotic drug use, 4.5% (95% CI, 0.1-23) in the aspirin-continued group, 2.9% (95% CI, 0.1-15) in the aspirin-discontinued group, 0% (95% CI, 0-78) in the replaced thienopyridine with aspirin group, 0% (95% CI, 0-26) in the thienopyridine-discontinued group, 13% (95% CI, 1.6-38) in the DOAC group, and 0% (95% CI, 0-45) in the warfarin group. The post-endoscopic resection bleeding rate in the DOAC group was significantly higher than that in the group without antithrombotic drugs (P = 0.003). The post-endoscopic resection bleeding rates did not differ between the other groups.Our results suggest that discontinuing aspirin is not necessary for esophageal endoscopic resection while we must be careful regarding DOAC.

Background and Aim Helicobacter pylori antibody levels in the blood are currently measured using an ELISA. In April 2016, FUJIFILM Wako Pure Chemical Corporation launched the “l‐type Wako Helicobacter pylori antibody J" test, which is based on the latex agglutination turbidimetric immunoassay. In this study, we investigated the usefulness of the Wako test. Methods We measured H. pylori antibody levels using both the ELISA and Wako test in 180 patients who underwent upper gastrointestinal endoscopy at our hospital between September 2017 and February 2019. Ninety patients were infected with H. pylori. We calculated the diagnostic accuracy, sensitivity, and specificity of each test and the concordance rate between the ELISA and Wako test. If lower limits of 90% confidence intervals (CIs) for each diagnostic validity exceeded the 85% threshold, the usefulness of the diagnostic test was confirmed. Results The diagnostic accuracy, sensitivity, and specificity were 94.4% (90% CI, 90.8–97.0%), 94.4% (90% CI, 88.7–97.8%), and 94.4% (90% CI, 88.7–97.8%), respectively, when the Wako test was used, and 94.4% (90% CI, 90.8–97.0%), 88.9% (90% CI, 81.9–93.8%), and 100% (90% CI, 96.0–100%), respectively, when the ELISA was used. The concordance rate between the two tests was high (κ = 0.8444). Conclusions We confirmed the usefulness of the Wako test, especially when screening for H. pylori infection, due to its high sensitivity., “l‐type Wako Helicobacter pylori antibody J” test is based on the latex agglutination turbidimetric immunoassay. Many samples can be analyzed simultaneously, rapidly, and more economically using this kit. l‐HP J test showed a high diagnosis performance, and is not inferior to ELISA. The l‐HP J test is useful, especially when screening for Helicobacter pylori infection, due to its high sensitivity.

Background and Aim l‐Menthol has smooth muscle‐relaxing and antiperistaltic effects. We examined its effectiveness against peristalsis resumption during endoscopic submucosal dissection (ESD) of gastric tumors. Methods We retrospectively examined clinical data of 485 patients (501 lesions) who underwent ESD for upper gastrointestinal tumors in 2017. We included 119 patients (127 lesions) in whom peristaltic movement resumed during ESD and l‐menthol was applied; 366 patients (374 lesions) without l‐menthol application were used as controls. Video recordings were reviewed to determine whether l‐menthol suppressed peristalsis resumption. Results In cases with l‐menthol application, 2 (2.9%), 36 (14.3%), and 89 (71.2%) lesions were found in the upper (U), middle (M), and lower (L) regions, respectively. In the control group, the corresponding values were 66 (17.6%), 215 (57.5%), and 93 (24.9%), respectively. l‐Menthol efficacy was observed in 116 of the 127 treated lesions (91.3%), over 90% of which were in the posterior wall of the U region, anterior wall and greater curvature of the M region, and anterior wall and lesser curvature of the L region. The most and least effective areas for l‐menthol application were the anterior wall of gastric antrum and posterior wall of the M region, respectively. The mean time from application to peristalsis inhibition was 8.7 s. No adverse effects were observed; perforation and secondary hemorrhage were not significantly different between the groups. Conclusion Direct l‐menthol application to the submucosal layer during mucosal resection affects smooth muscles and rapidly inhibits peristalsis resumption. Clinically, l‐Menthol can be used to suppress peristalsis recurrence during ESD, without adverse effects., Direct l‐menthol application to the submucosal layer during mucosal resection. When peristaltic resumption was seen, we sprayed l‐menthol on submucosal layer directly. Peristalsis stopped rapidly (8.7 seconds). l‐menthol was effective in 91.5% cases.

Diagnosis using artificial intelligence (AI) with deep learning could be useful in endoscopic examinations. We investigated the ability of AI to detect superficial esophageal squamous cell carcinoma (ESCC) from esophagogastroduodenoscopy (EGD) videos. We retrospectively collected 8428 EGD images of esophageal cancer to develop a convolutional neural network through deep learning. We evaluated the detection accuracy of the AI diagnosing system compared with that of 18 endoscopists. We used 144 EGD videos for the two validation sets. First, we used 64 EGD observation videos of ESCCs using both white light imaging (WLI) and narrow-band imaging (NBI). We then evaluated the system using 80 EGD videos from 40 patients (20 with superficial ESCC and 20 with non-ESCC). In the first set, the AI system correctly diagnosed 100% ESCCs. In the second set, it correctly detected 85% (17/20) ESCCs. Of these, 75% (15/20) and 55% (11/22) were detected by WLI and NBI, respectively, and the positive predictive value was 36.7%. The endoscopists correctly detected 45% (25–70%) ESCCs. With AI real-time assistance, the sensitivities of the endoscopists were significantly improved without AI assistance (p

Introduction: Curative rates of endoscopic treatment for undifferentiated-type early gastric cancer (EGC), particularly mixed poorly differentiated adenocarcinoma (MIXED-POR), are lower than those of endoscopic treatment for the differentiated type. Magnifying endoscopy with narrow-band imaging (ME-NBI) is useful for diagnoses of the histological type. This study aimed to investigate the detection rates of MIXED-POR among undifferentiated-type EGCs using biopsy and ME-NBI in order to improve curative rates through endoscopic treatment. Methods: We analyzed 267 lesions initially subjected to endoscopic submucosal resection (ESD) and histologically diagnosed as undifferentiated-type EGCs between July 2005 and December 2016 at our hospital. We obtained written informed consent from all participants. Biopsy and ME-NBI findings were compared to distinguish pure signet ring cell carcinoma (PURE-SIG) and MIXED-POR. ME-NBI findings were divided into 2 categories depending on the presence of irregular vessels. Results of biopsy and ME-NBI (combination method) were also analyzed, and detection rates of MIXED-POR and PURE-SIG were evaluated in terms of sensitivity, specificity, and accuracy. Results: Overall, 114 lesions were analyzed. Fifty-eight lesions (50.9%) were identified as MIXED-POR. With biopsy, the detection rate of MIXED-POR was significantly lower than that of PURE-SIG (p < 0.0001). ME-NBI detected significantly more MIXED-POR with irregular vessels than PURE-SIG (p < 0.0001). The combination method could detect significantly more MIXED-POR than PURE-SIG (p < 0.0001). The sensitivity and accuracy for MIXED-POR diagnosis were significantly higher with the combination method than with biopsy alone (p < 0.0001). Discussion/Conclusion: Combining biopsy and ME-NBI improved the accuracy of pretreatment diagnosis before ESD in undifferentiated-type cancer.

Image recognition using artificial intelligence (AI) has progressed significantly due to innovative technologies such as machine learning and deep learning. In the field of gastric cancer (GC) management, research on AI-based diagnosis such as anatomical classification of endoscopic images, diagnosis of Helicobacter pylori infection, and detection and qualitative diagnosis of GC is being conducted, and an accuracy equivalent to that of physicians has been reported. It is expected that AI will soon be introduced in the field of endoscopic diagnosis and management of gastric cancer as a supportive tool for physicians, thus improving the quality of medical care.

We aimed to clarify the long-term outcomes of endoscopic resection (ER) for early gastric cancers (EGCs) based on pathological curability in a multicenter prospective cohort study.We analyzed the long-term outcomes of 9054 patients with 10,021 EGCs undergoing ER between July 2010 and June 2012. Primary endpoint was the 5-year overall survival (OS). The hazard ratio for all-cause mortality was calculated using the Cox proportional hazards model. We also compared the 5-year OS with the expected one calculated for the surgically resected patients with EGC. If the lower limit of the 95% confidence interval (CI) of the 5-year OS exceeded the expected 5-year OS minus a margin of 5% (threshold 5-year OS), ER was considered to be effective. Pathological curability was categorized into en bloc resection, negative margins, and negative lymphovascular invasion: differentiated-type, pT1a, ulcer negative, ≤2 cm (Category A1); differentiated-type, pT1a, ulcer negative,2 cm or ulcer positive, ≤3 cm (Category A2); undifferentiated-type, pT1a, ulcer negative, ≤2 cm (Category A3); differentiated-type, pT1b (SM1), ≤3 cm (Category B); or noncurative resections (Category C).Overall, the 5-year OS was 89.0% (95% CI, 88.3%-89.6%). In a multivariate analysis, no significant differences were observed when the hazard ratio of Categories A2, A3, and B were compared with that of A1. In all the pathological curability categories, the lower limit of the 95% CI for the 5-year OS exceeded the threshold 5-year OS.ER can be recommended as a standard treatment for patients with EGCs fulfilling Category A2, A3, and B, as well as A1 (UMIN Clinical Trial Registry, UMIN000005871).

Endoscopists' abilities to diagnose early gastric cancers (EGCs) vary, especially between specialists and nonspecialists. We developed an artificial intelligence (AI)-based diagnostic support tool "Tango" to differentiate EGCs and compared its performance with that of endoscopists.The diagnostic performances of Tango and endoscopists (34 specialists, 42 nonspecialists) were compared using still images of 150 neoplastic and 165 non-neoplastic lesions. Neoplastic lesions included EGCs and adenomas. The primary outcome was to show the noninferiority of Tango (based on sensitivity) over specialists. The secondary outcomes were the noninferiority of Tango (based on accuracy) over specialists and the superiority of Tango (based on sensitivity and accuracy) over nonspecialists. The lower limit of the 95% confidence interval (CI) of the difference between Tango and the specialists for sensitivity was calculated, with-10% defined as noninferiority and0% defined as superiority in the primary outcome. The comparable differences between Tango and the endoscopists for each performance were calculated, with10% defined as superiority and0% defined as noninferiority in the secondary outcomes.Tango achieved superiority over the specialists based on sensitivity (84.7% vs. 65.8%, difference 18.9%, 95% CI 12.3-25.3%) and demonstrated noninferiority based on accuracy (70.8% vs. 67.4%). Tango achieved superiority over the nonspecialists based on sensitivity (84.7% vs. 51.0%) and accuracy (70.8% vs. 58.4%).The AI-based diagnostic support tool for EGCs demonstrated a robust performance and may be useful to reduce misdiagnosis.

Background No studies have compared the performance of microvascular and microsurface patterns alone with their combination in patients undergoing magnifying endoscopy with narrow-band imaging for diagnosing gastric cancer. This study aimed to clarify the differences in diagnostic performance among these methods. Methods Thirty-three participating endoscopists who had received specialized training in magnifying endoscopy evaluated the microvascular and microsurface patterns of images of 106 cancerous and 106 non-cancerous lesions. If classified as “irregular,” the lesion was diagnosed as gastric cancer. To evaluate diagnostic performance, we compared the diagnostic accuracy, sensitivity, and specificity of these methods. Results Performance-related items did not differ significantly between microvascular and microsurface patterns. However, the diagnostic accuracy and sensitivity were significantly higher when using a combination of these methods than when using microvascular (82.1% [76.4–86.7] vs. 76.4% [70.3–81.6] and 69.8% [60.5–77.8] vs. 63.2% [53.7–71.8]; P P = 0.008, respectively) or microsurface (82.1% [76.4–86.7] vs. 73.6% [67.3–79.1] and 69.8% [60.5–77.8] vs. 52.8% [43.4‒62.1]; both, P Conclusions We demonstrate the superiority of the combination of microvascular and microsurface patterns over microvascular or microsurface patterns alone for diagnosing gastric cancer. Our data support the use of the former method in clinical practice. Although a major limitation of this study was its retrospective, single-center design, our findings may help to improve the diagnosis of 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.

Artificial intelligence (AI) that surpasses human ability in image recognition is expected to be applied in the field of gastrointestinal endoscopes. Accordingly, its research and development (RD) is being actively conducted. With the development of endoscopic diagnosis, there is a shortage of specialists who can perform high-precision endoscopy. We will examine whether AI with excellent image recognition ability can overcome this problem.Since 2016, papers on artificial intelligence using convolutional neural network (CNN in other word Deep Learning) have been published. CNN is generally capable of more accurate detection and classification than conventional machine learning. This is a review of papers using CNN in the gastrointestinal endoscopy area, along with the reasons why AI is required in clinical practice. We divided this review into four parts: stomach, esophagus, large intestine, and capsule endoscope (small intestine).Potential applications for the AI include colorectal polyp detection and differentiation, gastric and esophageal cancer detection, and lesion detection in capsule endoscopy. The accuracy of endoscopic diagnosis will increase if the AI and endoscopist perform the endoscopy together.

Management strategies for primary non-ampullary duodenal adenocarcinoma (NADAC) in early stage are not well established given its low incidence. This study aimed to elucidate clinicopathological features of early NADAC, including risk for lymph nodal metastasis (LNM). In total, 166 patients with early NADAC underwent initial treatment at our institution between 2006 and 2019, of whom 153 had intramucosal (M-) and 13 had submucosal (SM-) NADAC. These endoscopic and pathological features were retrospectively analyzed. Risk factors for LNM were evaluated in 46 early NADAC patients who underwent surgery with lymph node dissection. Compared with M-NADAC, SM-NADAC was significantly more frequently located at the proximal side of the papilla, with mixed elevated and depressed macroscopic type, histologically poorly differentiated tumor and lymphovascular invasion (LVI) (85% vs. 47%, P = 0.009; 54% vs. 5%, P

Background We previously reported for the first time the usefulness of artificial intelligence (AI) systems in detecting gastric cancers. However, the “original convolutional neural network (O-CNN)” employed in the previous study had a relatively low positive predictive value (PPV). Therefore, we aimed to develop an advanced AI-based diagnostic system and evaluate its applicability for the classification of gastric cancers and gastric ulcers. Methods We constructed an “advanced CNN” (A-CNN) by adding a new training dataset (4453 gastric ulcer images from 1172 lesions) to the O-CNN, which had been trained using 13 584 gastric cancer and 373 gastric ulcer images. The diagnostic performance of the A-CNN in terms of classifying gastric cancers and ulcers was retrospectively evaluated using an independent validation dataset (739 images from 100 early gastric cancers and 720 images from 120 gastric ulcers) and compared with that of the O-CNN by estimating the overall classification accuracy. Results The sensitivity, specificity, and PPV of the A-CNN in classifying gastric cancer at the lesion level were 99.0 % (95 % confidence interval [CI] 94.6 %−100 %), 93.3 % (95 %CI 87.3 %−97.1 %), and 92.5 % (95 %CI 85.8 %−96.7 %), respectively, and for classifying gastric ulcers were 93.3 % (95 %CI 87.3 %−97.1 %), 99.0 % (95 %CI 94.6 %−100 %), and 99.1 % (95 %CI 95.2 %−100 %), respectively. At the lesion level, the overall accuracies of the O- and A-CNN for classifying gastric cancers and gastric ulcers were 45.9 % (gastric cancers 100 %, gastric ulcers 0.8 %) and 95.9 % (gastric cancers 99.0 %, gastric ulcers 93.3 %), respectively. Conclusion The newly developed AI-based diagnostic system can effectively classify gastric cancers and gastric ulcers.

Objectives Detecting early gastric cancer is difficult, and it may even be overlooked by experienced endoscopists. Recently, artificial intelligence based on deep learning through convolutional neural networks (CNNs) has enabled significant advancements in the field of gastroenterology. However, it remains unclear whether a CNN can outperform endoscopists. In this study, we evaluated whether the performance of a CNN in detecting early gastric cancer is better than that of endoscopists. Methods The CNN was constructed using 13,584 endoscopic images from 2639 lesions of gastric cancer. Subsequently, its diagnostic ability was compared to that of 67 endoscopists using an independent test dataset (2940 images from 140 cases). Results The average diagnostic time for analyzing 2940 test endoscopic images by the CNN and endoscopists were 45.5 ± 1.8 s and 173.0 ± 66.0 min, respectively. The sensitivity, specificity, and positive and negative predictive values for the CNN were 58.4%, 87.3%, 26.0%, and 96.5%, respectively. These values for the 67 endoscopists were 31.9%, 97.2%, 46.2%, and 94.9%, respectively. The CNN had a significantly higher sensitivity than the endoscopists (by 26.5%; 95% confidence interval, 14.9-32.5%). Conclusion The CNN detected more early gastric cancer cases in a shorter time than the endoscopists. The CNN needs further training to achieve higher diagnostic accuracy. However, a diagnostic support tool for gastric cancer using a CNN will be realized in the near future.

With the application of artificial intelligence (AI) in deep learning, it has become possible to develop an AI that can be used clinically even in the field of upper endoscopy, which has been said to be difficult to diagnose. This review summarizes current studies on upper gastrointestinal tract based on AI and deep learning. At present, AI research on gastric cancer detection, Heliobactor pylori infection diagnosis, and esophagus cancer detection is progressing, and there is a possibility that AI can be used to assist in diagnosing invasion of depth of gastric caners and esophageal cancers. The studies reviewed show evidence that the use of AI in diagnosing cancer in the upper gastrointestinal tract as well as in the lower gastrointestinal tract, where research has been advanced, will be introduced to the clinical site in a form that contributes to detecting suspected cancer lesions, determining treatment policies, and improving examination accuracy.

Objectives The prognosis for pharyngeal cancer is relatively poor. It is usually diagnosed in an advanced stage. Although the recent development of narrow-band imaging (NBI) and increased awareness among endoscopists have enabled detection of superficial pharyngeal cancer, these techniques are still not prevalent worldwide. Nevertheless, artificial intelligence (AI)-based deep learning has led to significant advancements in various medical fields. Here, we demonstrate the diagnostic ability of AI-based detection of pharyngeal cancer from endoscopic images in esophagogastroduodenoscopy. Methods We retrospectively collected 5403 training images of pharyngeal cancer from 202 superficial cancers and 45 advanced cancers from the Cancer Institute Hospital, Tokyo, Japan. Using these images, we developed an AI-based diagnostic system with convolutional neural networks. We prepared 1912 validation images from 35 patients with 40 pharyngeal cancers and 40 patients without pharyngeal cancer to evaluate our system. Results Our AI-based diagnostic system correctly detected all pharyngeal cancer lesions (40/40) in the patients with cancer, including three small lesions smaller than 10 mm. For each image, the AI-based system correctly detected pharyngeal cancers in images obtained via NBI with a sensitivity of 85.6%, much higher sensitivity than that for images obtained via white light imaging (70.1%). The novel diagnostic system took only 28 s to analyze 1912 validation images. Conclusions The novel AI-based diagnostic system detected pharyngeal cancer with high sensitivity. It could facilitate early detection, thereby leading to better prognosis and quality of life for patients with pharyngeal cancers in the near future.

Introduction: We aimed to investigate the safety and efficacy of self-expandable metallic stent (SEMS) placement in patients with prior radiotherapy (RT) using the Niti-S stent, which is characterized by low radial force, in comparison to patients without prior RT. Methods: A consecutive series of 83 patients who were treated by SEMS placement using Niti-S stent for severe malignant esophageal obstruction or fistula were enrolled. The adverse event rates and efficacy were retrospectively compared between patients with/without prior RT before SEMS placement (RT group [n = 32] versus non-RT group [n = 51]). Results: The incidence rate of major adverse events in the RT group was 6.3% and was not significantly different from that in the non-RT group (5.9%, p = 0.95). Among the RT group, 84.4% were able to resume oral intake within a median of 2 days. Among the patients with fistula, 78.6% could resume oral intake and survive for 73 days after SEMS placement. Cox proportional hazard regression analysis identified significant factors affecting overall survival to be prior RT (hazard ratio [HR]: 1.96), low performance status (HR: 3.87), and subsequent anticancer treatment after SEMS placement (HR: 0.41). However, compared to the non-RT group, the RT group had received longer duration of anticancer treatment before SEMS placement and a lower rate of subsequent anticancer treatment after SEMS placement. Conclusions: With the Niti-S stent, the incidence of major adverse events was sufficiently low even for patients after RT. SEMS with low radial force would be an effective palliative treatment option for patients, regardless of prior RT.

Early detection of early gastric cancer (EGC) allows for less invasive cancer treatment. However, differentiating EGC from gastritis remains challenging. Although magnifying endoscopy with narrow band imaging (ME-NBI) is useful for differentiating EGC from gastritis, this skill takes substantial effort. Since the development of the ability to convolve the image while maintaining the characteristics of the input image (convolution neural network: CNN), allowing the classification of the input image (CNN system), the image recognition ability of CNN has dramatically improved. To explore the diagnostic ability of the CNN system with ME-NBI for differentiating between EGC and gastritis. A 22-layer CNN system was pre-trained using 1492 EGC and 1078 gastritis images from ME-NBI. A separate test data set (151 EGC and 107 gastritis images based on ME-NBI) was used to evaluate the diagnostic ability [accuracy, sensitivity, positive predictive value (PPV), and negative predictive value (NPV)] of the CNN system. The accuracy of the CNN system with ME-NBI images was 85.3%, with 220 of the 258 images being correctly diagnosed. The method’s sensitivity, specificity, PPV, and NPV were 95.4%, 71.0%, 82.3%, and 91.7%, respectively. Seven of the 151 EGC images were recognized as gastritis, whereas 31 of the 107 gastritis images were recognized as EGC. The overall test speed was 51.83 images/s (0.02 s/image). The CNN system with ME-NBI can differentiate between EGC and gastritis in a short time with high sensitivity and NPV. Thus, the CNN system may complement current clinical practice of diagnosis with ME-NBI.

Based on Japanese guidelines for endoscopic submucosal dissection (ESD) in undifferentiated-type early gastric cancer (UD-EGC), UD-predominant mixed-type (M-UD) EGC is considered high risk for lymph node metastasis (LNM). However, differences in LNM risk between pure UD (P-UD) and M-UD remain unclear. This study assessed risk factors for LNM considering differences between P-UD and M-UD and identified pathological features related to the lowest LNM risk. This single-center, retrospective study included 1425 patients with UD-EGC treated with surgical resection between April 2005 and May 2017. We divided patients into those with and without LNM and compared background characteristics and post-operative pathological results between groups. Patients were further stratified based on depth, tumor diameter, ulcerative findings, lymphatic invasion, vascular invasion, and histological type to clarify post-operative pathological features associated with the lowest LNM risk. When comparing background characteristics and post-operative pathological results, multivariate analysis showed that, in patients with LNM, tumor diameters were significantly larger, and there were higher rates of submucosal invasion, lymphatic invasion, and M-UD histological type. In patients with absence of ulcerative findings, absence of lymphatic invasion, and absence of vascular invasion, no LNM occurred among those with intramucosal P-UD tumor diameters of 1–40 mm (1–20 mm: 95% confidence interval [CI], 0–5.5%; 21–40 mm: 95% CI, 0–6.1%). Intramucosal P-UD EGC patients with absence of ulcerative findings, absence of lymphatic invasion, absence of vascular invasion, and tumor diameters of ≤ 40 mm did not show LNM. We suggest expanding indications for ESD to include these patients.

Endoscopic submucosal dissection (ESD) is the preferred treatment for esophageal squamous cell carcinoma (ESCC). However, ESD can be difficult when patients move due to insufficient sedation. We conducted a prospective confirmatory single arm study to evaluate the efficacy of using dexmedetomidine (DEX) in combination with midazolam as a novel sedation for ESD. Endoscopic submucosal dissection was performed without intubation in 65 patients. The primary outcome was the proportion of patients who did not move or require restraint during ESD, compared to historical control of ESD performed under midazolam sedation. Secondary outcomes included the frequency of complications and self-report questionnaires from patients and endoscopists. Restraint was not required in 97% of patients sedated using the combination of DEX and midazolam. Depressed respiration, low blood pressure, and bradycardia occurred in 23, 37, and 26% of patients, respectively. All patients recovered without severe complication. Occurrence of low blood pressure and bradycardia were higher, while respiratory depression was lower for the combination group than for the historical control group. The amount of midazolam used was significantly lower than in the control. Of note, 94% of patients had no painful sensations, with 3 reporting chest pain and 3 having a recollection of the procedure. Endoscopists were satisfied with the sedation in 94% of cases. All lesions were resected in en bloc fashion, without perforation. The combination of DEX and midazolam provided effective sedation for ESD for ESCC.

The double-tracer method has been established for sentinel node (SN) mapping in gastric cancer surgery. However, there remain several unresolved issues that prevent its widespread use in clinical practice. In this study, we aimed to demonstrate the feasibility of single-tracer SN mapping in laparoscopic surgery for gastric cancer, using indocyanine green (ICG) fluorescence imaging with a one-step nucleic acid amplification (OSNA) assay intraoperatively. Patients with clinical T1N0M0 gastric adenocarcinoma preoperatively were considered for inclusion if they had a single primary lesion 4 cm or less in maximal diameter. Immunohistochemical staining with the anti-cytokeratin 19 antibody was performed on preoperative biopsy specimens, and patients with faint positive reactions were excluded. Intraoperatively, single-tracer SN biopsy with ICG fluorescence imaging was performed, followed by laparoscopic gastrectomy with modified D1+ or D2 lymph node dissection. Twenty eligible patients underwent SN biopsy and laparoscopic gastrectomy. SNs were identified in 17 cases (85%), with a median number of three SNs per patient. The median times for SN mapping and OSNA assay were 19 and 35 min, respectively. OSNA assay detected one metastatic lymph node, but all other nodes were negative. No adverse effects were observed in relation to SN mapping. Single-tracer SN mapping by ICG fluorescence imaging with intraoperative diagnosis by OSNA assay is feasible and safe. SNs can be identified in most patients, without producing false-negative results. Further clinical trial to demonstrate the sensitivity is ongoing.

Background and Aims The prognosis of esophageal cancer is relatively poor. Patients are usually diagnosed at an advanced stage when it is often too late for effective treatment. Recently, artificial intelligence (AI) using deep learning has made remarkable progress in medicine. However, there are no reports on its application for diagnosing esophageal cancer. Here, we demonstrate the diagnostic ability of AI to detect esophageal cancer including squamous cell carcinoma and adenocarcinoma. Methods We retrospectively collected 8428 training images of esophageal cancer from 384 patients at the Cancer Institute Hospital, Japan. Using these, we developed deep learning through convolutional neural networks (CNNs). We also prepared 1118 test images for 47 patients with 49 esophageal cancers and 50 patients without esophageal cancer to evaluate the diagnostic accuracy. Results The CNN took 27 seconds to analyze 1118 test images and correctly detected esophageal cancer cases with a sensitivity of 98%. CNN could detect all 7 small cancer lesions less than 10 mm in size. Although the positive predictive value for each image was 40%, misdiagnosing shadows and normal structures led to a negative predictive value of 95%. The CNN could distinguish superficial esophageal cancer from advanced cancer with an accuracy of 98%. Conclusions The constructed CNN system for detecting esophageal cancer can analyze stored endoscopic images in a short time with high sensitivity. However, more training would lead to higher diagnostic accuracy. This system can facilitate early detection in practice, leading to a better prognosis in the near future.

The endocytoscopic system (ECS) helps in virtual realization of histology and can aid in confirming histological diagnosis in vivo. We propose replacing biopsy-based histology for esophageal squamous cell carcinoma (ESCC) by using the ECS. We applied deep-learning artificial intelligence (AI) to analyse ECS images of the esophagus to determine whether AI can support endoscopists for the replacement of biopsy-based histology. A convolutional neural network-based AI was constructed based on GoogLeNet and trained using 4715 ECS images of the esophagus (1141 malignant and 3574 non-malignant images). To evaluate the diagnostic accuracy of the AI, an independent test set of 1520 ECS images, collected from 55 consecutive patients (27 ESCCs and 28 benign esophageal lesions) were examined. On the basis of the receiver-operating characteristic curve analysis, the areas under the curve of the total images, higher magnification pictures, and lower magnification pictures were 0.85, 0.90, and 0.72, respectively. The AI correctly diagnosed 25 of the 27 ESCC cases, with an overall sensitivity of 92.6%. Twenty-five of the 28 non-cancerous lesions were diagnosed as non-malignant, with a specificity of 89.3% and an overall accuracy of 90.9%. Two cases of malignant lesions, misdiagnosed as non-malignant by the AI, were correctly diagnosed as malignant by the endoscopist. Among the 3 cases of non-cancerous lesions diagnosed as malignant by the AI, 2 were of radiation-related esophagitis and one was of gastroesophageal reflux disease. AI is expected to support endoscopists in diagnosing ESCC based on ECS images without biopsy-based histological reference.

Anastomotic leak is a potentially life-threatening complication following esophageal cancer surgery. In this study, we aimed to clarify the efficacy of endoscopic filling with polyglycolic acid (PGA) sheets and fibrin glue for anastomotic leak after esophageal cancer surgery. Consecutive patients who underwent endoscopic filling with PGA sheets and fibrin glue for anastomotic leak after esophageal cancer surgery between August 2014 and January 2020 were included in the study, with its efficacy retrospectively reviewed. We performed endoscopic filling using two methods: (1) filling the fistula with PGA sheets, followed by the application of a fibrinogen and thrombin solution (conventional method) and (2) filling the fistula with PGA sheets pre-soaked in a fibrinogen solution, followed by the application of a thrombin solution (pre-soak method). A total of 14 patients underwent endoscopic filling procedures within the study period. The endoscopic filling procedures were successfully performed in all cases and no adverse events associated with the procedures were observed. Fistula closure was obtained in 10 (71%) cases. In the 10 successful cases, the median number of procedures was 1 (range 1–3) and the median time from the first procedure to oral intake was 7.5 days (range 4–36 days). The success rate of the pre-soak method was significantly higher than that of the conventional method (90% vs. 25%, P = 0.041). Endoscopic filling with PGA sheets and fibrin glue is a safe and effective treatment for the closure of an anastomotic leak. The pre-soak method can achieve successful endoscopic filling.

For diagnosing gastric cancer, differences in the diagnostic performance between endocytoscopy with narrow-band imaging and magnifying endoscopy with narrow-band imaging have not been reported. We aimed to clarify these differences by analyzing diagnoses made by endoscopists in Japan. This single-center retrospective cohort study used 106 cancerous and 106 non-cancerous images obtained via both modalities (total, 424 images) for diagnosis. Sixty-one endoscopists with varying experience levels from 45 institutions were included. Diagnostic accuracy, sensitivity, specificity, and positive and negative predictive values were evaluated to determine the diagnostic performance of each modality and compared using the Mann–Whitney U test. Among all endoscopists, diagnostic accuracy, sensitivity, positive predictive value, and negative predictive value were higher with endocytoscopy with narrow-band imaging than with magnifying endoscopy with narrow-band imaging (percentage [95% confidence interval]: 78.8% [76.4–83.0%] versus 72.2% [69.3–73.6%], p

Duodenal varices are ectopic varices that are rare but can involve any site along the digestive tract outside the gastroesophageal region. Ectopic variceal bleeding is generally massive and life threatening; the mortality rate is approximately 40%. Up to 17% of ectopic varices occur in the duodenum. However, duodenal varices pose a significant therapeutic challenge due to the lack of standard treatment guidelines. We report a case of duodenal variceal bleeding secondary to portal vein stenosis in a 77-year-old woman receiving chemotherapy for unresectable perihilar cholangiocarcinoma. The patient presented with melena, nausea, vomiting and unstable vital signs suggestive of hemorrhagic shock. Emergency esophagogastroduodenoscopy revealed large nodular varices with a ruptured erosion on top in the superior duodenal angle, and variceal bleeding had stopped by the time of the procedure. Subsequent computed tomography showed the development of portosystemic collaterals; therefore, we performed percutaneous portal vein stent placement to reduce portal vein pressure. Since persistent bleeding was suspected, we also performed endoscopic injection sclerotherapy and achieved successful hemostasis with an improvement in liver function. This case revealed that a combination of portal vein stent placement and endoscopic injection sclerotherapy might be an effective therapy for duodenal variceal bleeding caused by portal vein stenosis.

Background and Aims Endoscopic submucosal dissection (ESD) has become an important and minimally invasive treatment for early gastric cancer (EGC) with a negligible risk of metastasis not only for differentiated-type (D-type) cancer but also for undifferentiated-type (UD-type) cancer. We aimed to investigate the incidence and characteristics of metachronous cancer after ESD for UD-type cancer, which has not yet been elucidated. Methods In total, 175 patients who underwent ESD for UD-type EGC were enrolled. For comparison, 350 patients who underwent ESD for D-type EGC during the same period were randomly selected. These patients underwent a follow-up EGD annually. The median observation period was 6.0 years and 5.4 years, respectively. Results The annual incidence of metachronous cancer after ESD for UD-type and D-type cancer was .9% and 5.3%, respectively. Among the patients who underwent ESD for UD-type cancer, 30.9% of patients were uninfected with Helicobacter pylori, whereas all patients who underwent ESD for D-type cancer were infected with H pylori. All patients who developed metachronous cancer were infected with H pylori. UD-type metachronous cancer developed more frequently in patients after ESD for UD-type cancer than after ESD for D-type cancer, and the curative resection rate of ESD was significantly lower in these cases. Conclusions Metachronous cancers developed only in H pylori-infected patients in this cohort. Although metachronous cancer incidence was significantly less frequent in patients after ESD for UD-type cancer, the curative resection rate of ESD was significantly lower. Routine surveillance should be conducted more carefully after ESD for UD-type cancer, especially in H pylori-infected patients.

Background and Aims The performance of magnifying endoscopy with narrow-band imaging (ME-NBI) using a computer-aided diagnosis (CAD) system in diagnosing early gastric cancer (EGC) is unclear. Here, we aimed to clarify the differences in the diagnostic performance between expert endoscopists and the CAD system using ME-NBI. Methods The CAD system was pretrained using 1492 cancerous and 1078 noncancerous images obtained using ME-NBI. One hundred seventy-four videos (87 cancerous and 87 noncancerous videos) were used to evaluate the diagnostic performance of the CAD system using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). For each item, comparisons were made between the CAD system and 11 experts who were skilled in diagnosing EGC using ME-NBI with clinical experience of more than 1 year at our hospital. Results The CAD system demonstrated an AUC of 0.8684. The accuracy, sensitivity, specificity, PPV, and NPV were 85.1% (95% confidence interval [95% CI], 79.0-89.6), 87.4% (95% CI, 78.8-92.8), 82.8% (95% CI, 73.5-89.3), 83.5% (95% CI, 74.6-89.7), and 86.7% (95% CI, 77.8-92.4), respectively. The CAD system was significantly more accurate than 2 experts, significantly less accurate than 1 expert, and not significantly different from the remaining 8 experts. Conclusions The overall performance of the CAD system using ME-NBI videos in diagnosing EGC was considered good and was equivalent to or better than that of several experts. The CAD system may prove useful in the diagnosis of EGC in clinical practice.

Background Gastrectomy with lymphadenectomy is recommended for type 3 gastric neuroendocrine tumors (G-NETs). This study aimed to identify the risk factors for lymph node metastasis (LNM) arising from G-NETs to assess the suitability of endoscopic resection (ER). Methods Nationwide clinicopathological data of patients with type 3 G-NETs who underwent surgery or ER were collected. A single pathologist graded the histological tumor specimens. Results Among 176 cases from 53 institutions, 144 were eligible for analysis (90 NET-G1 and 54 NET-G2 grade, 8-mm median-size tumors). Of these, 63 patients had undergone ER (15 with additional surgeries). Histological data regarding LNM were available for 93 surgical patients. LNM was confirmed in 15 (16%) tumors and was correlated with tumor diameter, invasion depth, and tumor grade. LNM was negative in 6 tumors ≤5 mm, confined to the mucosa or submucosa, with a grade of G1, and without lymphovascular invasion, but the number of cases was too small to propose ER indications. Among 48 patients treated with ER alone, only 1 developed recurrence; no mortality was observed at follow-up, although many patients were classified with SM2/NET-G2/tumors >5 mm. This suggests that not all LNMs arising from small G-NETs are fatal. Conclusion Gastrectomy with lymphadenectomy for Type 3 G-NETs is recommended on the basis of lymph node metastasis. However, ER for type 3 G-NETs ≤10 mm, confined to the mucosa or submucosa, with a grade of G1 has shown excellent survival outcomes despite the risk of LNM, and therefore, could be an alternative treatment option.

Objectives A Japanese multicenter prospective cohort study examining endoscopic resection (ER) for early gastric cancer (EGC) has been conducted using a Web registry developed to determine the short-term and long-term outcomes based on absolute and expanded indications. We hereby present the short-term outcomes of this study. Methods All consecutive patients with EGC or suspected EGC undergoing ER at 41 participating institutions between July 2010 and June 2012 were enrolled and prospectively registered into the Web registry. The baseline characteristics were entered before ER, and the short-term outcomes were collected at 6 months following ER. Results Nine thousand six hundred and sixteen patients with 10 821 lesions underwent ER (endoscopic submucosal dissection [ESD]: 99.4%). The median procedure time was 76 min, and R0 resections were achieved for 91.6% of the lesions. Postoperative bleeding and intraoperative perforation occurred in 4.4% and 2.3% of the patients, respectively. Significant independent factors correlated with a longer procedure time (120 min or longer) were as follows: tumor size >20 mm, upper-third location, middle-third location, local recurrent lesion, ulcer findings, gastric tube, male gender, and submucosa. Histopathologically, 10 031 lesions were identified as common-type gastric cancers. The median tumor size was 15 mm. Noncurative resections were diagnosed for 18.3% of the lesions. Additional surgery was performed for 48.6% (824 lesions) of the 1695 noncurative ER lesions with a possible risk of lymph node (LN) metastasis. Among them, 64 (7.8%) exhibited LN metastasis. Conclusions This multicenter prospective study showed favorable short-term outcomes for gastric ESD.

Image recognition using artificial intelligence with deep learning through convolutional neural networks (CNNs) has dramatically improved and been increasingly applied to medical fields for diagnostic imaging. We developed a CNN that can automatically detect gastric cancer in endoscopic images. A CNN-based diagnostic system was constructed based on Single Shot MultiBox Detector architecture and trained using 13,584 endoscopic images of gastric cancer. To evaluate the diagnostic accuracy, an independent test set of 2296 stomach images collected from 69 consecutive patients with 77 gastric cancer lesions was applied to the constructed CNN. The CNN required 47 s to analyze 2296 test images. The CNN correctly diagnosed 71 of 77 gastric cancer lesions with an overall sensitivity of 92.2%, and 161 non-cancerous lesions were detected as gastric cancer, resulting in a positive predictive value of 30.6%. Seventy of the 71 lesions (98.6%) with a diameter of 6 mm or more as well as all invasive cancers were correctly detected. All missed lesions were superficially depressed and differentiated-type intramucosal cancers that were difficult to distinguish from gastritis even for experienced endoscopists. Nearly half of the false-positive lesions were gastritis with changes in color tone or an irregular mucosal surface. The constructed CNN system for detecting gastric cancer could process numerous stored endoscopic images in a very short time with a clinically relevant diagnostic ability. It may be well applicable to daily clinical practice to reduce the burden of endoscopists.

Background: In recent years, effective outcomes of endoscopic submucosal dissection (ESD) for esophagogastric junction cancer including short-segment Barrett’s esophagus (SSBE) cancer have been reported. However, the efficacy of ESD for long-segment Barrett’s esophagus (LSBE) cancer is unknown. Aim: To clarify the treatment outcomes of ESD for LSBE cancer versus SSBE cancer. Methods: A total of 86 patients with 91 superficial Barrett’s esophageal adenocarcinomas who underwent ESD were enrolled; of these, 68 had underlying SSBE and 18 had LSBE. Procedure outcomes and prognosis were compared. Results: There was no significant difference in age and tumor diameter among patients. The only complication observed was stricture, but it was not significant (2 vs. 9%). No significant difference was observed in the negative horizontal margin rates (94.1 vs. 95.7%), R0 resection rates (83.8 vs. 82.6%), curative resection rates (72.1 vs. 73.9%), and noncurative factors. Both LSBE and SSBE cancer showed favorable 3-year overall survival rates (95.0 vs. 94.4%) in the median observation period of 28.5 months. Conclusions: ESD for LSBE cancer achieved procedure outcomes and short-term prognosis comparable to SSBE. ESD has the potential to be an effective therapeutic option for esophageal neoplasms in patients with LSBE.

BACKGROUND AND AIM In Japan, an increase in the number of routine esophagogastroduodenoscopy procedures is expected because several studies have reported that endoscopy screening has reduced gastric cancer mortality. Magnifying narrow-band imaging has been reported to be effective for accurate diagnosis of gastric abnormalities such as cancers, adenomas, and intestinal metaplasia. However, the efficacy of this method in routine esophagogastroduodenoscopy has not been clarified. METHODS We divided 3763 patients into two groups. The non-magnification group included 1842 patients who underwent endoscopy screening using GIF-H260/LUCERA-SPECTRUM between October 2014 and February 2015, whereas the magnification group included 1921 patients who underwent screening using GIF-H290Z/LUCERA-ELITE between March 2015 and May 2015. In the magnification group, diagnosis of cancer was conducted using the VS classification system. We did not carry out a biopsy when results were confirmed as non-cancer using magnifying narrow-band imaging. If cancer was diagnosed, or when a cancer or non-cancer diagnosis was difficult, we carried out a biopsy. We analyzed and compared the diagnostic performance between the two groups. RESULTS Gastric biopsy rate was significantly lower in the magnification group (29%) than in the non-magnification group (41%) (P < 0.001). Positive predictive value (PPV) for gastric cancer was significantly higher in the magnification group (5.5%) than in the non-magnification group (2.5%) (P < 0.001). Furthermore, PPV for gastric epithelial neoplasia was significantly higher in the magnification group (7.9%) than in the non-magnification group (3.2%) (P < 0.001). CONCLUSION Magnifying narrow-band imaging improves the diagnostic performance of routine esophagogastroduodenoscopy.

Background: The factors associated with the pathogenesis of Helicobacter pylori-uninfected undifferentiated-type early gastric cancer (HPUGC) remain unclear. This study compared patient characteristics, including medical history and alcohol/tobacco use, of HPUGC patients with characteristics of patients with H. pylori-positive undifferentiated-type early gastric cancer (HPPGC) to clarify and gain understanding on those differences that could play a role in the pathogenesis. Methods: This retrospective study included 282 patients who were treated endoscopically from March 2005 to March 2014. This cohort consisted of 232 patients with HPPGC (82.3%) and 50 patients with HPUGC (17.7%). Patient characteristics were analyzed by subgroups of HPUGC vs. HPPGC, with comparisons for age, gender, cancer history, comorbidity of lifestyle diseases requiring medication (hypertension, type 2 diabetes, and dyslipidemia), cumulative amount of alcohol consumption, and smoking history (Brinkman index [BI]). Results: HPUGC patients were typically younger, had less frequent hypertension, and had higher BI values (p < 0.05 for all parameters). In a younger non-hypertensive subgroup, the OR for high BI (BI ≥340) in the HPUGC group vs. HPPGC group was 5.049 (95% CI 2.458–10.373, p < 0.0001). Conclusions: The investigation of clinical factors identified smoking history as being possibly contributing to the pathogenesis of HPUGC. Future research is necessary at the cellular and genetic levels.

In Japan, endoscopic resection (ER) is often used to treat esophageal squamous cell carcinoma (ESCC) when invasion depths are diagnosed as EP-SM1, whereas ESCC cases deeper than SM2 are treated by surgical operation or chemoradiotherapy. Therefore, it is crucial to determine the invasion depth of ESCC via preoperative endoscopic examination. Recently, rapid progress in the utilization of artificial intelligence (AI) with deep learning in medical fields has been achieved. In this study, we demonstrate the diagnostic ability of AI to measure ESCC invasion depth. We retrospectively collected 1751 training images of ESCC at the Cancer Institute Hospital, Japan. We developed an AI-diagnostic system of convolutional neural networks using deep learning techniques with these images. Subsequently, 291 test images were prepared and reviewed by the AI-diagnostic system and 13 board-certified endoscopists to evaluate the diagnostic accuracy. The AI-diagnostic system detected 95.5% (279/291) of the ESCC in test images in 10 s, analyzed the 279 images and correctly estimated the invasion depth of ESCC with a sensitivity of 84.1% and accuracy of 80.9% in 6 s. The accuracy score of this system exceeded those of 12 out of 13 board-certified endoscopists, and its area under the curve (AUC) was greater than the AUCs of all endoscopists. The AI-diagnostic system demonstrated a higher diagnostic accuracy for ESCC invasion depth than those of endoscopists and, therefore, can be potentially used in ESCC diagnostics.

Pretreatment biopsy may not correctly diagnose mixed-type early gastric cancers. Despite reports on the usefulness of magnifying endoscopy with narrow-band imaging in diagnosing early gastric cancers, no reports exist on differences in magnifying endoscopy with narrow-band imaging findings between differentiated-type-predominant mixed-type and undifferentiated-type-predominant mixed-type early gastric cancers. This study aimed to clarify differences in magnifying endoscopy with narrow-band imaging findings and investigate the additive effect of combining magnifying endoscopy with narrow-band imaging and biopsy findings for pretreatment histological-type diagnosis. Patients undergoing endoscopic submucosal dissection as initial treatment between April 2005 and March 2017 participated in this retrospective study. There were 156 differentiated-type-predominant mixed-type and 36 undifferentiated-type-predominant mixed-type lesions. We extracted the most significant magnifying endoscopy with narrow-band imaging findings of differentiated-type-predominant mixed-type and undifferentiated-type-predominant mixed-type lesions using multivariate analysis and compared the accuracy, sensitivity, and specificity between pretreatment biopsy alone and a combination of biopsy and magnifying endoscopy with narrow-band imaging findings. Significant magnifying endoscopy with narrow-band imaging findings was fine network pattern in differentiated-type-predominant and corkscrew pattern in undifferentiated-type-predominant mixed-type lesions. Accuracy, sensitivity, and specificity were significantly higher with combined biopsy and magnifying endoscopy with narrow-band imaging findings than with pretreatment biopsy alone. The study results demonstrated the additive effect of magnifying endoscopy with narrow-band imaging with biopsy for diagnosing mixed-type early gastric cancers. This study may be beneficial in routine practice because it indicates a possibility of reducing additional surgery after endoscopic submucosal resection because of incorrect diagnosis of histological type.

Background and aim Gastric neoplasms (GN), including gastric adenoma and carcinoma, are well known as extracolonic manifestations of familial adenomatous polyposis (FAP). We aimed to investigate the clinicopathological features of GN in FAP patients and to clarify their relationship with the endoscopic status of the background mucosa. Methods We analyzed the records of 39 patients who were diagnosed with FAP and underwent esophagogastroduodenoscopy between April 2005 and July 2016. Patients were divided into two groups according to atrophic gastritis (AG) status. Endoscopic findings of GN and background mucosa, and histopathological findings, including phenotypic expression of GN and mutation locus of adenomatous polyposis coli (APC) gene, were evaluated. Results Gastric neoplasms were more predominant in the AG-positive group than in the AG-negative group (6/9, 66.7% vs 7/30, 23.3%; P = 0.039). Of 36 GN detected in 13 patients, six GN in five patients were followed and 30 GN in eight patients were endoscopically resected and analyzed. GN in the AG-negative group frequently showed whitish color, were located in the proximal stomach, and presented the gastric immunophenotype compared to GN in the AG-positive group. All GN were intramucosal lesions and were curatively resected regardless of AG status. APC germline mutations were identified in 32 patients. In patients with GN, a significantly higher number of mutation loci were among exons 10-15 (codons 564-1465). Conclusion Clinicopathological characteristics and phenotypic expressions of GN in FAP patients depend on background mucosa status with or without AG. These findings are useful for detecting GN in FAP patients.

Epstein–Barr virus-positive gastric cancer (EBVGC) is associated with a low prevalence of lymph node metastasis (LNM); however, EBV status is not considered in the indication of endoscopic resection (ER). We aimed to clarify the implication of EBV status for ER of pT1b GC. Consecutive cases of pT1b GCs treated with surgery between 2005 and 2014 were retrospectively analyzed. Clinicopathological factors and LNM status were compared between EBVGC and non-EBVGC groups. EBVGC accounted for 7.9% (71 of 898) cases. Compared to non-EBVGC, EBVGC was more frequent in males (p = 0.0055), the upper third region (p

Owing to increased awareness and use of narrow-band imaging, there are more opportunities to treat superficial pharyngeal cancer (SPC). The present study aimed to describe the short- and long-term outcomes of endoscopic resection (ER) for SPC.This study included 166 consecutive SPC in 113 patients treated during 2006 to 2013 at one referral cancer center. In the first period, we treated patients using endoscopic mucosal resection (EMR), in the second period using conventional ESD (cESD) and in the recent period using double-scope ESD (dsESD), which involves a second thin endoscope for assistance to produce traction. Median follow-up period was 30 months.All lesions were diagnosed as squamous cell carcinoma. Complete resection rate of cESD and dsESD procedures was 56.4% and 82.3% (P 0.01), and local recurrence rate was 2.6% and 0.0%, respectively. Procedure duration was significantly shorter for dsESD than for cESD (P 0.05). Four cases of recurrent lymph node (LN) metastasis were observed; however, all patients with LN metastases survived to a 48-month median interval after neck dissection. Risk factors for LN metastasis included subepithelium invasion, tumor thickness1000 μm, droplet infiltration, and lymphovascular invasion. Overall survival rate after 5 years was 79.5%; no patients died of SPC. Cumulative rate of metachronous SPC after 5 years was 46.5%.ER for SPC is a feasible and effective treatment, although metachronous SPC occurred frequently. For the technique of ER, dsESD was effective.

Background and Aims Laparoscopic gastric resection is widely used for gastric submucosal tumors (SMTs). However, determining an appropriate resection line using only the laparoscopic approach is difficult. We developed a laparoscopic and endoscopic cooperative surgery (LECS) technique by combining laparoscopic gastric resection with endoscopic submucosal dissection, and we have used this procedure to resect gastric SMTs. In this study, the procedure is presented and its safety and feasibility for resecting gastric SMTs are evaluated. Methods This retrospective study included 100 patients who underwent LECS for SMTs at the Department of Gastroenterological Surgery, Cancer Institute, between June 2006 and November 2014. The demographics, tumor histopathologic characteristics, and operative and follow-up data were reviewed. Results Complete resection with negative surgical margins was achieved in all patients, and LECS was performed regardless of tumor location. The mean operation time was 174.3 minutes, with an estimated blood loss of 16.3 mL. In addition, the mean time until the initiation of oral intake was 1.4 days, and the mean postoperative hospital stay was 8.4 days. Moreover, no local or distant tumor recurrence was observed. The only severe adverse event was leakage, which was observed in 1 patient. Conclusions LECS was performed with a reasonable operation time, low blood loss, and minimal adverse events. Therefore LECS is safe and feasible for resecting gastric SMTs.