Exploring non-curative endoscopic submucosal dissection: Current treatment optimization and future indication expansion.

The increasing popularity of endoscopic submucosal dissection (ESD) as a treatment for early gastric cancer has highlighted the importance of quality assessment in achieving curative resections. This article emphasizes the significance of evaluating ESD quality, not only for curative cases but also for non-curative ones. Postoperative assessment relies on the endoscopic curability (eCura) classification, but management strategies for eCuraC-1 tumour with a positive horizontal margin are unclear. Current research primarily focuses on comparing additional surgical procedures in high-risk patients, while studies specifically targeting eCuraC-1 patients are limited. Exploring management strategies and follow-up outcomes for such cases could provide valuable insights. Furthermore, the application of molecular imaging using near-infrared fluorescent tracers holds promise for precise tumour diagnosis and navigation, potentially impacting the management of early-stage gastric cancer patients. Advancing research in these areas is essential for improving the overall efficacy of endoscopic techniques and refining treatment indications.

Effect of an artificial intelligence-assisted system on endoscopic diagnosis of superficial oesophageal squamous cell carcinoma and precancerous lesions: a multicentre, tandem, double-blind, randomised controlled trial.

BACKGROUND: Despite the usefulness of white light endoscopy (WLE) and non-magnified narrow-band imaging (NBI) for screening for superficial oesophageal squamous cell carcinoma and precancerous lesions, these lesions might be missed due to their subtle features and interpretation variations among endoscopists. Our team has developed an artificial intelligence (AI) system to detect superficial oesophageal squamous cell carcinoma and precancerous lesions using WLE and non-magnified NBI. We aimed to evaluate the auxiliary diagnostic performance of the AI system in a real clinical setting. METHODS: We did a multicentre, tandem, double-blind, randomised controlled trial at 12 hospitals in China. Eligible patients were aged 18 years or older and underwent sedated upper gastrointestinal endoscopy for screening, investigation of gastrointestinal symptoms, or surveillance. Patients were randomly assigned (1:1) to either the AI-first group or the routine-first group using a computerised random number generator. Patients, pathologists, and statistical analysts were masked to group assignment, whereas endoscopists and research assistants were not. The same endoscopist at each centre did tandem upper gastrointestinal endoscopy for each eligible patient on the same day. In the AI-first group, the endoscopist did the first examination with the assistance of the AI system and the second examination without it. In the routine-first group, the order of examinations was reversed. The primary outcome was the miss rate of superficial oesophageal squamous cell carcinoma and precancerous lesions, calculated on a per-lesion and per-patient basis. All analyses were done on a per-protocol basis. This trial is registered with the Chinese Clinical Trial Registry (ChiCTR2100052116) and is completed. FINDINGS: Between Oct 19, 2021, and June 8, 2022, 5934 patients were randomly assigned to the AI-first group and 5912 to the routine-first group, of whom 5865 and 5850 were eligible for analysis. Per-lesion miss rates were 1·7% (2/118; 95% CI 0·0-4·0) in the AI-first group versus 6·7% (6/90; 1·5-11·8) in the routine-first group (risk ratio 0·25, 95% CI 0·06-1·08; p=0·079). Per-patient miss rates were 1·9% (2/106; 0·0-4·5) in AI-first group versus 5·1% (4/79; 0·2-9·9) in the routine-first group (0·37, 0·08-1·71; p=0·40). Bleeding after biopsy of oesophageal lesions was observed in 13 (0·2%) patients in the AI-first group and 11 (0·2%) patients in the routine-first group. No serious adverse events were reported by patients in either group. INTERPRETATION: The observed effect of AI-assisted endoscopy on the per-lesion and per-patient miss rates of superficial oesophageal squamous cell carcinoma and precancerous lesions under WLE and non-magnified NBI was consistent with substantial benefit through to a neutral or small negative effect. The effectiveness and cost-benefit of this AI system in real-world clinical settings remain to be further assessed. FUNDING: National Natural Science Foundation of China, 1·3·5 project for disciplines of excellence, West China Hospital, Sichuan University, and Chengdu Science and Technology Project. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Artificial intelligence for detecting and delineating the extent of superficial esophageal squamous cell carcinoma and precancerous lesions under narrow-band imaging (with video).

BACKGROUND AND AIMS: Although narrow-band imaging (NBI) is a useful modality for detecting and delineating esophageal squamous cell carcinoma (ESCC), there is a risk of incorrectly determining the margins of some lesions even with NBI. This study aimed to develop an artificial intelligence (AI) system for detecting superficial ESCC and precancerous lesions and delineating the extent of lesions under NBI. METHODS: Nonmagnified NBI images from 4 hospitals were collected and annotated. Internal and external image test datasets were used to evaluate the detection and delineation performance of the system. The delineation performance of the system was compared with that of endoscopists. Furthermore, the system was directly integrated into the endoscopy equipment, and its real-time diagnostic capability was prospectively estimated. RESULTS: The system was trained and tested using 10,047 still images and 140 videos from 1112 patients and 1183 lesions. In the image testing, the accuracy of the system in detecting lesions in internal and external tests was 92.4% and 89.9%, respectively. The accuracy of the system in delineating extents in internal and external tests was 88.9% and 87.0%, respectively. The delineation performance of the system was superior to that of junior endoscopists and similar to that of senior endoscopists. In the prospective clinical evaluation, the system exhibited satisfactory performance, with an accuracy of 91.4% in detecting lesions and an accuracy of 85.9% in delineating extents. CONCLUSIONS: The proposed AI system could accurately detect superficial ESCC and precancerous lesions and delineate the extent of lesions under NBI.

Artificial intelligence for diagnosing gastric lesions under white-light endoscopy.

BACKGROUND: The ability of endoscopists to identify gastric lesions is uneven. Even experienced endoscopists may miss or misdiagnose lesions due to heavy workload or fatigue or subtle changes in lesions under white-light endoscopy (WLE). This study aimed to develop an artificial intelligence (AI) system that could diagnose six common gastric lesions under WLE and to explore its role in assisting endoscopists in diagnosis. METHODS: Images of early gastric cancer, advanced gastric cancer, submucosal tumor, polyp, peptic ulcer, erosion, and lesion-free gastric mucosa were retrospectively collected to train and test the system. The performance of the system was compared with that of 12 endoscopists. The performance of endoscopists with or without referring to the system was also evaluated. RESULTS: A total of 29,809 images from 8947 patients and 1579 images from 496 patients were used to train and test the system, respectively. For per-lesion analysis, the overall accuracy of the system was 85.7%, which was comparable to that of senior endoscopists (85.1%, P = 0.729) and significantly higher than that of junior endoscopists (78.8%, P < 0.001). With system assistance, the overall accuracies of senior and junior endoscopists increased to 89.3% (4.2%, P < 0.001) and 86.2% (7.4%, P < 0.001), respectively. Senior and junior endoscopists achieved varying degrees of improvement in the diagnostic performance of other types of lesions except for polyp. The diagnostic times of senior (3.8 vs 3.2 s per image, P = 0.500) and junior endoscopists (6.2 vs 4.6 s per image, P = 0.144) assisted by the system were both slightly shortened, despite no significant differences. CONCLUSIONS: The proposed AI system could be applied as an auxiliary tool to reduce the workload of endoscopists and improve the diagnostic accuracy of gastric lesions.

Artificial intelligence for diagnosing microvessels of precancerous lesions and superficial esophageal squamous cell carcinomas: a multicenter study.

BACKGROUND: Intrapapillary capillary loop (IPCL) is an important factor for predicting invasion depth of esophageal squamous cell carcinoma (ESCC). The invasion depth is closely related to the selection of treatment strategy. However, diagnosis of IPCLs is complicated and subject to interobserver variability. This study aimed to develop an artificial intelligence (AI) system to predict IPCLs subtypes of precancerous lesions and superficial ESCC. METHODS: Images of magnifying endoscopy with narrow band imaging from three hospitals were collected retrospectively. IPCLs subtypes were annotated on images by expert endoscopists according to Japanese Endoscopic Society classification. The performance of the AI system was evaluated using internal and external validation datasets (IVD and EVD) and compared with that of the 11 endoscopists. RESULTS: A total of 7094 images from 685 patients were used to train and validate the AI system. The combined accuracy of the AI system for diagnosing IPCLs subtypes in IVD and EVD was 91.3% and 89.8%, respectively. The AI system achieved better performance than endoscopists in predicting IPCLs subtypes and invasion depth. The ability of junior endoscopists to diagnose IPCLs subtypes (combined accuracy: 84.7% vs 78.2%, P < 0.0001) and invasion depth (combined accuracy: 74.4% vs 67.9%, P < 0.0001) were significantly improved with AI system assistance. Although there was no significant differences, the performance of senior endoscopists was slightly elevated. CONCLUSIONS: The proposed AI system could improve the diagnostic ability of endoscopists to predict IPCLs classification of precancerous lesions and superficial ESCC.

Artificial intelligence for detecting superficial esophageal squamous cell carcinoma under multiple endoscopic imaging modalities: A multicenter study.

BACKGROUND AND AIM: Diagnosis of esophageal squamous cell carcinoma (ESCC) is complicated and requires substantial expertise and experience. This study aimed to develop an artificial intelligence (AI) system for detecting superficial ESCC under multiple endoscopic imaging modalities. METHODS: Endoscopic images were retrospectively collected from West China Hospital, Sichuan University as a training dataset and an independent internal validation dataset. Images from other four hospitals were used as an external validation dataset. The AI system was compared with 11 experienced endoscopists. Furthermore, videos were collected to assess the performance of the AI system. RESULTS: A total of 53 933 images from 2621 patients and 142 videos from 19 patients were used to develop and validate the AI system. In the internal and external validation datasets, the performance of the AI system under all or different endoscopic imaging modalities was satisfactory, with sensitivity of 92.5-99.7%, specificity of 78.5-89.0%, and area under the receiver operating characteristic curves of 0.906-0.989. The AI system achieved comparable performance with experienced endoscopists. Regarding superficial ESCC confined to the epithelium, the AI system was more sensitive than experienced endoscopists on white-light imaging (90.8% vs 82.5%, P = 0.022). Moreover, the AI system exhibited good performance in videos, with sensitivity of 89.5-100% and specificity of 73.7-89.5%. CONCLUSIONS: We developed an AI system that showed comparable performance with experienced endoscopists in detecting superficial ESCC under multiple endoscopic imaging modalities and might provide valuable support for inexperienced endoscopists, despite requiring further evaluation.

New anti-reflux plastic stent to reduce the risk of stent-related cholangitis in the treatment of biliary strictures.

BACKGROUND: There is little data available on the role of new anti-reflux plastic stents (ARPSs). AIM: To compare the use of ARPSs with that of traditional plastic stents (TPSs) for patients with biliary strictures. METHODS: Consecutive patients with biliary strictures who underwent first endoscopic biliary stenting between February 2016 and May 2019 were included. The onset of stent-related cholangitis, stent patency, clinical success, and other adverse events were evaluated. RESULTS: Sixty-seven patients in the ARPS group and 66 patients in the TPS group were included in the final analyses. Fewer patients experienced stent-related cholangitis in the ARPS group than that in the TPS group (8 patients vs 18 patients; P = 0.030). The median time till the onset of first stent-related cholangitis was later in the ARPS group than that in the TPS group (128.5 d vs 76 d; P = 0.039). The cumulative median stent patency in the ARPS group was 185 d, which was significantly longer than that in the TPS group (133 d; P = 0.001). The clinical success rates and other adverse events did not significantly differ between both groups. CONCLUSION: Placement of new ARPS might be a safe and effective optional therapeutic strategy to reduce the risk of stent-related cholangitis and prolong stent patency.

Aorto-esophageal fistula caused by fishbone ingestion: a case report on staged endovascular and endoscopic treatment.

BACKGROUND: Aorto-esophageal fistula (AEF) caused by foreign bodies ingestion is a rare but devastating disorder. Thoracic endovascular aortic repair (TEVAR) has become a widely accepted intervention for treating aorto-esophageal fistulas. As for post-TEVAR esophageal defect, secondary esophagectomy has been the recommended choice for most of the AEFs, but there is no general consensus with regard to the need of secondary surgeries for patients in the absence of clear signs of reinfection or bleeding. We herein presented a case of an AEF caused by fishbone ingestion, after successful TEVAR, the esophageal lesion was closed endoscopically. CASE PRESENTATION: A 38-year-old male presented with esophageal fistula for 4 months. He was diagnosed with AEF because of Chiari's triad after fishbone ingestion 4 months ago. Emergency thoracic aortic stent implantation was done, and given broad spectrum antibiotics and blood transfusion. His symptoms were improved, and discharged with an esophageal fistula left to heal itself. Nevertheless, after 4 months, re-examination of esophago-gastro-duodenoscopy revealed that the diameter of the fistula was changed from 3 to 6 mm. He was then admitted to our hospital for esophageal fistula repair. Laboratory examinations and chest computed tomography showed no signs of active infection, and endoscopic closure of the fistula was achieved with 4 clips. After that, he was discharged and gradually returned to normal diet. CONCLUSION: For AEFs in the absence of active infection with repaired aorta but persistent esophageal fistula, endoscopic closure by endoclips might be an effective treatment choice.

Artificial intelligence-assisted esophageal cancer management: Now and future.

Esophageal cancer poses diagnostic, therapeutic and economic burdens in high-risk regions. Artificial intelligence (AI) has been developed for diagnosis and outcome prediction using various features, including clinicopathologic, radiologic, and genetic variables, which can achieve inspiring results. One of the most recent tasks of AI is to use state-of-the-art deep learning technique to detect both early esophageal squamous cell carcinoma and esophageal adenocarcinoma in Barrett's esophagus. In this review, we aim to provide a comprehensive overview of the ways in which AI may help physicians diagnose advanced cancer and make clinical decisions based on predicted outcomes, and combine the endoscopic images to detect precancerous lesions or early cancer. Pertinent studies conducted in recent two years have surged in numbers, with large datasets and external validation from multi-centers, and have partly achieved intriguing results of expert's performance of AI in real time. Improved pre-trained computer-aided diagnosis algorithms in the future studies with larger training and external validation datasets, aiming at real-time video processing, are imperative to produce a diagnostic efficacy similar to or even superior to experienced endoscopists. Meanwhile, supervised randomized controlled trials in real clinical practice are highly essential for a solid conclusion, which meets patient-centered satisfaction. Notably, ethical and legal issues regarding the black-box nature of computer algorithms should be addressed, for both clinicians and regulators.

Peroral endoscopic myotomy for management of gastrointestinal motility disorder.

Achalasia is a type of esophageal motility disorder, consisting of relaxation dysfunction of the lower esophagus and disturbed esophageal peristalsis. Related clinical symptoms include dysphagia, regurgitation, chest pain, and weight loss. Traditional treatment options include endoscopic botulinum toxin injection, endoscopic pneumatic dilation, and laparoscopic Heller's myotomy. These therapies mainly relieve symptoms by reducing the pressure on the lower esophageal sphincter and reducing blood flow resistance at the esophagogastric junction. Based on endoscopic submucosal dissection and natural orifice transluminal endoscopic surgery, peroral endoscopic myotomy (POEM) is a purely endoscopic method of myotomy with minimal invasiveness and a low rate of adverse events when performed by experienced operators. Since then, numerous studies have shown the significant clinical efficacy and safety of POEM. The purpose of this article is to introduce different modified POEMs, special indications for different POEMs, and their advantages as well as disadvantages.

Biliary spontaneous dislodgement spiral stent for patients who underwent mechanical lithotripsy.

BACKGROUND: The incidence of post-endoscopic retrograde cholangiopancreatography (ERCP) cholangitis (PEC) in patients who underwent mechanical lithotripsy (ML) for large stone removal is high (up to 13.3%). One of the main causes is remaining small fragments or sludge that can impair normal biliary drainage. Endoscopic placement of a nasobiliary tube or a conventional plastic biliary stent has been commonly used under such conditions, but the patient may suffer from significant discomfort after the placement of a nasobiliary tube, while additional endoscopy is required for stent removal. We developed a biliary spontaneous dislodgement spiral stent (BSDSS) to overcome those shortcomings. AIM: To evaluate the feasibility, safety, and effectiveness of inserting a BSDSS for patients who underwent ML for large stone removal. METHODS: We conducted a single-center, retrospective, cohort study at West China Hospital, Sichuan University. A total of 91 consecutive patients with large biliary stones (≥ 10 mm) in the common bile duct who underwent ML between November 2017 and July 2018 were included. The 49 eligible patients were divided into the BSDSS group and the nasobiliary tube group. Technical success, post-ERCP adverse events (including PEC, post-ERCP pancreatitis, stone recurrence, BSDSS retention, self-extraction and dislocation of the nasobiliary tube), drainage time, and postoperative stay were measured and compared. RESULTS: Twenty-one patients in the BSDSS group and 28 patients in the nasobiliary tube group were included in the analyses. The baseline characteristics and clinical information were similar in the two groups. Insertions of BSDSS and nasobiliary tube were technically successful in all 49 patients. There was no significant difference in the incidence of overall post-ERCP adverse events between the two groups (4.8% in the BSDSS group vs 17.9% in the nasobiliary tube group, P = 0.219). The median duration of drainage time (3 d in the BSDSS group vs 4 d in the nasobiliary tube group) and length of postoperative stay (4 d in the BSDSS group vs 5 d in the nasobiliary tube group) also did not differ (P = 0.934, and P = 0.223, respectively). CONCLUSION: Endoscopic placement of a BSDSS appears to be feasible, safe and effective for patients who underwent ML for large stone removal.

Risk factors for distal migration of biliary plastic stents and related duodenal injury.

BACKGROUND: The risk factors of duodenal injury from distal migrated biliary plastic stents remain uncertain. The aim of this study was to determine the risk factors of distal migration and its related duodenal injury in patients who underwent placement of a single biliary plastic stent for biliary strictures. METHODS: We retrospectively reviewed all patients with biliary strictures who underwent endoscopic placement of a single biliary plastic stent from January 2006 to October 2017. RESULTS: Two hundred forty-eight patients with 402 endoscopic retrograde cholangiopancreatography procedures were included. The incidence of distal migration was 6.2%. The frequency of duodenal injury was 2.2% in all cases and 36% in cases with distal migration. Benign biliary strictures (BBS), length of the stent above the proximal end of the stricture (> 2 cm), and duration of stent retention (< 3 months) were independently associated with distal migration (p = 0.018, p = 0.009, and p = 0.016, respectively). Duodenal injury occurred more commonly in cases with larger angle (≥ 30°) between the distal end of the stent and the centerline of the patient's body (p = 0.018) or in cases with stent retention < 3 months (p = 0.031). CONCLUSIONS: The risk factors of distal migration are BBS and the length of the stent above the proximal end of the stricture. The risk factor of duodenal injury due to distal migration is large angle (≥ 30°) between the distal end of the stent and the centerline of the patient's body. Distal migration and related duodenal injury are more likely to present during the early period after biliary stenting.