Combined treatment of refractory benign stricture after esophageal endoscopic mucosal dissection: A case report.

BACKGROUND: Endoscopic submucosal dissection (ESD) post-procedure stricture is a relatively common long-term complication following ESD treatment. A range of approaches has been implemented for the treatment of post-procedural stricture using endoscopic techniques such as endoscopic dilation, self-expandable metallic stent insertion, local steroid injection in the esophagus, oral steroid administration, radial incision and cutting (RIC). The actual efficacy of these different therapeutic options is highly variable, and uniform international standards for the prevention or treatment of stricture. CASE SUMMARY: In this report, we describe the case of a 51-year-old male diagnosed with early esophageal cancer. To protect against esophageal stricture, the patient was administered oral steroids and underwent self-expandable metallic stent insertion for 45 d. Despite these interventions, stricture was detected at the lower edge of the stent following its removal. The patient remained refractory to multiple rounds of endoscopic bougie dilation treatment, and thus suffered from complex refractory benign esophageal stricture. As such, RIC combined with bougie dilation and steroid injection was employed to treat this patient more effectively, ultimately achieving satisfactory therapeutic efficacy. CONCLUSION: Combination of RIC, dilation, and steroid injection can be safely and effectively implemented to treat cases of post-ESD refractory esophageal stricture.

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.