Advances in the application of regenerative medicine in prevention of post-endoscopic submucosal dissection for esophageal stenosis

Wang, Jiaxin; Zhao, Yan; Zhang, Shutian

doi:10.2478/jtim-2022-0011

Cited by 7 publications

(3 citation statements)

References 87 publications

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“…Steroid injection therapy and oral steroid administration are the mainstream. Many other clinical applications have also been developed, such as tissue shielding methods with polyglycolic acid sheet, autologous oral mucosal epithelial sheet transplantation, and stent placement [22][23][24][25][26]. However, it would be better if these preventive procedures are adopted before the stricture happens.…”

Section: Discussionmentioning

confidence: 99%

A novel risk score model of esophageal stricture for patients undergoing endoscopic submucosal dissection

Yan,

Yang,

Gao

et al. 2023

European Journal of Gastroenterology &Amp; Hepatology

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Background and purpose Endoscopic submucosal dissection (ESD) is a promising technique for superficial esophageal lesions. However, stricture is a frequent adverse complication. This study was performed to develop a precise and convenient score prediction model for esophageal strictures after ESD, and compare its efficacy with a previously published predictive model. Methods This study enrolled clinical data of patients who underwent esophageal ESD for superficial esophageal lesions. Possible risk factors for esophageal stricture were identified by univariate and multivariate logistic regression analysis. Then we developed a prediction model according to the Framingham system for the first time and presented a convenient table containing the risk probability for each patient. In addition, we validated our score model and the previously published model in our center. Results A total of 838 patients were enrolled in this study and 6 variables, including age, surgery time, location of the lesion, circumference of the lesion, longitudinal resection length, and depth of infiltration were comprised in the score model. The total score ranged from 0 to 16 points and the risk probability was presented in one concise table for each patient. Areas under receiver-operator characteristic curves for the prediction model were 0.715 in derivation group and 0.804 in validation group. Conclusion We designed and validated a prediction score model for esophageal stricture after ESD, which can be applied conveniently to stratify the stricture risk after esophageal ESD and may facilitate appropriate clinical decision-making for these patients.

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Section: Discussionmentioning

confidence: 99%

A novel risk score model of esophageal stricture for patients undergoing endoscopic submucosal dissection

Yan,

Yang,

Gao

et al. 2023

European Journal of Gastroenterology &Amp; Hepatology

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“…Similar to the endoscopic treatment for colorectal polyps, the choices for SNADETs mainly include cold snare polypectomy (CSP), EMR, underwater EMR (UEMR), ESD, and laparoscopic endoscopic cooperative surgery (LECS). [ 60 , 61 , 62 ] However, characterized by a narrow lumen, rich vascularity, weak muscle layer, abundant Brunner’s gland, and the hardship of endoscope control, the duodenum ranks as one of the most dangerous operating areas in the digestive tract. [ 63 ] Furthermore, unlike the intensive experience in colonoscopy, [ 64 ] the experience of endoscopic treatment in the duodenum remains limited.…”

Section: Endoscopic Treatment For Snadetsmentioning

confidence: 99%

Endoscopic diagnosis and treatment of superficial non-ampullary duodenal epithelial tumors: A review

Zhao,

Jiao,

Yang

et al. 2023

Journal of Translational Internal Medicine

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The surface of the small bowel mucosa is covered more than any other section of the digestive canal; however, the overall prevalence of small bowel tumors of the whole gastrointestinal tract is evidently low. Owing to the improvement in endoscopic techniques, the prevalence of small bowel tumors has increased across multiple countries, which is mainly due to an increase in duodenal tumors. Superficial non-ampullary duodenal epithelial tumors (SNADETs) are defined as tumors originating from the non-ampullary region in the duodenum that share similarities and discrepancies with their gastric and colorectal counterparts in the pathogenesis and clinicopathologic characteristics. To date, white light endoscopy (WLE) remains the cornerstone of endoscopic diagnosis for SNADETs. Besides, narrow-band imaging (NBI) techniques and magnifying endoscopy (ME) have been widely used in the clinic and endorsed by multiple guidelines and consensuses for SNADETs’ evaluation. Confocal laser endomicroscopy (CLE), endocytoscopy (ECS), and artificial intelligence (AI) are also up-and-coming methods, showing an exceptional value in the diagnosis of SNADETs. Similar to the endoscopic treatment for colorectal polyps, the choices for SNADETs mainly include cold snare polypectomy (CSP), endoscopic mucosal resection (EMR), endoscopic submucosal dissection (ESD), and laparoscopic endoscopic cooperative surgery (LECS). However, owing to the narrow lumen, rich vascularity, weak muscle layer, abundant Brunner’s gland, and the hardship of endoscope control, the duodenum ranks as one of the most dangerous operating areas in the digestive tract. Therefore, endoscopists must anticipate the difficulties in endoscopic maneuverability, remain aware of the increased risk of complications, and then select the appropriate treatment according to the advantages and disadvantages of each method.

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“…[ 1 , 2 ] Compared with computed tomography and magnetic resonance imaging, [ 3 ] EUS is considered the most accurate procedure for detecting and diagnosing SMTs owing to its unique ability to examine tumors with high proximity. [ 4 – 9 ] Besides, EUS is the only imaging technique that can delineate the separate histologic layers of the GI tract. [ 10 , 11 ]…”

Section: Introductionmentioning

confidence: 99%

A deep learning–based system to identify originating mural layer of upper gastrointestinal submucosal tumors under EUS

Li,

Zhang,

Yao

et al. 2023

Endosc Ultrasound

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Background and Objective EUS is the most accurate procedure to determine the originating mural layer and subsequently select the treatment of submucosal tumors (SMTs). However, it requires superb technical and cognitive skills. In this study, we propose a system named SMT Master to determine the originating mural layer of SMTs under EUS. Materials and Methods We developed 3 models: deep convolutional neural network (DCNN) 1 for lesion segmentation, DCNN2 for mural layer segmentation, and DCNN3 for the originating mural layer classification. A total of 2721 EUS images from 201 patients were used to train the 3 models. We validated our model internally and externally using 283 images from 26 patients and 172 images from 26 patients, respectively. We applied 368 images from 30 patients for the man-machine contest and used 30 video clips to test the originating mural layer classification. Results In the originating mural layer classification task, DCNN3 achieved a classification accuracy of 84.43% and 80.68% at internal and external validations, respectively. In the video test, the accuracy was 80.00%. DCNN1 achieved Dice coefficients of 0.956 and 0.776 for lesion segmentation at internal and external validations, respectively, whereas DCNN2 achieved Dice coefficients of 0.820 and 0.740 at internal and external validations, respectively. The system achieved 90.00% accuracy in classification, which is comparable with that of EUS experts. Conclusions Our proposed system has the potential to solve difficulties in determining the originating mural layer of SMTs in EUS procedures, which relieves the EUS learning pressure of physicians.

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Advances in the application of regenerative medicine in prevention of post-endoscopic submucosal dissection for esophageal stenosis

Cited by 7 publications

References 87 publications

A novel risk score model of esophageal stricture for patients undergoing endoscopic submucosal dissection

A novel risk score model of esophageal stricture for patients undergoing endoscopic submucosal dissection

Endoscopic diagnosis and treatment of superficial non-ampullary duodenal epithelial tumors: A review

A deep learning–based system to identify originating mural layer of upper gastrointestinal submucosal tumors under EUS

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