Search

Objectives: Endoscopic submucosal dissection (ESD) for superficial esophageal squamous cell carcinoma (ESCC) is performed for the treatment of lesions with varied backgrounds and factors. However, the predictive factors associated with the technical difficulty of ESD remain unknown in patients with varied lesions. Therefore, this study aimed to identify the predictive factors associated with the technical difficulty of ESD for ESCC using a retrospective cohort. Methods: This multicenter, retrospective study was conducted in 10 hospitals in Japan. Consecutive patients who underwent esophageal ESD between January 2013 and December 2019 were enrolled. Lesions of subepithelial tumors, adenocarcinoma, and adenoma were excluded. Difficult lesions were defined as ESD requiring a long procedure time (≥120 min), perforation development, piecemeal resection, or discontinued ESD. In the present study, the clinical factors were assessed to identify the technical difficulty of ESD using univariate and multivariate analyses. Results: Among 1708 lesions treated with esophageal ESD, eight subepithelial tumors, 44 adenocarcinomas, and two adenomas were excluded. Finally, 1505 patients with 1654 lesions were analyzed, and 217 patients with 217 lesions (13.1%) were classified as patients with difficult lesions. In multivariate analysis, the predictive factors associated with the technical difficulty of ESD were as follows: tumors with varices, tumors with diverticulum, antiplatelet use (discontinued), circumference of tumor (≥1/2), preoperative tumor size ≥30 mm, trainee, and nonhigh‐volume center. Conclusion: This multicenter retrospective study identified the predictive factors associated with the technical difficulty of ESD for ESCC with varied backgrounds and factors. [ABSTRACT FROM AUTHOR]

Introduction: Favorable long-term outcomes of endoscopic submucosal dissection (ESD) for early remnant gastric cancer (ERGC) have been reported in single-center studies from advanced institutions. However, no studies have examined the long-term outcomes using a multicenter database. This study aimed to investigate the long-term outcomes of the aforementioned approach using a large multicenter database. Methods: This retrospective multicenter cohort study included 242 cases with 256 lesions that underwent ESD for ERGC between April 2009 and March 2019 across 12 centers. We investigated the long-term outcomes of these patients with the Kaplan-Meier method, and the relationship between curability, additional treatment, or hospital category, and the survival time was evaluated using the log-rank test. Results: During the median follow-up period of 48.4 months, the 5-year overall survival rate was 81.3%, and the 5-year gastric cancer-specific survival rate was 98.1%. The survival time of patients of endoscopic curability (eCura) C-2 without additional surgery was significantly shorter than the corresponding of patients of eCura A/B/C-1 and eCura C-2 with additional surgery. There was no significant difference in either overall survival or gastric cancer-specific survival rate between the high-volume and non-high-volume hospitals. Conclusion: The gastric cancer-specific survival of ESD for ERGC using a multicenter database was favorable. ESD for ERGC is widely applicable regardless of the hospital case volume. Management in accordance with the latest guidelines will lead to long-term survival. [ABSTRACT FROM AUTHOR]

Objectives: Three subcategories of high‐risk flat and depressed lesions (FDLs), laterally spreading tumors non‐granular type (LST‐NG), depressed lesions, and large sessile serrated lesions (SSLs), are highly attributable to post‐colonoscopy colorectal cancer (CRC). Efficient and organized educational programs on detecting high‐risk FDLs are lacking. We aimed to explore whether a web‐based educational intervention with training on FIND clues (fold deformation, intensive stool/mucus attachment, no vessel visibility, and demarcated reddish area) may improve the ability to detect high‐risk FDLs. Methods: This was an international web‐based randomized control trial that enrolled non‐expert endoscopists in 13 Asian countries. The participants were randomized into either education or non‐education group. All participants took the pre‐test and post‐test to read 60 endoscopic images (40 high‐risk FDLs, five polypoid, 15 no lesions) and answered whether there was a lesion. Only the education group received a self‐education program (video and training questions and answers) between the tests. The primary outcome was a detection rate of high‐risk FDLs. Results: In total, 284 participants were randomized. After excluding non‐responders, the final data analyses were based on 139 participants in the education group and 130 in the non‐education group. The detection rate of high‐risk FDLs in the education group significantly improved by 14.7% (66.6–81.3%) compared with −0.8% (70.8–70.0%) in the non‐education group. Similarly, the detection rate of LST‐NG, depressed lesions, and large SSLs significantly increased only in the education group by 12.7%, 12.0%, and 21.6%, respectively. Conclusion: Short self‐education focusing on detecting high‐risk FDLs was effective for Asian non‐expert endoscopists. (UMIN000042348). [ABSTRACT FROM AUTHOR]

Artificial Intelligence (ai) systems are precious support for decision-making, with many applications also in the medical domain. The interaction between mds and ai enjoys a renewed interest following the increased possibilities of deep learning devices. However, we still have limited evidence-based knowledge of the context, design, and psychological mechanisms that craft an optimal human–ai collaboration. In this multicentric study, 21 endoscopists reviewed 504 videos of lesions prospectively acquired from real colonoscopies. They were asked to provide an optical diagnosis with and without the assistance of an ai support system. Endoscopists were influenced by ai ( O R = 3.05 ), but not erratically: they followed the ai advice more when it was correct ( O R = 3.48 ) than incorrect ( O R = 1.85 ). Endoscopists achieved this outcome through a weighted integration of their and the ai opinions, considering the case-by-case estimations of the two reliabilities. This Bayesian-like rational behavior allowed the human–ai hybrid team to outperform both agents taken alone. We discuss the features of the human–ai interaction that determined this favorable outcome. [ABSTRACT FROM AUTHOR]

Accurate in-vivo optical characterization of colorectal polyps is key to select the optimal treatment regimen during colonoscopy. However, reported accuracies vary widely among endoscopists. We developed a novel intelligent medical device able to seamlessly operate in real-time using conventional white light (WL) endoscopy video stream without virtual chromoendoscopy (blue light, BL). In this work, we evaluated the standalone performance of this computer-aided diagnosis device (CADx) on a prospectively acquired dataset of unaltered colonoscopy videos. An international group of endoscopists performed optical characterization of each polyp acquired in a prospective study, blinded to both histology and CADx result, by means of an online platform enabling careful video assessment. Colorectal polyps were categorized by reviewers, subdivided into 10 experts and 11 non-experts endoscopists, and by the CADx as either "adenoma" or "non-adenoma". A total of 513 polyps from 165 patients were assessed. CADx accuracy in WL was found comparable to the accuracy of expert endoscopists (CADxWL/Exp; OR 1.211 [0.766–1.915]) using histopathology as the reference standard. Moreover, CADx accuracy in WL was found superior to the accuracy of non-expert endoscopists (CADxWL/NonExp; OR 1.875 [1.191–2.953]), and CADx accuracy in BL was found comparable to it (CADxBL/CADxWL; OR 0.886 [0.612–1.282]). The proposed intelligent device shows the potential to support non-expert endoscopists in systematically reaching the performances of expert endoscopists in optical characterization. [ABSTRACT FROM AUTHOR]

Background and Aim: Accurate polyp size estimation is essential in deciding the therapeutic strategy of colorectal polyps and endoscopic surveillance intervals. However, many endoscopists frequently make incorrect size estimations without being aware of their errors. This cross‐sectional study aimed to clarify the characteristics of endoscopists associated with inaccurate estimation. Methods: We previously conducted a web trial involving 261 endoscopists in 51 institutions in Japan to assess their ability to estimate polyp size. Participants answered questions about polyp size using visual estimates in a test involving images of 30 polyps. Here, we investigated the relationships between inaccurate size estimation and the backgrounds of participants. The rates of overestimation and underestimation of polyp size were also compared to clarify any trends in the answers of participants with low accuracy (< 50%). Results: Multivariable logistic regression analysis revealed that the number of colonoscopic procedures in the past year was the only factor associated with a low accuracy of polyp size estimation (odds ratio 0.750, 95% confidence interval 0.609–0.925; P = 0.007). Endoscopists with low accuracy had a greater tendency to overestimate polyp size (42.3% overestimation and 21.2% underestimation, P < 0.001) compared with other endoscopists (16.6% overestimation and 17.9% underestimation, P = 0.951). Conclusions: Endoscopists with limited experience of colonoscopy in the past year were more likely to make frequent errors in size estimation. Furthermore, endoscopists making inaccurate size estimations had a propensity to overestimate polyp size. [ABSTRACT FROM AUTHOR]