Vascular density of superficial esophageal squamous cell carcinoma determined by direct observation of resected specimen using narrow band imaging with magnifying endoscopy

Endoscopic submucosal dissection for superficial esophageal cancer in the remnant esophagus after esophagectomy

Treatment of esophageal cancer in the remnant esophagus after esophagectomy is highly invasive, therefore, early detection and minimally invasive treatment are considered necessary. Consequently, we aimed to clarify the safety and efficacy of endoscopic submucosal dissection (ESD) for residual esophageal cancer compared to that for esophageal cancer in a normal cervical esophagus. This study involved 47 patients with 59 residual esophageal cancers and 92 patients with 107 cervical esophageal cancers in normal esophagus who underwent ESD between January 2008 and December 2023. Their clinicopathological findings and long-term outcomes were retrospectively collected and evaluated. The median tumor diameter was 13 mm, and the median procedure time was 31 minutes in remnant esophagus group, with no significant difference between the two groups. No serious complications such as perforation, massive intraoperative bleeding, and pneumonia were observed in the remnant group, except for one case of postoperative bleeding. The rates of complete resection and disease specific survival were not significantly different between two groups, with complete resection rate of 86.4% and 5-year disease-specific survival rate of 95.7% in the remnant esophagus group. No local recurrence was observed during the median observation period of 43 months in the remnant esophagus group. ESD for superficial cancer of the remnant esophagus showed a high complete resection rate without serious complications and good local-regional control with no evidence of local recurrence. This indicates that ESD is a safe and useful treatment for superficial cancer of the remnant esophagus.

Microvascular structural changes in esophageal squamous cell carcinoma pathology according to intrapapillary capillary loop types under magnifying endoscopy

BACKGROUND

The intrapapillary capillary loop (IPCL) characteristics, visualized using magnifying endoscopy, are commonly assessed for preoperative evaluation of the infiltration depth of esophageal squamous cell carcinoma (ESCC). Japan Esophageal Society (JES) classification is the most widely used classification. Microvascular structural changes are evaluated by magnifying endoscopy for the presence or absence of each morphological factor: tortuosity, dilatation, irregular caliber, and different shapes. However, the pathological characteristics of IPCLs have not been thoroughly investigated, especially the microvascular structures corresponding to the deepest parts of the lesions' infiltration.

AIM

To investigate differences in pathological microvascular structures of ESCC, which correspond to the deepest parts of the lesions' infiltration.

METHODS

Patients with ESCC and precancerous lesions diagnosed at Peking University Third Hospital were enrolled between January 2019 and April 2023. Patients first underwent magnified endoscopic examination, followed by endoscopic submucosal dissection or surgical treatment. Pathological images were scanned using a three-dimensional slice scanner, and the pathological structural differences in different types, according to the JES classification, were analyzed using nonparametric tests and t-tests.

RESULTS

The 35 lesions were divided into four groups according to the JES classification: A, B1, B2, and B3. Statistical analyses revealed significant differences (a P < 0.05) in the short and long calibers, area, location, and density between types A and B. Notably, there were no significant differences in these parameters between types B1 and B2 and between types B2 and B3 (P > 0.05). However, significant differences in the short calibers, long calibers, and area of IPCL were observed between types B1 and B3 (a P < 0.05); no significant differences were found in the density or location (P > 0.05).

CONCLUSION

Pathological structures of IPCLs in the deepest infiltrating regions differ among various IPCL types classified by the JES classification under magnifying endoscopy, especially between the types A and B.

Human-Like Artificial Intelligent System for Predicting Invasion Depth of Esophageal Squamous Cell Carcinoma Using Magnifying Narrow-Band Imaging Endoscopy: A Retrospective Multicenter Study

INTRODUCTION

Endoscopic evaluation is crucial for predicting the invasion depth of esophagus squamous cell carcinoma (ESCC) and selecting appropriate treatment strategies. Our study aimed to develop and validate an interpretable artificial intelligence-based invasion depth prediction system (AI-IDPS) for ESCC.

METHODS

We reviewed the PubMed for eligible studies and collected potential visual feature indices associated with invasion depth. Multicenter data comprising 5,119 narrow-band imaging magnifying endoscopy images from 581 patients with ESCC were collected from 4 hospitals between April 2016 and November 2021. Thirteen models for feature extraction and 1 model for feature fitting were developed for AI-IDPS. The efficiency of AI-IDPS was evaluated on 196 images and 33 consecutively collected videos and compared with a pure deep learning model and performance of endoscopists. A crossover study and a questionnaire survey were conducted to investigate the system's impact on endoscopists' understanding of the AI predictions.

RESULTS

AI-IDPS demonstrated the sensitivity, specificity, and accuracy of 85.7%, 86.3%, and 86.2% in image validation and 87.5%, 84%, and 84.9% in consecutively collected videos, respectively, for differentiating SM2-3 lesions. The pure deep learning model showed significantly lower sensitivity, specificity, and accuracy (83.7%, 52.1% and 60.0%, respectively). The endoscopists had significantly improved accuracy (from 79.7% to 84.9% on average, P = 0.03) and comparable sensitivity (from 37.5% to 55.4% on average, P = 0.27) and specificity (from 93.1% to 94.3% on average, P = 0.75) after AI-IDPS assistance.

DISCUSSION

Based on domain knowledge, we developed an interpretable system for predicting ESCC invasion depth. The anthropopathic approach demonstrates the potential to outperform deep learning architecture in practice.

Revising the European Society of Gastrointestinal Endoscopy (ESGE) research priorities: a research progress update

BACKGROUND

One of the aims of the European Society of Gastrointestinal Endoscopy (ESGE) is to encourage high quality endoscopic research at a European level. In 2016, the ESGE research committee published a set of research priorities. As endoscopic research is flourishing, we aimed to review the literature and determine whether endoscopic research over the last 4 years had managed to address any of our previously published priorities.

METHODS

As the previously published priorities were grouped under seven different domains, a working party with at least two European experts was created for each domain to review all the priorities under that domain. A structured review form was developed to standardize the review process. The group conducted an extensive literature search relevant to each of the priorities and then graded the priorities into three categories: (1) no longer a priority (well-designed trial, incorporated in national/international guidelines or adopted in routine clinical practice); (2) remains a priority (i. e. the above criterion was not met); (3) redefine the existing priority (i. e. the priority was too vague with the research question not clearly defined).

RESULTS

The previous ESGE research priorities document published in 2016 had 26 research priorities under seven domains. Our review of these priorities has resulted in seven priorities being removed from the list, one priority being partially removed, another seven being redefined to make them more precise, with eleven priorities remaining unchanged. This is a reflection of a rapid surge in endoscopic research, resulting in 27 % of research questions having already been answered and another 27 % requiring redefinition.

CONCLUSIONS

Our extensive review process has led to the removal of seven research priorities from the previous (2016) list, leaving 19 research priorities that have been redefined to make them more precise and relevant for researchers and funding bodies to target.

A deep learning method for delineating early gastric cancer resection margin under chromoendoscopy and white light endoscopy

BACKGROUND

Accurate delineation of cancer margins is critical for endoscopic curative resection. This study aimed to train and validate real-time fully convolutional networks for delineating the resection margin of early gastric cancer (EGC) under indigo carmine chromoendoscopy (CE) or white light endoscopy (WLE), and evaluated its performance and that of magnifying endoscopy with narrow-band imaging (ME-NBI).

METHODS

We collected CE and WLE images of EGC lesions to train fully convolutional networks ENDOANGEL. ENDOANGEL was tested both on stationary images and endoscopic submucosal dissection (ESD) videos. The accuracy and reliability of ENDOANGEL and NBI-dependent delineation were further evaluated by a novel endoscopy-pathology point-to-point marking.

RESULTS

ENDOANGEL had an accuracy of 85.7% in the CE images and 88.9% in the WLE images under an overlap ratio threshold of 0.60 in comparison with the manual markers labeled by the experts. In the ESD videos, the resection margins predicted by ENDOANGEL covered all areas of high-grade intraepithelial neoplasia and cancers. The minimum distance between the margins predicted by ENDOANGEL and the histological cancer boundary was 3.44 ± 1.45 mm which outperformed the resection margin based on ME-NBI.

CONCLUSIONS

ENDOANGEL has the potential to assist endoscopists in delineating the resection extent of EGC under CE or WLE during ESD.