Introduction

Advances in endoscopic techniques have increased the detection of pharyngeal and esophageal squamous cell carcinoma (SCC) during upper gastrointestinal endoscopy. Iodine staining is a useful method for the early detection of pharyngeal and esophageal SCC. However, due to the irritant nature of Lugol’s solution, its use in routine screening examinations is limited. Moreover, detailed pharyngeal observation is still challenging due to the pharyngeal reflex and anatomical factors. In recent years, the application of artificial intelligence (AI) in the diagnosis and identification of cancer through endoscopy has progressed, but its use in cancer risk prediction remains limited. In this study, we developed an AI model to predict high-risk cases of pharyngeal and esophageal SCC by identifying multiple Lugol-voiding lesions (LVLs) in the esophagus using pharyngeal background mucosa images and evaluated its diagnostic performance.

Aims & Methods

Among cases that underwent esophageal iodine staining at Cancer Institute Hospital between April 2015 and March 2021, we excluded images of patients with a history of pharyngeal surgery and those with pharyngeal SCC. After this exclusion, we obtained a dataset of 22,069 pharyngeal images from 905 cases. A total of 10,074 images from 425 cases, including white light imaging (WLI) and narrow-band imaging (NBI), were used to train the AI model. Model accuracy was validated using 4,029 images from 182 cases. We applied a Triplet Network to learn feature space and suppress overfitting. Using pre-trained features, we constructed an LVL classification model based on Efficient Net. LVLs in the esophagus were graded as follows: A, no lesions; B, 1 to 10 lesions; and C, ≥10 lesions per endoscopic view. The AI model was then evaluated using 7,966 images from 298 test cases to assess its diagnostic performance for LVL-C. Furthermore, we calculated AI-predicted scores for LVL-C among the LVL-A/B/C groups, and performed a Cox proportional hazards analysis to assess the association between pharyngeal and esophageal SCC development and background factors, including AI-based prediction of LVL-C.

Results

Among 298 test cases, the median age was 60 years, and 201 cases (67%) were male. The distribution of cases among the LVL grade was as follows: LVL-A: 144 cases, LVL-B: 41 cases, and LVL-C: 113 cases. For the test cases, the accuracy/sensitivity/specificity of LVL-C prediction using WLI images was 71.5% / 62.5% / 78.3%, respectively. Using NBI images, these were 77.7% / 91.2% / 69.1%. When both WLI and NBI images were combined, accuracy was 78.2%, sensitivity was 89.4%, and specificity was 71.4%. The mean AI-based prediction score of LVL-C was 0.27 for LVL-A, 0.57 for LVL-B, and 0.61 for LVL-C. The median follow-up period for the test cases was 80 months, during which 38 cases developed pharyngeal SCC and 83 cases developed esophageal SCC. Cox proportional hazards analysis revealed that AI-predicted LVL-C was significantly associated with the risk of pharyngeal SCC (hazard ratio :12.00, 95% CI: 1.56-92.50, p=0.02). Similarly, AI-predicted LVL-C and current alcohol intake were significantly associated with the risk of esophageal SCC (HR: 4.20, 95% CI: 1.92-9.16, p<0.01 and HR ;1.62, 95%CI 1.00-2.63, p=0.04 respectively).

Conclusion

The AI-based prediction of LVL-C showed good performance with a sensitivity of 89.4%, and it may be useful for predicting the development of both pharyngeal and esophageal SCC.

Introduction

The presence of bubbles during esophagogastroduodenoscopy (EGD) is common and may impair adequate mucosal visualization (MV).

Aims & Methods

The primary objective was to evaluate the effect of pre-endoscopic simethicone administration on mucosal visibility, using the GRACE (Gastroscopy Rate of Cleanliness Evaluation) scale. Secondary objectives included assessment of endoscopy duration, endoscopist satisfaction, and the detection rate of endoscopic findings.
This was a prospective, single-center, randomized, blinded study including patients undergoing elective EGD between December 2024 and March 2025. Patients were randomized into three groups: A (100 mg simethicone ≤10 minutes before EGD), B (100 mg simethicone >10 minutes before EGD), and C (50 mL water, placebo). All received a total volume of 50 mL. Patients with gastroparesis, achalasia, or prior gastrointestinal surgery were excluded. MV was assessed using the GRACE scale (validated in 2024), which scores each segment (esophagus, stomach, duodenum) from 0 to 3 based on bubble quantity, resulting in a total score from 0 (inadequate) to 9 (excellent). Endoscopist satisfaction was subjectively assessed on a scale from 0 (not satisfied) to 10 (highly satisfied).

Results

A total of 82 patients were included (18 in group A, 34 in group B, and 30 in group C). Fifty-two patients received 100 mg of simethicone and 30 received placebo. Median simethicone administration time was 8 minutes in group A and 19 minutes in group B. Simethicone significantly improved MV compared to placebo (mean GRACE score: 7.62±1.7 vs 5.83±1.7; p<0.001), with significant improvements in all segments (esophagus: 2.65 vs 2.03, p<0.001; stomach: 2.21 vs 1.63, p=0.002; duodenum: 2.69 vs 2.17, p=0.001). A very weak negative correlation was found between GRACE score and simethicone timing (r = -0.058; p = 0.685). Median endoscopist satisfaction was higher in the simethicone group (8 vs 7; p=0.001), and strongly correlated with total GRACE score (r = 0.855; p<0.001). No significant differences were observed in endoscopy duration (7 vs 6 minutes; p=0.800) or diagnostic yield (p=0.416).

Conclusion

Pre-endoscopic administration of simethicone significantly improved mucosal visibility across all upper GI segments, supporting its routine use in clinical practice. The GRACE scale is a useful and objective tool that correlates strongly with subjective endoscopist satisfaction.

References

Esposito G, Dilaghi E, Costa-Santos C, Ligato I, Annibale B, Dinis-Ribeiro M, Areia M; GRACE Investigators. The Gastroscopy RAte of Cleanliness Evaluation (GRACE) Scale: an international reliability and validation study. Endoscopy. 2025 Apr;57(4):312-320. doi: 10.1055/a-2422-0856. Epub 2024 Sep 25. Erratum in: Endoscopy. 2025 Apr;57(4):C2. doi: 10.1055/a-2545-0228. PMID: 39321961
Manfredi G, Bertè R, Iiritano E, Alicante S, Londoni C, Brambilla G, Romeo S, Menozzi F, Griffanti P, Brandi G, Moreschi O, Pezzilli R, Zullo A, Buscarini E. Premedication with simethicone and N-acetylcysteine for improving mucosal visibility during upper gastrointestinal endoscopy in a Western population. Endosc Int Open. 2021 Feb;9(2):E190-E194. doi: 10.1055/a-1315-0114. Epub 2021 Jan 25. PMID: 33532557; PMCID: PMC7834924.

Introduction

Gastric cancer is one of the most common and lethal malignancies worldwide¹. A recognized independent risk factor for the development of this neoplasm is the presence of moderate-to-severe chronic atrophic gastritis (OLGA stage III-IV)^2,3.
In Italy regions with varying epidemiology for gastric cancer coexist. Notably, the Po Valley area, encompassing the provinces of Cremona and Mantua, is a high-risk region, with a standardized incidence rate of 32.2 cases per 100,000 men and 15.9 cases per 100,000 women⁴.

Aims & Methods

The present single-center retrospective observational study aims to evaluate the correlation between the incidence, over a period of approximately 10 years, of dysplastic and neoplastic lesions amenable to endoscopic resection and OLGA staging and other recognized risk factors for gastric cancer in this high-risk population.
We retrospectively analyzed all mucosal resections (EMR), submucosal dissections (ESD), and hybrid resections (Hybrid EMR/ESD) performed at our hospital between December 2014 and September 2024 for visible gastric lesions identified as low-grade dysplasia (LGD) or high-grade dysplasia (HGD) in pre-resection biopsies. For each patient, we collected demographic data, information on risk factors for gastric neoplasia, pre- and post-resection histology and details related to the endoscopic resection procedure. High Definition Chromo-Endoscopy (HD-CE) with at least 5 guided biopsies from antrum, incisura and corpus were performed concurrently with biopsy sampling of visible lesions and all specimens underwent to a second-look pathological examination.

Results

A total of 66 patients (36 males and 30 females) with a mean age of 74.7 years were included in the study. Pre-resection biopsies revealed low-grade dysplasia (LGD) in 62% of cases and high-grade dysplasia (HGD) in the remaining 38%. Forty-two patients underwent ESD, 14 EMR and 10 Hybrid EMR/ESD. However, in 3 patients the ESD procedure was discontinued due to massive intra-procedural bleeding, perforation and evidence of deep infiltration involving the muscularis propria. Examination of the resected specimens identified 29 lesions as LGD (44%), 17 as HGD (26%), 2 as intramucosal adenocarcinomas (3%), 14 as pT1a adenocarcinomas (21%), and 4 as pT1b adenocarcinomas (6%). Regarding risk factors: 9 patients (14%) had a first-degree family history of gastric neoplasia, while 16 patients (24%) were affected by Helicobacter pylori at the time the lesion was identified. The more interesting finding comes from the pre-resection OLGA staging: 4 patients had no gastric mucosal atrophy (OLGA 0), and 35 patients had early-stage chronic atrophic gastritis (15 OLGA I and 20 OLGA II). Among the remaining patients, 23 presented with OLGA stage III, and 4 with OLGA stage IV. Therefore, 59% of patients had an OLGA staging of II or lower at the time of the onset of the dysplastic or neoplastic lesion.

Conclusion

Our experience confirms what has already been observed in Asian countries: traditional risk factors for gastric neoplasia are insufficient in high-risk areas to identify the population that might benefit from short-term endoscopic follow-up.
These findings further support the statement included in the recently published update of the ESGE guidelines on the management of epithelial precancerous conditions and early neoplasia of the stomach (MAPS III), highlighting the need for periodic screening in high-risk populations regardless of additional risk factors⁵.

References

1. Smyth EC, Nilsson M, Grabsch HI, van Grieken NC, Lordick F. Gastric cancer. Lancet. 2020;396(10251):635-648. doi:10.1016/S0140-6736(20)31288-5
2. Rugge M, de Boni M, Pennelli G, et al. Gastritis OLGA-staging and gastric cancer risk: a twelve-year clinico-pathological follow-up study. Aliment Pharmacol Ther. 2010;31(10):1104-1111. doi:10.1111/j.1365-2036.2010.04277.x
3. Yue H, Shan L, Bin L. The significance of OLGA and OLGIM staging systems in the risk assessment of gastric cancer: a systematic review and meta-analysis. Gastric Cancer. 2018;21(4):579-587. doi:10.1007/s10120-018-0812-3
4. Val Padana Cancer Registry, ATS (Health Protection Agency) Val Padana, https://www.ats-valpadana.it/documents/1654672/64558781/Stomaco.pdf/3a88e15f-a32e-9344-a748-fdfa71f138ea
5. Dinis-Ribeiro M, Libânio D, Uchima H, et al. Management of epithelial precancerous conditions and early neoplasia of the stomach (MAPS III): European Society of Gastrointestinal Endoscopy (ESGE), European Helicobacter and Microbiota Study Group (EHMSG) and European Society of Pathology (ESP) Guideline update 2025. Endoscopy. 2025;57(5):504-554. doi:10.1055/a-2529-5025

Introduction

Burnout is an increasingly recognised occupational hazard that negatively affects clinicians' well-being, patient safety and the sustainability of healthcare systems. It is characterised by emotional exhaustion, depersonalisation, and a sense of low personal accomplishment. In this systematic review and meta-analysis, we aimed to estimate the global prevalence of burnout in gastroenterology, hepatology and endoscopy.

Aims & Methods

We searched MEDLINE, Embase, Scopus and PsycINFO, from their inception to November 2024, for studies reporting the prevalence of burnout among gastroenterologists, hepatologists and endoscopists. The primary outcome was the pooled prevalence of burnout. The secondary outcomes included the prevalence of emotional exhaustion, depersonalisation, the sense of low personal accomplishment, and gender-related differences in burnout.

Results

A total of 22 studies comprising 8,124 participants were included. The pooled prevalence of burnout was 45% (95% CI, 37% - 54%), with significant variability observed across different geographical regions, assessment tools and definitions of burnout. The pooled prevalence of emotional exhaustion was 31% (95% CI, 22% - 40%), depersonalisation was 23% (95% CI, 16% - 31%), and low sense of personal accomplishment was 25% (95% CI, 10% - 40%). Female gastroenterologists were more likely to experience burnout than males (OR 1.53; 95% CI, 1.16 – 2.01; p<0.001).

Conclusion

Almost half of gastroenterologists and endoscopists experience burnout, with females being disproportionately affected. These findings highlight the need for urgent actions to address burnout and its contributing factors, including gender disparities.

Introduction

Artificial intelligence (AI) is playing an increasingly prominent role in gastrointestinal endoscopy, particularly in enhancing real-time lesion detection during colonoscopy. This study evaluates the impact of an advanced AI-assisted detection system on the Adenoma Detection Rate (ADR), Adenomas per Colonoscopy (APC), and predictive performance, comparing outcomes across endoscopists with different levels of experience.

Aims & Methods

Three endoscopists participated in the study: two with limited experience (Physicians A and B) and one expert (Physician C). A total of 720 colonoscopies were analyzed, with 400 procedures performed using AI assistance and 320 without, evenly distributed among the three operators.
Patients included were between 40 and 75 years of age and underwent colonoscopy either as a screening examination or following a positive fecal occult blood test. Exclusion criteria comprised a history of inflammatory bowel disease (IBD), hereditary polyposis syndromes, major colorectal surgery, or inadequate bowel preparation. For each procedure, data were collected on ADR, APC, the predictive accuracy of the AI system, and retraction time (from cecum to anus).

Results

The use of AI resulted in a marked and consistent improvement in all primary performance indicators across all three endoscopists.
In terms of ADR, Physician A improved from 23.8% without AI to 29.7% with AI; Physician B from 26.9% to 31.6%; and Physician C from 34.7% to 36.6%. Similarly, the APC index increased from 0.52 to 0.63 for Physician A, from 0.55 to 0.65 for Physician B, and from 0.64 to 0.73 for Physician C.
The AI system demonstrated high predictive accuracy across all operators, with no false positives recorded for polyps ≥4 mm in size. Prediction rates were 87.9% for Physician A, 89% for Physician B, and 92% for Physician C, confirming the device’s reliability in supporting polyp identification during real-time examination. Retraction times were slightly prolonged with AI usage: 8.3 minutes vs 7.5 for Physician A, 8.7 vs 7.4 for Physician B, and 8.8 vs 8.0 for Physician C. However, these differences did not reach statistical significance, indicating that AI support did not meaningfully affect procedural efficiency.

Conclusion

The integration of AI into colonoscopy workflows significantly improved both ADR and APC, with the most substantial impact observed in less experienced endoscopists. Physicians A and B, who initially showed suboptimal detection metrics, achieved levels of quality comparable to those of the expert operator in the absence of AI, highlighting AI’s value as a tool for bridging the gap in operator performance. The high predictive reliability of the system—particularly for clinically relevant lesions—and the absence of false positives ≥4 mm further support its clinical utility. Although retraction times increased slightly with AI, this change was not statistically significant, suggesting that the diagnostic advantages were not offset by decreased procedural efficiency. Overall, AI proves to be a valuable and scalable solution to enhance adenoma detection, support clinical training, and promote uniform quality standards in colorectal cancer screening.

References

1.Antonelli, G., Gkolfakis, P., Tziatzios, G., Papanikolaou, I. S., Triantafyllou, K., & Hassan, C. (2020). Artificial intelligence-aided colonoscopy: Recent developments and future perspectives. World journal of gastroenterology, 26(47), 7436–7443.
2.Hassan, C., Balsamo, G., Lorenzetti, R., Zullo, A., & Antonelli, G. (2022). Artificial Intelligence Allows Leaving-In-Situ Colorectal Polyps. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association, 20(11), 2505–2513.e4
3.Houwen, B. B. S. L., Hassan, C., Coupé, V. M. H., Greuter, M. J. E., Hazewinkel, Y., Vleugels, J. L. A., Antonelli, G., Bustamante-Balén, M., Coron, E., Cortas, G. A., Dinis-Ribeiro, M., Dobru, D. E., East, J. E., Iacucci, M., Jover, R., Kuvaev, R., Neumann, H., Pellisé, M., Puig, I., Rutter, M. D., … Dekker, E. (2022). Definition of competence standards for optical diagnosis of diminutive colorectal polyps: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement. Endoscopy, 54(1), 88–99.