Introduction

Anxiety is a common and significant problem in patients who need to undergo colonoscopy^[1]. ​The efficacy of mindfulness-based stress reduction (MBSR) in alleviating anxiety during the rehabilitation of chronic disease patients has been well-documented^[2]. However, limited evidence exists on the application of brief MBSR in patients with preoperative anxiety undergoing colonic endoscopic submucosal dissection (ESD) and its potential effects on bispectral index (BIS).

Results & Findings

A total of 120 patients scheduled for colonoscopy-assisted colonic ESD at the First Affiliated Hospital of Zhengzhou University from January 2024 to December 2024 were enrolled （Approval No.2024-KY-1063-001）. Patients were randomly divided into two groups (n=60) using a random number table: the brief MBSR group (Group M) and the control group (Group C).
Compared with Group C, Group M exhibited significantly lower APAIS scores (21.28 ± 4.53 vs. 12.36 ± 2.90), reduced BIS values (96.42 ± 10.03 vs. 73.86 ± 3.60), and slower heart rates (HR: 85.52 ± 11.78 vs. 64.22 ± 4.54) at both T1 and T2. At T3, Group M also demonstrated lower APAIS scores (16.90 ± 1.78 vs. 15.30 ± 3.46) and higher patient satisfaction scores (10.00 ± 0.00 vs. 7.94 ± 0.87) (P < 0.05). No statistically significant differences were observed between the groups in SBP, DBP,MAP, postoperative adverse events, or PACU recovery time at any time points (P > 0.05).

Summary & Discussion

Brief Mindfulness-Based Stress Reduction (MBSR) reduces Amsterdam Preoperative Anxiety and Information Scale (APAIS) scores. The underlying mechanism involves enhancing individuals' awareness and acceptance of the present moment^[3], modulating negative emotional responses, and elevating mindfulness levels, thereby alleviating preoperative anxiety.
MBSR reduces the BIS, and the proposed mechanism may involve a shift in dominant EEG activity from beta waves (associated with wakefulness and focused attention, BIS range 85–100) to alpha waves (linked to relaxation and closed-eye states, BIS range 65–85, median 70) and theta waves (observed during light sleep and REM sleep). This aligns with prior studies demonstrating that MBSR enhances alpha and theta wave activity in specific brain regions^[4].
Brief Mindfulness-Based Stress Reduction (MBSR) significantly improved patient satisfaction. By replacing preoperative negative emotions such as tension and anxiety with mindful awareness, the intervention reduced anxiety-related adverse reactions[2]., enhanced procedural comfort and treatment adherence, and fostered a more positive humanistic care experience. These findings suggest that short-term MBSR serves as a valuable psychological adjunct to optimize patient-centered outcomes in clinical settings.

Conclusion

Brief MBSR effectively alleviated preoperative anxiety in patients undergoing colonic ESD, modulated the spectral components and neural oscillatory activity of EEG waves, and reduced BIS values.

References

[1]Chen YS, Feng GH, Yue QQ, Wang YF, Liu M, Zhao KH, Tang T, Huang MT, Yi WT, Yan HL, Yan JH, Zeng Y. Effects of non-pharmacological interventions on anxiety in patients undergoing colonoscopy: A network meta-analysis of randomized controlled trials. J Psychosom Res. 2025 Apr;191:112065. doi: 10.1016/j.jpsychores.2025.112065. Epub 2025 Feb 19. PMID: 40043571.
[2]Xu L, Guan A, Huang Y. Effects of online mindfulness-based interventions on mental and physical health outcomes in cancer patients: A systematic review and meta-analysis of randomized controlled trials. Medicine (Baltimore). 2025 Mar 21;104(12):e41870. doi: 10.1097/MD.0000000000041870. PMID: 40128036; PMCID: PMC11936609.
[3]Reilly A, Sharif A, Bhagra O, Dominari A, Katsos K, Nathani KR, Johnson SE, Bydon M. Evaluation of mindfulness-based interventions for pain, anxiety, and depression in spinal cord injury patients: A systematic review and meta-analysis. Clin Neurol Neurosurg. 2025 Apr;251:108839. doi: 10.1016/j.clineuro.2025.108839. Epub 2025 Mar 10. PMID: 40080944.
[4]Lazarou I, Oikonomou VP, Mpaltadoros L, Grammatikopoulou M, Alepopoulos V, Stavropoulos TG, Bezerianos A, Nikolopoulos S, Kompatsiaris I, Tsolaki M; RADAR-AD Consortium. Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study. Front Aging Neurosci. 2023 May 30;15:1167410. doi: 10.3389/fnagi.2023.1167410. PMID: 37388185; PMCID: PMC10306118.

Disclosure

The authors disclose no conflicts.

Introduction

In colorectal epithelial neoplasms, lesions classified as type 2B according to the Japan Narrow Band Imaging (NBI) Expert Team classification (JNET), which are characterized by irregular microsurface or microvascular patterns, are often difficult to diagnose accurately using NBI magnifying endoscopy (ME) alone. Therefore, supplementary pit pattern diagnosis using crystal violet (CV)-stained ME (CV-ME) is recommended. However, CV is potentially carcinogenic, and CV-ME is relatively complex and time-consuming. Acetic acid (AA)-enhanced NBI ME (ANBI-ME) has been proposed as a simpler and safer alternative. Based on our previous study identifying 4.5% AA as the optimal concentration[1], this study prospectively evaluated the diagnostic utility of 4.5% ANBI-ME as a substitute for CV-ME (UMIN registration number: 00045621).

Aims & Methods

From October 2021 to March 2024, colorectal lesions classified as JNET type 2B or 3 during colonoscopy were prospectively enrolled until 300 cases were included. Each lesion underwent ANBI-ME with 4.5% AA, followed by CV-ME. The area of suspected deepest invasion was selected, and one representative image from ANBI-ME and one from CV-ME were independently assessed by two expert endoscopists blinded to histopathology. Intermethod and interobserver agreement were evaluated using Cohen’s weighted kappa. Diagnostic accuracy for each modality was calculated using the individual and consensus diagnoses of the two experts (McNemar’s test). AA whitening duration (AD), representing a reversible mucosal reaction, was measured during ANBI-ME and analyzed by histological depth (low-grade dysplasia [LGD], high-grade dysplasia [HGD], superficial submucosal invasive carcinoma [SMs], and deep submucosal invasive carcinoma [SMd]) using Kaplan–Meier analysis and the log-rank test.

Results

After excluding four unresected lesions, 296 lesions were analyzed. Median lesion size was 18 mm. Locations included the cecum (30), ascending colon (47), transverse colon (69), descending colon (13), sigmoid colon (73), and rectum (64); 122 lesions were elevated and 174 flat. Histological diagnosis included 77 LGD, 145 HGD, 18 SMs, and 56 SMd. Good agreement was observed between modalities (κ = 0.65 and 0.62) and between observers (κ = 0.78 for ANBI-ME, κ = 0.66 for CV-ME). Consensus was reached in 216 ANBI-ME and 192 CV-ME cases. Diagnostic accuracy was significantly higher with ANBI-ME than CV-ME for both observers (81% vs. 76%, p = 0.028; 75% vs. 69%, p = 0.025). Among consensus cases, ANBI-ME also showed higher accuracy (66% vs. 57%, p < 0.01). Median AD (in seconds) was 52 for LGD, 80 for HGD, 132 for SMs, and 107 for SMd, with a significantly shorter duration observed in LGD (p < 0.001).

Conclusion

ANBI-ME demonstrated diagnostic performance equivalent to or superior to CV-ME for colorectal lesions classified as JNET type 2B or 3. In addition, AA whitening duration (AD) may complement the assessment of histological depth of invasion.

References

[1]. Shimizu T, Yamagata T, Kanno Y, et al. A single-center pilot study on the efficacy and safety of acetic acid-enhanced magnifying endoscopy with narrow-band imaging for diagnosis of colorectal epithelial neoplasms. Gastrointest Endosc. 2025;101(2):416-424.

Introduction

Deep learning systems in gastrointestinal endoscopy are traditionally pretrained on large, diverse datasets comprising generic, non-medical images before being trained on scarce endoscopic data. Foundation models are models pretrained based on domain-specific datasets. For endoscopy, foundation models require large datasets of general endoscopic images. Yet datasets for developing such models remain limited. In this study, we present GastroNet-5M, a dataset comprising 4,820,653 endoscopic images of approximately 500,000 procedures.

Aims & Methods

GastroNet-5M is composed of anonymized endoscopic images collected from eight Dutch hospitals between 2012 and 2020. Using a self-supervised learning approach, this dataset enabled the development of a foundation model for various endoscopic AI applications. In this study, we compared GastroNet-5M-pretrained models against current state-of-the-art models with traditional pretraining approaches and all publicly available endoscopic foundation models.
We evaluated diagnostic performance on 9 classification and 9 segmentation tasks, including Barrett’s neoplasia detection, colorectal polyp characterization, and gastric cancer invasion depth prediction. All models were trained from scratch for each task. Data efficiency was assessed by repeating all classification tasks with progressively smaller training sets (i.e. 100%, 50%, 25%, 10% and 5%). Robustness was evaluated across 12 datasets reflecting data heterogeneity such as variation in endoscope manufacturer, imaging modality (e.g., virtual chromoendoscopy), and image quality.

Results

GastroNet-5M-pretrained models outperformed all benchmarks in 8 of 9 classification tasks, with an average AUC improvement of 6.8% (Table 1). For segmentation, they achieved higher Dice scores compared to all other models across all 9 tasks, with an average gain of 15.4%. In data efficiency experiments, GastroNet-5M models achieved the highest AUC in 5 of 9 tasks when training data was limited, while no other model led in more than one. In robustness testing, they outperformed other models in 8 of 12 tasks evaluating heterogeneous data conditions.

Table 1. Area-Under-the-Curve scores of the GastroNet-5M-pretrained model and benchmark models for all classification tasks.

Conclusion

GastroNet-5M, a multicenter dataset of over 5 million unlabeled endoscopic images, offers a valuable resource for pretraining deep learning models in endoscopy. The use of GastroNet-5M enhances diagnostic accuracy, reduces the need for scarce application-specific endoscopic imagery, and improves robustness of endoscopic AI systems to the inevitable data heterogeneity in clinical practice. GastroNet-5M is publicly accessible for further research and development.

References

1. Sanderson E, Matuszewski BJ. arXiv preprint arXiv:2401.06278. 2024.
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14. van der Zander QEW, Schreuder RM, Fonollà R, et al. Endoscopy. 2021.
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Introduction

Since 2029 national curricula for sedation and emergency management in endoscopy has established for endoscopy staff. NAPS are trained in three-day courses. After a baseline assessment in 2013, the effect of the training was evaluated in a survey in 2018.

Results & Findings

The questionnaire was completed by 356 endoscopy departments (95% in hospitals, 6% in private practice).

• Most departments operate in a multidisciplinary manner (85% gastroenterology, 59% TEE, 13% cardiology, 1.12% urology).
• In 52% of departments, 100% of staff have been trained, while 30% have trained 75-100% of staff. Refresher courses are completed every 2-5 years by 77% of units, while annual resuscitation courses are established in 93% od units.
• 98% have examination rooms equipped with BB, pulse oximeter, ECG, and oxygen supply. The second suction is available in 80%, and capnography in 9%. 83% have their own recovery room, 16% use other recovery rooms.
• ASA classification is used in 80% of unit for risk assessment, while Mallampati score is used in 7% only. 38% developed department specific scores. 63% perform the sign-in for all patients, 16% for 75-100% of patients. Only 10% of departments never perform a sign-in.
• 35% of units perform team-time-out (TTO) for all patients, 11% for 75-100% of patients. Only 26% of departments never use TTO.
• In 47% of departments, a dedicated person for patient monitoring and sedation is available. 30% have this person in 75-100% of patients, and 14% have this person in 25-50% of cases.
• Propofol mono sedation by bolus application is used in 88% of units, TCI in 17% of units, combination Propofol and Midazolam is used in 27%.
• In 77% of units, inpatients and outpatient are equally monitored in the recovery area while 21% of units only use the recovery area for outpatients.
• In 73% of units, physicians discharge the patient, in 12% nurses discharge patients.
• In 80% of departments, patients are only allowed to leave the endoscopy with an accompanying person.
• 70% of departments document all complications, but only 42% evaluate the complication rate statistically.
• 42% of units reported to have no problems to establish all requirements for sedation and patient monitoring. 37% reported about staff shortage. 12% could not find new staff, 25% reported about financial problems. 44% reported about resistance in their own department or with hospital management to establish improvements.

Summary & Discussion

• Comparing data from 2013, 2018 and 2024, improvements could be identified in the establishment of riss assessment by using ASA Score and individual checklists, Malampati score is still not well-known. The establishment of TTO increased from 20 to 35% in all patients, but still needs to be improved.
• The availability of a sedating person remains unchanged with 40 to 47% in all patients and 30% in 75-100% of patients. The recovery situation remains unchanged.

Conclusion

Staff shortage and resistance within the own team are the main challenges when establishing safe sedation and patient monitoring in Endoscopy.

Disclosure

no conflict of interest

Introduction

Lymphocytes inhibit the progression of hepatocellular carcinoma (HCC) through immune surveillance within an immunosuppressive microenvironment. Reduced lymphocyte counts, often associated with systemic inflammation, have been implicated in facilitating tumor progression. In contrast, elevated monocyte counts have been reported to be associated with microvascular invasion and poor prognosis in patients with HCC. Therefore, a high lymphocyte-to-monocyte ratio (LMR), calculated by dividing the lymphocyte count by the monocyte count, is considered a favorable prognostic indicator and is associated with improved clinical outcomes in patients with HCC.

Aims & Methods

We assessed the utility of the LMR in predicting the prognosis of patients with unresectable hepatocellular carcinoma who were treated with atezolizumab plus bevacizumab (Atezo/Bev). The study involved 941 patients who received Atezo/Bev treatment between September 2020 and February 2025. The median age was 74.0 years, and 754 were male. Performance status (PS) was distributed as follows: 741 patients with PS 0, 169 with PS 1, and 31 with PS ≥2. The liver background conditions were as follows: 149 patients with hepatitis B, 282 with hepatitis C, and 449 with non-hepatitis B or C (NBNC). Child-Pugh scores were distributed as follows: 522 patients with a score of 5, 254 with a score of 6, 67 with a score of 7, and 37 with a score of ≥8. The Barcelona Clinic Liver Cancer (BCLC) stages were as follows: 77 patients with stage ≤A, 317 with stage B, and 547 with stage ≥C. The median values of key biomarkers were as follows: LMR: 3.33, NLR: 2.63, AFP: 34.1 ng/mL. The median observation period was 14.3 months. NLR was included in Model 1, and LMR was incorporated in Model 2 of the multivariate analysis.

Results

The progression-free survival (PFS) was 6.8 months, and the overall survival (OS) was 23.6 months. The optimal cutoff for LMR, determined via time-dependent receiver operating characteristic (ROC) analysis based on median OS, was 3.6. The objective response rate (ORR) and disease control rate (DCR) were 27.3% and 76.5%, respectively. In the multivariate analysis of PFS, Model 1 identified the following factors as significant: BMI (HR: 0.98), Child-Pugh score ≥7 (HR: 1.34), BCLC stage C or higher (HR: 1.23), Log AFP (HR: 1.16), second or later treatment line (HR: 1.19). In Model 2, LMR was included as a significant factor (HR: 0.94). For OS, the following factors were identified as significant: age (HR: 1.01), Child-Pugh score ≥7 (HR: 2.09), BCLC stage C or higher (HR: 1.24), Log AFP (HR: 1.28), second or later treatment line (HR: 1.24), and NLR (HR: 1.03). The integrated discrimination improvement (IDI) for NLR and LMR at PFS (at 3 and 6 months) was 0.012 (95% CI: 0.012). The net reclassification improvement (NRI) was 0.016 (95% CI: 0.006-0.030, p<0.001) at 3 months, 0.023 (95% CI: 0.006-0.030, p<0.001) at 6 months, and 0.023 (95% CI: 0.004-0.024, p<0.001) at 12 months. The IDI for NLR and LMR at OS (12 and 24 months) was 0.027 (95% CI: 0.011-0.049, p=0.002) and 0.034 (95% CI: 0.012-0.064, p<0.001), with LMR demonstrating superior performance. The NRI for OS at 12 and 24 months was 0.036 (95% CI: 0.016-0.062, p<0.001) and 0.053 (95% CI: 0.020-0.091, p<0.001), respectively, both favoring LMR. In the time-dependent ROC analysis, the area under the curve (AUROC) was higher for LMR compared to NLR throughout the study period, with the exception of PFS at 3 months and OS at 18 months.

Conclusion

The LMR serves as a valuable biomarker for predicting prognosis in patients receiving Atezo/Bev.

Disclosure

Toshifumi Tada: lecture fees from AbbVie, AstraZeneca, Eisai, and Chugai
Atsushi Hiraoka: lecture fees from Eisai, Bayer, Eli Lilly, and Otsuka
Hidenori Toyoda: lecture fees from AbbVie, Eisai, Gilead, Terumo, and Bayer