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Objective: To develop and externally validate an updated artificial intelligence (AI) prediction system for stratifying the risk of lymph node metastasis (LNM) in T2 colorectal cancer (CRC)., Background: Recent technical advances allow complete local excision of T2 CRC, traditionally treated with surgical resection. Yet, the widespread adoption of this approach is hampered by the inability to stratify the risk of LNM., Methods: Data from patients with pT2 CRC undergoing surgical resection between April 2000 and May 2022 at one Japanese and one Italian center were analyzed. Primary goal was AI system development for accurate LNM prediction. Predictors encompassed 7 variables: age, sex, tumor size, tumor location, lymphovascular invasion, histologic differentiation, and carcinoembryonic antigen level. The tool's discriminating power was assessed through area under the curve, sensitivity, and specificity., Results: Out of 735 initial patients, 692 were eligible. Training and validation cohorts comprised of 492 and 200 patients, respectively. The AI model displayed an area under the curve of 0.75 in the combined validation data set. Sensitivity for LNM prediction was 97.8%, and specificity was 15.6%. The positive and the negative predictive value were 25.7% and 96%, respectively. The false negative rate was 2.2%, and the false positive was 84.4%., Conclusions: Our AI model, based on easily accessible clinical and pathologic variables, moderately predicts LNM in T2 CRC. However, the risk of false negative needs to be considered. The training of the model including more patients across western and eastern centers - differentiating between colon and rectal cancers - may improve its performance and accuracy., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background and Aim: Accurate stratification of the risk of lymph node metastasis (LNM) following endoscopic resection of submucosal invasive (T1) colorectal cancer (CRC) is imperative for determining the necessity for additional surgery. In this systematic review, we evaluated the efficacy of prediction of LNM by artificial intelligence (AI) models utilizing whole slide image (WSI) in patients with T1 CRC., Methods: In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic review was conducted through searches in PubMed (MEDLINE), Embase, and the Cochrane Library for relevant studies published up to December 2023. The inclusion criteria were studies assessing the accuracy of hematoxylin and eosin-stained WSI-based AI models for predicting LNM in patients with T1 CRC., Results: Four studies met the criteria for inclusion in this systematic review. The area under the receiver operating characteristic curve for these AI models ranged from 0.57 to 0.76. In the three studies in which AI performance was compared directly with current treatment guidelines, AI consistently exhibited a higher area under the receiver operating characteristic curve. At a fixed sensitivity of 100%, specificities ranged from 18.4% to 45.0%., Conclusions: Artificial intelligence models based on WSI can potentially address the issue of diagnostic variability between pathologists and exceed the predictive accuracy of current guidelines. However, these findings require confirmation by larger studies that incorporate external validation., (© 2024 The Author(s). Journal of Gastroenterology and Hepatology published by Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)

Submucosal invasive (T1) colorectal cancer is a significant clinical management challenge, with an estimated 10% of patients developing extraintestinal lymph node metastasis. This condition necessitates surgical resection along with lymph node dissection to achieve a curative outcome. Thus, the precise preoperative assessment of lymph node metastasis risk is crucial to guide treatment decisions after endoscopic resection. Contemporary clinical guidelines strive to identify a low-risk cohort for whom endoscopic resection will suffice, applying stringent criteria to maximize patient safety. Those failing to meet these criteria are often recommended for surgical resection, with its associated mortality risks although it may still include patients with a low risk of metastasis. In the quest to enhance the precision of preoperative lymph node metastasis risk prediction, innovative models leveraging artificial intelligence or nomograms are being developed. Nevertheless, the debate over the ideal sensitivity and specificity for such models persists, with no consensus on target metrics. This review puts forth postoperative mortality rates as a practical benchmark for the sensitivity of predictive models. We underscore the importance of this method and advocate for research to amass data on surgical mortality in T1 colorectal cancer. Establishing specific benchmarks for predictive accuracy in lymph node metastasis risk assessment will hopefully optimize the treatment of T1 colorectal cancer.

Background: Lymph node metastasis (LNM) occurs in 20-25% of patients with T2 colorectal cancer (CRC). Identification of risk factors for LNM in T2 CRC may help identify patients who are at low risk and thereby potential candidates for endoscopic full-thickness resection. We examined risk factors for LNM in T2 CRC with the goal of establishing further criteria of the indications for endoscopic resection., Methods: MEDLINE, CENTRAL, and EMBASE were systematically searched from inception to November 2023. Studies that investigated the association between the presence of LNM and the clinical and pathological factors of T2 CRC were included. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Certainty of evidence (CoE) was assessed using the GRADE approach., Results: Fourteen studies (8349 patients) were included. Overall, the proportion of LNM was 22%. The meta-analysis revealed that the presence of lymphovascular invasion (OR, 5.5; 95% CI 3.7-8.3; high CoE), high-grade tumor budding (OR, 2.4; 95% CI 1.5-3.7; moderate CoE), poor differentiation (OR, 2.2; 95% CI 1.8-2.7; moderate CoE), and female sex (OR, 1.3; 95% CI 1.1-1.7; high CoE) were associated with LNM in T2 CRC. Lymphatic invasion (OR, 5.0; 95% CI 3.3-7.6) was a stronger predictor of LNM than vascular invasion (OR, 2.4; 95% CI 2.1-2.8)., Conclusions: Lymphovascular invasion, high-grade tumor budding, poor differentiation, and female sex were risk factors for LNM in T2 CRC. Endoscopic resection of T2 CRC in patients with very low risk for LNM may become an alternative to conventional surgical resection., Trial Registration: PROSPERO, CRD42022316545., (© 2024. The Author(s) under exclusive licence to Japan Society of Clinical Oncology.)

Background and Aims: Image-enhanced endoscopy has attracted attention as a method for detecting inflammation and predicting outcomes in patients with ulcerative colitis (UC); however, the procedure requires specialist endoscopists. Artificial intelligence (AI)-assisted image-enhanced endoscopy may help nonexperts provide objective accurate predictions with the use of optical imaging. We aimed to develop a novel AI-based system using 8853 images from 167 patients with UC to diagnose "vascular-healing" and establish the role of AI-based vascular-healing for predicting the outcomes of patients with UC., Methods: This open-label prospective cohort study analyzed data for 104 patients with UC in clinical remission. Endoscopists performed colonoscopy using the AI system, which identified the target mucosa as AI-based vascular-active or vascular-healing. Mayo endoscopic subscore (MES), AI outputs, and histologic assessment were recorded for 6 colorectal segments from each patient. Patients were followed up for 12 months. Clinical relapse was defined as a partial Mayo score >2 RESULTS: The clinical relapse rate was significantly higher in the AI-based vascular-active group (23.9% [16/67]) compared with the AI-based vascular-healing group (3.0% [1/33)]; P = .01). In a subanalysis predicting clinical relapse in patients with MES ≤1, the area under the receiver operating characteristic curve for the combination of complete endoscopic remission and vascular healing (0.70) was increased compared with that for complete endoscopic remission alone (0.65)., Conclusions: AI-based vascular-healing diagnosis system may potentially be used to provide more confidence to physicians to accurately identify patients in remission of UC who would likely relapse rather than remain stable., Competing Interests: Disclosure The following authors disclosed financial relationships: Y. Maeda: grants from the Japan Society for the Promotion of Science during the conduct of the study. S. Kudo and M. Misawa: consultant and speaker fees from Olympus Corp. All of the other authors disclosed no financial relationships., (Copyright © 2024 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

Approximately 10% of submucosal invasive (T1) colorectal cancers demonstrate extraintestinal lymph node metastasis, necessitating surgical intervention with lymph node dissection. The ability to identify T1b (submucosal invasion depth ≥ 1000 µm) as a risk factor for lymph node metastasis via pre-treatment endoscopy is crucial in guiding treatment strategies. Accurately distinguishing T1b from T1a (submucosal invasion depth < 1000 µm) or dysplasia remains a significant challenge for artificial intelligence (AI) systems, which require high and consistent diagnostic capabilities. Moreover, as endoscopic therapies like endoscopic full-thickness resection and endoscopic intermuscular dissection evolve, and the focus on reducing unnecessary surgeries intensifies, the initial management of T1 colorectal cancers via endoscopic treatment is anticipated to increase. Consequently, the development of highly accurate and reliable AI systems is essential, not only for pre-treatment depth assessment but also for post-treatment risk stratification of lymph node metastasis. While such AI diagnostic systems are still under development, significant advancements are expected in the near future to improve decision-making in T1 colorectal cancer management., Competing Interests: Conflict of interest The authors (Katsuro Ichimasa, Shin-ei Kudo, Masashi Misawa, Yuki Takashina, Khay Guan Yeoh, and Hideyuki Miyachi) hereby declare no conflict of interest regarding this review article entitled “Role of the artificial intelligence in the management of T1 colorectal cancer”. No relevant disclosures., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Backgrounds and Aims: The Mayo endoscopic subscore (MES) is the most popular endoscopic disease activity measure of ulcerative colitis (UC). Artificial intelligence (AI)-assisted colonoscopy is expected to reduce diagnostic variability among endoscopists. However, no study has been conducted to ascertain whether AI-based MES assignments can help predict clinical relapse, nor has AI been verified to improve the diagnostic performance of non-specialists., Methods: This open-label, prospective cohort study enrolled 110 patients with UC in clinical remission. The AI algorithm was developed using 74713 images from 898 patients who underwent colonoscopy at three centers. Patients were followed up after colonoscopy for 12 months, and clinical relapse was defined as a partial Mayo score >2. A multi-video, multi-reader analysis involving 124 videos was conducted to determine whether the AI system reduced the diagnostic variability among six non-specialists., Results: The clinical relapse rate for patients with AI-based MES = 1 (24.5% [12/49]) was significantly higher (log-rank test, P = 0.01) than that for patients with AI-based MES = 0 (3.2% [1/31]). Relapse occurred during the 12-month follow-up period in 16.2% (13/80) of patients with AI-based MES = 0 or 1 and 50.0% (10/20) of those with AI-based MES = 2 or 3 (log-rank test, P = 0.03). Using AI resulted in better inter- and intra-observer reproducibility than endoscopists alone., Conclusions: Colonoscopy using the AI-based MES system can stratify the risk of clinical relapse in patients with UC and improve the diagnostic performance of non-specialists., (© The Author(s) 2024. Published by Oxford University Press on behalf of European Crohn’s and Colitis Organisation.)

Objectives: Lymphovascular invasion (LVI) is a critical risk factor for lymph node metastasis (LNM), which requires additional surgery after endoscopic resection of T1 colorectal cancer (CRC). However, the impact of additional staining on estimating LNM is unclear. This systematic review aimed to evaluate the impact of additional staining on determining LNM in T1 CRC., Methods: We searched five electronic databases. Outcomes were diagnostic odds ratio (DOR), assessed using hierarchical summary receiver operating characteristic curves, and interobserver agreement among pathologists for positive LVI, assessed using Kappa coefficients (κ). We performed a subgroup analysis of studies that simultaneously included a multivariable analysis for other risk factors (deep submucosal invasion, poor differentiation, and tumor budding)., Results: Among the 64 studies (18,097 patients) identified, hematoxylin-eosin (HE) and additional staining for LVI had pooled sensitivities of 0.45 (95% confidence interval [CI] 0.32-0.58) and 0.68 (95% CI 0.44-0.86), specificities of 0.88 (95% CI 0.78-0.94) and 0.76 (95% CI 0.62-0.86), and DORs of 6.26 (95% CI 3.73-10.53) and 6.47 (95% CI 3.40-12.32) for determining LNM, respectively. In multivariable analysis, the DOR of additional staining for LNM (DOR 5.95; 95% CI 2.87-12.33) was higher than that of HE staining (DOR 1.89; 95% CI 1.13-3.16) (P = 0.01). Pooled κ values were 0.37 (95% CI 0.22-0.52) and 0.62 (95% CI 0.04-0.99) for HE and additional staining for LVI, respectively., Conclusion: Additional staining for LVI may increase the DOR for LNM and interobserver agreement for positive LVI among pathologists., (© 2023 The Authors. Digestive Endoscopy published by John Wiley & Sons Australia, Ltd on behalf of Japan Gastroenterological Endoscopy Society.)

The current standard treatment for muscularis propria-invasive (T2) colorectal cancer is surgical colectomy with lymph node dissection. With the advent of new endoscopic resection techniques, such as endoscopic full-thickness resection or endoscopic intermuscular dissection, T2 colorectal cancer, with metastasis to 20%-25% of the dissected lymph nodes, may be the next candidate for endoscopic resection following submucosal-invasive (T1) colorectal cancer. We present a novel endoscopic treatment strategy for T2 colorectal cancer and suggest further study to establish evidence on oncologic and endoscopic technical safety for its clinical implementation.

Objectives: Computer-aided characterization (CADx) may be used to implement optical biopsy strategies into colonoscopy practice; however, its impact on endoscopic diagnosis remains unknown. We aimed to evaluate the additional diagnostic value of CADx when used by endoscopists for assessing colorectal polyps., Methods: This was a single-center, multicase, multireader, image-reading study using randomly extracted images of pathologically confirmed polyps resected between July 2021 and January 2022. Approved CADx that could predict two-tier classification (neoplastic or nonneoplastic) by analyzing narrow-band images of the polyps was used to obtain a CADx diagnosis. Participating endoscopists determined if the polyps were neoplastic or not and noted their confidence level using a computer-based, image-reading test. The test was conducted twice with a 4-week interval: the first test was conducted without CADx prediction and the second test with CADx prediction. Diagnostic performances for neoplasms were calculated using the pathological diagnosis as reference and performances with and without CADx prediction were compared., Results: Five hundred polyps were randomly extracted from 385 patients and diagnosed by 14 endoscopists (including seven experts). The sensitivity for neoplasia was significantly improved by referring to CADx (89.4% vs. 95.6%). CADx also had incremental effects on the negative predictive value (69.3% vs. 84.3%), overall accuracy (87.2% vs. 91.8%), and high-confidence diagnosis rate (77.4% vs. 85.8%). However, there was no significant difference in specificity (80.1% vs. 78.9%)., Conclusions: Computer-aided characterization has added diagnostic value for differentiating colorectal neoplasms and may improve the high-confidence diagnosis rate., (© 2023 Japan Gastroenterological Endoscopy Society.)

Introduction: Treatment guidelines for colorectal cancer (CRC) suggest 2 classifications for histological differentiation-highest grade and predominant. However, the optimal predictor of lymph node metastasis (LNM) in T1 CRC remains unknown. This systematic review aimed to evaluate the impact of the use of highest-grade or predominant differentiation on LNM determination in T1 CRC., Methods: The study protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO, registration number: CRD42023416971) and was published in OSF ( https://osf.io/TMAUN/ ) on April 13, 2023. We searched 5 electronic databases for studies assessing the diagnostic accuracy of highest-grade or predominant differentiation to determine LNM in T1 CRC. The outcomes were sensitivity and specificity. We simulated 100 cases with T1 CRC, with an LNM incidence of 11.2%, to calculate the differences in false positives and negatives between the highest-grade and predominant differentiations using a bootstrap method., Results: In 42 studies involving 41,290 patients, the differentiation classification had a pooled sensitivity of 0.18 (95% confidence interval [CI] 0.13-0.24) and 0.06 (95% CI 0.04-0.09) ( P < 0.0001) and specificity of 0.95 (95% CI 0.93-0.96) and 0.98 (95% CI 0.97-0.99) ( P < 0.0001) for the highest-grade and predominant differentiations, respectively. In the simulation, the differences in false positives and negatives between the highest-grade and predominant differentiations were 3.0% (range 1.6-4.4) and -1.3% (range -2.0 to -0.7), respectively., Discussion: Highest-grade differentiation may reduce the risk of misclassifying cases with LNM as negative, whereas predominant differentiation may prevent unnecessary surgeries. Further studies should examine differentiation classification using other predictive factors., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The American College of Gastroenterology.)

Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Objectives: A computer-aided detection (CAD) system was developed to support the detection of colorectal lesions by deep learning using video images of lesions and normal mucosa recorded during colonoscopy. The study's purpose was to evaluate the stand-alone performance of this device under blinded conditions., Methods: This multicenter prospective observational study was conducted at four Japanese institutions. We used 326 videos of colonoscopies recorded with patient consent at institutions in which the Ethics Committees approved the study. The sensitivity of successful detection of the CAD system was calculated using the target lesions, which were detected by adjudicators from two facilities for each lesion appearance frame; inconsistencies were settled by consensus. Successful detection was defined as display of the detection flag on the lesion for more than 0.5 s within 3 s of appearance., Results: Of the 556 target lesions from 185 cases, detection success sensitivity was 97.5% (95% confidence interval [CI] 95.8-98.5%). The "successful detection sensitivity per colonoscopy" was 93% (95% CI 88.3-95.8%). For the frame-based sensitivity, specificity, positive predictive value, and negative predictive value were 86.6% (95% CI 84.8-88.4%), 84.7% (95% CI 83.8-85.6%), 34.9% (95% CI 32.3-37.4%), and 98.2% (95% CI 97.8-98.5%), respectively., Trial Registration: University Hospital Medical Information Network (UMIN000044622)., (© 2023 Japan Gastroenterological Endoscopy Society.)

The field of artificial intelligence is rapidly evolving, and there has been an interest in its use to predict the risk of lymph node metastasis in T1 colorectal cancer. Accurately predicting lymph node invasion may result in fewer patients undergoing unnecessary surgeries; conversely, inadequate assessments will result in suboptimal oncological outcomes. This narrative review aims to summarize the current literature on deep learning for predicting the probability of lymph node metastasis in T1 colorectal cancer, highlighting areas of potential application and barriers that may limit its generalizability and clinical utility.

Objectives: Japanese guidelines include high-grade (poorly differentiated) tumors as a risk factor for lymph node metastasis (LNM) in T1 colorectal cancer (CRC). However, whether the grading is based on the least or most predominant component when the lesion consists of two or more levels of differentiation varies among institutions. This study aimed to investigate which method is optimal for assessing the risk of LNM in T1 CRC., Methods: We retrospectively evaluated 971 consecutive patients with T1 CRC who underwent initial or additional surgical resection from 2001 to 2021 at our institution. Tumor grading was divided into low-grade (well- to moderately differentiated) and high-grade based on the least or predominant differentiation analyses. We investigated the correlations between LNM and these two grading analyses., Results: LNM was present in 9.8% of patients. High-grade tumors, as determined by least differentiation analysis, accounted for 17.0%, compared to 0.8% identified by predominant differentiation analysis. A significant association with LNM was noted for the least differentiation method ( p < 0.05), while no such association was found for predominant differentiation ( p = 0.18). In multivariate logistic regression, grading based on least differentiation was an independent predictor of LNM ( p = 0.04, odds ratio 1.68, 95% confidence interval 1.00-2.83). Sensitivity and specificity for detecting LNM were 27.4% and 84.1% for least differentiation, and 2.1% and 99.3% for predominant differentiation, respectively., Conclusions: Tumor grading via least differentiation analysis proved to be a more reliable measure for assessing LNM risk in T1 CRC compared to grading by predominant differentiation., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors. DEN Open published by John Wiley & Sons Australia, Ltd on behalf of Japan Gastroenterological Endoscopy Society.)

Objectives: Lymph node metastasis (LNM) prediction for T1 colorectal cancer (CRC) is critical for determining the need for surgery after endoscopic resection because LNM occurs in 10%. We aimed to develop a novel artificial intelligence (AI) system using whole slide images (WSIs) to predict LNM., Methods: We conducted a retrospective single center study. To train and test the AI model, we included LNM status-confirmed T1 and T2 CRC between April 2001 and October 2021. These lesions were divided into two cohorts: training (T1 and T2) and testing (T1). WSIs were cropped into small patches and clustered by unsupervised K-means. The percentage of patches belonging to each cluster was calculated from each WSI. Each cluster's percentage, sex, and tumor location were extracted and learned using the random forest algorithm. We calculated the areas under the receiver operating characteristic curves (AUCs) to identify the LNM and the rate of over-surgery of the AI model and the guidelines., Results: The training cohort contained 217 T1 and 268 T2 CRCs, while 100 T1 cases (LNM-positivity 15%) were the test cohort. The AUC of the AI system for the test cohort was 0.74 (95% confidence interval [CI] 0.58-0.86), and 0.52 (95% CI 0.50-0.55) using the guidelines criteria (P = 0.0028). This AI model could reduce the 21% of over-surgery compared to the guidelines., Conclusion: We developed a pathologist-independent predictive model for LNM in T1 CRC using WSI for determination of the need for surgery after endoscopic resection., Trial Registration: UMIN Clinical Trials Registry (UMIN000046992, https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr&#95;view.cgi?recptno=R000053590)., (© 2023 Japan Gastroenterological Endoscopy Society.)

Objectives: A "resect-and-discard" strategy has been proposed for diminutive adenomas in the colorectum. However, this strategy is sometimes difficult to implement because of the lack of confidence in differentiating low-grade adenoma (LGA) from advanced lesions such as high-grade adenoma or carcinoma. To perform real-time precise diagnosis of LGA with high confidence, we assessed whether endocytoscopy (EC) diagnosis, considering normal pit-like structure (NP-sign), an excellent indicator of LGA, could have additional diagnostic potential compared with conventional modalities., Methods: All the neoplastic lesions that were observed by non-magnifying narrow-band imaging (NBI), magnifying NBI (M-NBI), magnifying pit pattern, and EC prior to pathological examination between 2005 and 2018 were retrospectively investigated. The neoplastic lesions were classified into two categories: LGA and other neoplastic lesions. We assessed the differential diagnostic ability of EC with NP-sign between LGA and other neoplastic lesions compared with that of NBI, M-NBI, pit pattern, and conventional EC in terms of sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC)., Results: A total of 1376 lesions from 1097 patients were eligible. The specificity (94.9%), accuracy (91.5%), and area under the receiver operating characteristic curve (0.95) of EC with NP-sign were significantly higher than those of NBI, M-NBI, pit pattern, and conventional EC., Conclusions: EC diagnosis with NP-sign has significantly higher diagnostic performance for predicting colorectal LGA compared with the conventional modalities and enables stratification of neoplastic lesions for "resect-and-discard" with higher confidence., Competing Interests: None., (© 2023 The Authors. DEN Open published by John Wiley & Sons Australia, Ltd on behalf of Japan Gastroenterological Endoscopy Society.)

Objectives: Advances in endoscopic technology, including magnifying and image-enhanced techniques, have been attracting increasing attention for the optical characterization of colorectal lesions. These techniques are being implemented into clinical practice as cost-effective and real-time approaches. Additionally, with the recent progress in endoscopic interventions, endoscopic resection is gaining acceptance as a treatment option in patients with ulcerative colitis (UC). Therefore, accurate preoperative characterization of lesions is now required. However, lesion characterization in patients with UC may be difficult because UC is often affected by inflammation, and it may be characterized by a distinct "bottom-up" growth pattern, and even expert endoscopists have relatively little experience with such cases. In this systematic review, we assessed the current status and limitations of the use of optical characterization of lesions in patients with UC., Methods: A literature search of online databases (MEDLINE via PubMed and CENTRAL via the Cochrane Library) was performed from 1 January 2000 to 30 November 2021., Results: The database search initially identified 748 unique articles. Finally, 25 studies were included in the systematic review: 23 focused on differentiation of neoplasia from non-neoplasia, one focused on differentiation of UC-associated neoplasia from sporadic neoplasia, and one focused on differentiation of low-grade dysplasia from high-grade dysplasia and cancer., Conclusions: Optical characterization of neoplasia in patients with UC, even using advanced endoscopic technology, is still challenging and several issues remain to be addressed. We believe that the information revealed in this review will encourage researchers to commit to the improvement of optical diagnostics for UC-associated lesions., (© 2022 Japan Gastroenterological Endoscopy Society.)

Background: Colorectal cancer (CRC) can be classified into four consensus molecular subtypes (CMS) according to genomic aberrations and gene expression profiles. CMS is expected to be useful in predicting prognosis and selecting chemotherapy regimens. However, there are still no reports on the relationship between the morphology and CMS., Methods: This retrospective study included 55 subjects with T2 CRC undergoing surgical resection, of whom 30 had the depressed type and 25 the protruded type. In the classification of the CMS, we first defined cases with deficient mismatch repair as CMS1. And then, CMS2/3 and CMS4 were classified using an online classifier developed by Trinh et al. The staining intensity of CDX2, HTR2B, FRMD6, ZEB1, and KER and the percentage contents of CDX2, FRMD6, and KER are input into the classifier to obtain automatic output classifying the specimen as CMS2/3 or CMS4., Results: According to the results yielded by the online classifier, of the 30 depressed-type cases, 15 (50%) were classified as CMS2/3 and 15 (50%) as CMS4. Of the 25 protruded-type cases, 3 (12%) were classified as CMS1 and 22 (88%) as CMS2/3. All of the T2 CRCs classified as CMS4 were depressed CRCs. More malignant pathological findings such as lymphatic invasion were associated with the depressed rather than protruded T2 CRC cases., Conclusions: Depressed-type T2 CRC had a significant association with CMS4, showing more malignant pathological findings such as lymphatic invasion than the protruded-type, which could explain the reported association between CMS4 CRC and poor prognosis., Competing Interests: The authors have declared that no competing interests exist.

Background and Aims: Because of a lack of reliable preoperative prediction of lymph node involvement in early-stage T2 colorectal cancer (CRC), surgical resection is the current standard treatment. This leads to overtreatment because only 25% of T2 CRC patients turn out to have lymph node metastasis (LNM). We assessed a novel artificial intelligence (AI) system to predict LNM in T2 CRC to ascertain patients who can be safely treated with less-invasive endoscopic resection such as endoscopic full-thickness resection and do not need surgery., Methods: We included 511 consecutive patients who had surgical resection with T2 CRC from 2001 to 2016; 411 patients (2001-2014) were used as a training set for the random forest-based AI prediction tool, and 100 patients (2014-2016) were used to validate the AI tool performance. The AI algorithm included 8 clinicopathologic variables (patient age and sex, tumor size and location, lymphatic invasion, vascular invasion, histologic differentiation, and serum carcinoembryonic antigen level) and predicted the likelihood of LNM by receiver-operating characteristics using area under the curve (AUC) estimates., Results: Rates of LNM in the training and validation datasets were 26% (106/411) and 28% (28/100), respectively. The AUC of the AI algorithm for the validation cohort was .93. With 96% sensitivity (95% confidence interval, 90%-99%), specificity was 88% (95% confidence interval, 80%-94%). In this case, 64% of patients could avoid surgery, whereas 1.6% of patients with LNM would lose a chance to receive surgery., Conclusions: Our proposed AI prediction model has a potential to reduce unnecessary surgery for patients with T2 CRC with very little risk. (Clinical trial registration number: UMIN 000038257.)., (Copyright © 2022 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

Background & Aims: Deep submucosal invasion (DSI) is considered a key risk factor for lymph node metastasis (LNM) and important criterion to recommend surgery in T1 colorectal cancer. However, metastatic risk for DSI is shown to be low in the absence of other histologic risk factors. This meta-analysis determines the independent risk of DSI for LNM., Methods: Suitable studies were included to establish LNM risk for DSI in univariable analysis. To assess DSI as independent risk factor, studies were eligible if risk factors (eg, DSI, poor differentiation, lymphovascular invasion, and high-grade tumor budding) were simultaneously included in multivariable analysis or LNM rate of DSI was described in absence of poor differentiation, lymphovascular invasion, and high-grade tumor budding. Odds ratios (OR) and 95% CIs were calculated., Results: Sixty-seven studies (21,238 patients) were included. Overall LNM rate was 11.2% and significantly higher for DSI-positive cancers (OR, 2.58; 95% CI, 2.10-3.18). Eight studies (3621 patients) were included in multivariable meta-analysis and did not weigh DSI as a significant predictor for LNM (OR, 1.73; 95% CI, 0.96-3.12). As opposed to a significant association between LNM and poor differentiation (OR, 2.14; 95% CI, 1.39-3.28), high-grade tumor budding (OR, 2.83; 95% CI, 2.06-3.88), and lymphovascular invasion (OR, 3.16; 95% CI, 1.88-5.33). Eight studies (1146 patients) analyzed DSI as solitary risk factor; absolute risk of LNM was 2.6% and pooled incidence rate was 2.83 (95% CI, 1.66-4.78)., Conclusions: DSI is not a strong independent predictor for LNM and should be reconsidered as a sole indicator for oncologic surgery. The expanding armamentarium for local excision as first-line treatment prompts serious consideration in amenable cases to tailor T1 colorectal cancer management., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objectives: Complete endoscopic healing, defined as Mayo endoscopic score (MES) = 0, is an optimal target in the treatment of ulcerative colitis (UC). However, some patients with MES = 0 show clinical relapse within 12 months. Histologic goblet mucin depletion has emerged as a predictor of clinical relapse in patients with MES = 0. We observed goblet depletion in vivo using an endocytoscope, and analyzed the association between goblet appearance and future prognosis in UC patients., Methods: In this retrospective cohort study, all enrolled UC patients had MES = 0 and confirmed clinical remission between October 2016 and March 2020. We classified the patients into two groups according to the goblet appearance status: preserved-goblet and depleted-goblet groups. We followed the patients until March 2021 and evaluated the difference in cumulative clinical relapse rates between the two groups., Results: We identified 125 patients with MES = 0 as the study subjects. Five patients were subsequently excluded. Thus, we analyzed the data for 120 patients, of whom 39 were classified as the preserved-goblet group and 81 as the depleted-goblet group. The patients were followed-up for a median of 549 days. During follow-up, the depleted-goblet group had a significantly higher cumulative clinical relapse rate than the preserved-goblet group (19% [15/81] vs. 5% [2/39], respectively; P = 0.02)., Conclusions: Observing goblet appearance in vivo allowed us to better predict the future prognosis of UC patients with MES = 0. This approach may assist clinicians with onsite decision-making regarding treatment interventions without a biopsy., (© 2021 Japan Gastroenterological Endoscopy Society.)

With the prevalence of endoscopic submucosal dissection and endoscopic full thickness resection, which enable complete resection of T1 colorectal cancer with a negative margin, the treatment strategy following endoscopic resection has become more important. The necessity of secondary surgical resection is determined on the basis of the risk of lymph node metastasis according to the histopathological findings of resected specimens because ~10% of T1 colorectal cancer cases have lymph node metastasis. The current Japanese treatment guidelines state four risk factors for lymph node metastasis: lymphovascular invasion, histological differentiation, depth of submucosal invasion, and tumor budding. These guidelines have succeeded in stratifying the low-risk group for lymph node metastasis, in which endoscopic resection alone is acceptable for cure. On the other hand, there are some problems: there is variation in diagnosis methods and low interobserver agreement for each pathological factor and 90% of surgical resections are unnecessary, with lymph node metastasis negativity. To ensure patients with T1 colorectal cancer receive more appropriate treatment, these problems should be addressed. In this systematic review, we gave some suggestions to these practical issues of four pathological factors as predictors., (© 2021 Japan Gastroenterological Endoscopy Society.)

Background and Aim: Although patients report either improved or worsened halitosis after Helicobacter pylori eradication therapy, such complaints are subjective. Only a few studies have objectively evaluated reports of changes in halitosis after H. pylori eradication; thus, this study aimed to investigate these changes after a successful H. pylori eradication., Methods: Between February 2015 and October 2018, 56 347 patients visited the clinic. Informed consent for participation in this study was obtained from 164 patients scheduled to undergo upper gastrointestinal endoscopy due to halitosis. Of the 91 patients with H. pylori infection, the halitosis values were evaluated as Refres breath (RB) values using a Total Gas Detector™ System and compared before and after successful H. pylori eradication, as confirmed with urea breath testing., Results: Among the 91 patients treated, 77 patients were successfully eradicated of H. pylori and had their Refres values measured (21 men and 56 women; mean age, 64.2 ± 11.5 years, including 10 smokers); among these 77 patients, 27 showed RB values of > 60. Their RB values significantly improved from 73.5 Â (95% confidence interval [CI], 64.1-82.9) to 59.4 Â (95% CI, 50.0-68.8) (P = 0.038). Of the 30 patients who could be followed up for > 2 years after successful H. pylori eradication, 8 with an RB value ≥ 60 showed significant RB value improvements from 77.9 Â (95% CI, 59.4-96.4) to 30.1 Â (95% CI, 11.6-48.6) (P = 0.0016)., Conclusions: Helicobacter pylori eradication therapy could improve halitosis, and such improvement could be maintained even 2 years after successful eradication., (© 2022 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)

The incidence of T1 colorectal cancer is expected to increase because of the prevalence of colorectal cancer screening and the progress of endoscopic treatment such as endoscopic submucosal dissection or endoscopic full-thickness resection. Currently, the requirement for additional surgery after endoscopic resection of T1 colorectal cancer is determined according to several treatment guidelines (in USA, Europe, and Japan) referring to the following pathological findings: lymphovascular invasion, tumor differentiation, depth of invasion, and tumor budding, all of which are reported to be risk factors for lymph node metastasis. In addition to these factors, in this review, we investigate whether tumor location, which is an objective factor, has an impact on the presence of lymph node metastasis and recurrence. From recent studies, left-sided location, especially the sigmoid colon in addition to rectum, could be a risk factor for lymph node metastasis and cancer recurrence. The treatment of T1 colorectal cancer should be managed considering these findings., Competing Interests: Conflicts of Interest There are no conflicts of interest., (Copyright © 2022 by The Japan Society of Coloproctology.)

Background and Aims: Recently, the use of computer-aided detection (CADe) for colonoscopy has been investigated to improve the adenoma detection rate (ADR). We aimed to assess the efficacy of a regulatory-approved CADe in a large-scale study with high numbers of patients and endoscopists., Methods: This was a propensity score-matched prospective study that took place at a university hospital between July 2020 and December 2020. We recruited patients aged ≥20 years who were scheduled for colonoscopy. Patients with polyposis, inflammatory bowel disease, or incomplete colonoscopy were excluded. We used a regulatory-approved CADe system and conducted a propensity score matching-based comparison of the ADR between patients examined with and without CADe as the primary outcome., Results: During the study period, 2261 patients underwent colonoscopy with the CADe system or routine colonoscopy, and 172 patients were excluded in accordance with the exclusion criteria. Thirty endoscopists (9 nonexperts and 21 experts) were involved in this study. Propensity score matching was conducted using 5 factors, resulting in 1836 patients included in the analysis (918 patients in each group). The ADR was significantly higher in the CADe group than in the control group (26.4% vs 19.9%, respectively; relative risk, 1.32; 95% confidence interval, 1.12-1.57); however, there was no significant increase in the advanced neoplasia detection rate (3.7% vs 2.9%, respectively)., Conclusions: The use of the CADe system for colonoscopy significantly increased the ADR in a large-scale prospective study including 30 endoscopists (Clinical trial registration number: UMIN000040677.)., (Copyright © 2022 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

Background: Although small colorectal neoplasms (< 10 mm) are often easily resected endoscopically and are considered to have less malignant potential compared with large neoplasms (≥ 10 mm), some are invasive to the submucosa., Aim: To clarify the clinicopathological features of small T1 colorectal cancers., Methods: Of 32025 colorectal lesions between April 2001 and March 2018, a total of 1152 T1 colorectal cancers resected endoscopically or surgically were included in this study and were divided into two groups by tumor size: a small group (< 10 mm) and a large group (≥ 10 mm). We compared clinicopathological factors including lymph node metastasis (LNM) between the two groups., Results: The incidence of small T1 cancers was 10.1% (116/1152). The percentage of initial endoscopic treatment in small group was significantly higher than in large group (< 10 mm 74.1% vs ≥ 10 mm 60.2%, P < 0.01). In the surgical resection cohort ( n = 798), the rate of LNM did not significantly differ between the two groups (small 12.3% vs large 10.9%, P = 0.70). In addition, there were also no significant differences between the two groups in pathological factors such as histological grade, vascular invasion, or lymphatic invasion., Conclusion: Because there was no significant difference in the rate of LNM between small and large T1 colorectal cancers, the requirement for additional surgical resection should be determined according to pathological findings, regardless of tumor size., Competing Interests: Conflict-of-interest statement: All authors declare no conflict of interest., (©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.)

With the widely spreading population-based screening programs for colorectal cancer and recent improvements in endoscopic diagnosis, the number of endoscopic resections in subjects with T1 colorectal cancer has been increasing. Some reports suggest that endoscopic resection prior to surgical resection of T1 colorectal cancer has no adverse effect on prognosis and contributes to this tendency. The decision on the need for surgical resection as an additional treatment after endoscopic resection of T1 colorectal cancer should be made according to the metastasis risk to lymph nodes based on histopathological findings. Because lymph node metastasis occurs in approximately 10% of patients with T1 colorectal cancer according to current international guidelines, the remaining 90% of patients may be at an increased risk of surgical resection and associated postoperative mortality, with no clinical benefit derived from unnecessary surgical resection. Although a more accurate prediction system for lymph node metastasis is needed to solve this problem, risk stratification for lymph node metastasis remains controversial. In this review, we focus on the current status of risk stratification of T1 colorectal cancer metastasis to lymph nodes and outline future perspectives.

Competing Interests: Competing interests The authors declare that they have no conflict of interest.

The European Society of Gastrointestinal Endoscopy does not recommend self-expanding metal stent (SEMS) placement as a bridge to surgery (BTS) for malignant colorectal obstruction (MCRO). However, no universally accepted consensus has been determined. The present study aimed to evaluate the short- and long-term outcomes of SEMS placement vs. emergency surgery (ES) for MCRO. Surgical resection of colorectal cancer was performed in 3,840 patients between April 2001 and June 2016. Of these, 93 patients had MCRO requiring emergency decompression. Only patients in whom the colorectal lesion was ultimately resected were included; thus, the present study included 62 patients treated with MCRO via SEMS placement as a BTS (n=25) or via ES (n=37). The rates of laparoscopic surgery, primary anastomosis, stoma formation, lymph node dissection, adverse events, 30-day mortality and disease-free survival were evaluated. The clinical success rate of SEMS placement was 92.0% (23/25). Compared with the ES group, the SEMS group had higher rates of laparoscopic surgery (68.0 vs. 2.7%; P<0.001) and primary anastomosis (88.0 vs. 51.4%; P=0.003), a greater number of dissected lymph nodes (30 vs. 18; P=0.001), and lower incidences of stoma formation (24.0 vs. 67.6%; P=0.002) and overall adverse events (24.0 vs. 62.2%; P=0.004). The 30-day mortality and disease-free survival of the SEMS group were not significantly different to that of the ES group (0 vs. 2.7%; P=1.000; log-rank test; P=0.10). In conclusion, as long as adverse events such as perforation are minimized, SEMS placement as a BTS could be a first treatment option for MCRO. The present study is registered in the University Hospital Medical Network Clinical Trials Registry (UMIN R000034868)., (Copyright: © Yagawa et al.)

Background & Aims: In accordance with guidelines, most patients with T1 colorectal cancers (CRC) undergo surgical resection with lymph node dissection, despite the low incidence (∼10%) of metastasis to lymph nodes. To reduce unnecessary surgical resections, we used artificial intelligence to build a model to identify T1 colorectal tumors at risk for metastasis to lymph node and validated the model in a separate set of patients., Methods: We collected data from 3134 patients with T1 CRC treated at 6 hospitals in Japan from April 1997 through September 2017 (training cohort). We developed a machine-learning artificial neural network (ANN) using data on patients' age and sex, as well as tumor size, location, morphology, lymphatic and vascular invasion, and histologic grade. We then conducted the external validation on the ANN model using independent 939 patients at another hospital during the same period (validation cohort). We calculated areas under the receiver operator characteristics curves (AUCs) for the ability of the model and US guidelines to identify patients with lymph node metastases., Results: Lymph node metastases were found in 319 (10.2%) of 3134 patients in the training cohort and 79 (8.4%) of /939 patients in the validation cohort. In the validation cohort, the ANN model identified patients with lymph node metastases with an AUC of 0.83, whereas the guidelines identified patients with lymph node metastases with an AUC of 0.73 (P < .001). When the analysis was limited to patients with initial endoscopic resection (n = 517), the ANN model identified patients with lymph node metastases with an AUC of 0.84 and the guidelines identified these patients with an AUC of 0.77 (P = .005)., Conclusions: The ANN model outperformed guidelines in identifying patients with T1 CRCs who had lymph node metastases. This model might be used to determine which patients require additional surgery after endoscopic resection of T1 CRCs. UMIN Clinical Trials Registry no: UMIN000038609., (Copyright © 2021 AGA Institute. Published by Elsevier Inc. All rights reserved.)

The global incidence and mortality rate of colorectal cancer remains high. Colonoscopy is regarded as the gold standard examination for detecting and eradicating neoplastic lesions. However, there are some uncertainties in colonoscopy practice that are related to limitations in human performance. First, approximately one-fourth of colorectal neoplasms are missed on a single colonoscopy. Second, it is still difficult for non-experts to perform adequately regarding optical biopsy. Third, recording of some quality indicators (e.g. cecal intubation, bowel preparation, and withdrawal speed) which are related to adenoma detection rate, is sometimes incomplete. With recent improvements in machine learning techniques and advances in computer performance, artificial intelligence-assisted computer-aided diagnosis is being increasingly utilized by endoscopists. In particular, the emergence of deep-learning, data-driven machine learning techniques have made the development of computer-aided systems easier than that of conventional machine learning techniques, the former currently being considered the standard artificial intelligence engine of computer-aided diagnosis by colonoscopy. To date, computer-aided detection systems seem to have improved the rate of detection of neoplasms. Additionally, computer-aided characterization systems may have the potential to improve diagnostic accuracy in real-time clinical practice. Furthermore, some artificial intelligence-assisted systems that aim to improve the quality of colonoscopy have been reported. The implementation of computer-aided system clinical practice may provide additional benefits such as helping in educational poorly performing endoscopists and supporting real-time clinical decision-making. In this review, we have focused on computer-aided diagnosis during colonoscopy reported by gastroenterologists and discussed its status, limitations, and future prospects., (© 2020 Japan Gastroenterological Endoscopy Society.)

Introduction: In contrast to most colorectal carcinomas arising from pedunculated or sessile protruded adenomas, submucosal-invasive (pT1) colorectal carcinoma exhibiting a depressed surface (hereinafter, "depressed colorectal carcinoma," identified by means of high-definition endoscopy) is considered to be derived from depressed precursors. We hypothesized that depressed colorectal neoplasms have unique clinicopathological features different that are different from those of protruded and flat colorectal neoplasms., Methods: We classified 27,129 colorectal neoplasms (909 pT1 carcinomas and 26,220 adenomas) resected between 2001 and 2017 into depressed (211 carcinomas and 109 adenomas), flat (304 carcinomas and 11,246 adenomas), and protruded subtypes (394 carcinomas and 14,865 adenomas) and compared their clinicopathological features. As exploratory analyses of pT1 carcinomas, we conducted whole-exome sequencing for 19 depressed and 8 protruded subtypes and RNA sequencing for 8 depressed and 8 protruded subtypes., Results: pT1 carcinomas were more common in depressed lesions (66%) than in protruded (2.6%) and flat lesions (2.6%) (P < 0.001). Compared with nondepressed pT1 carcinomas, depressed pT1 carcinomas were positively correlated with lymphovascular invasion, tumor budding, and massive submucosal invasion and inversely correlated with the presence of an adenoma component (all P < 0.001). Depressed adenomas were more likely to contain high-grade dysplasia than nondepressed adenomas (49% vs 11%, P < 0.001). A KRAS mutation was observed only in one of the 19 depressed pT1 carcinomas. Relative to protruded carcinomas, depressed carcinomas generally exhibited higher expression of genes related to angiogenesis and epithelial-mesenchymal transition., Discussion: Depressed colorectal neoplasms may harbor a unique combination of malignant histopathological phenotypes and molecular features.

Objectives: Recent studies have suggested the necessity of therapeutic intervention for patients with ulcerative colitis at high risk of clinical relapse with a Mayo endoscopic score (MES) of 1. The aim of this retrospective cohort study was to demonstrate the impact of intramucosal capillary network changes and crypt architecture abnormalities to stratify the risk of relapse in patients with an MES of 1., Methods: All included patients had an MES of ≤1 and confirmed sustained clinical remission between October 2016 and April 2019. We classified patients with an MES of 1 as "intramucosal capillary/crypt (ICC)-active" or "ICC-inactive" using endocytoscopic evaluation. We followed patients until October 2019 or until relapse; the main outcome measure was the difference in clinical relapse-free rates between ICC-active and ICC-inactive patients with an MES of 1., Results: We included 224 patients and analyzed data for 218 (82 ICC-active and 54 ICC-active with an MES of 1 and 82 with an MES of 0). During follow-up, among the patients with an MES of 1, 30.5% (95% confidence interval 20.8-41.6; 25/82) of the patients relapsed in the ICC-active group and 5.6% (95% confidence interval 1.2-15.4; 3/54) of the patients relapsed in the ICC-inactive group. The ICC-inactive group had a significantly higher clinical relapse-free rate compared with the ICC-active group (P < 0.01)., Conclusions: In vivo intramucosal capillary network and crypt architecture patterns stratified the risk of clinical relapse in patients with an MES of 1 (UMIN 000032580; UMIN 000036359)., (© 2020 Japan Gastroenterological Endoscopy Society.)

Purpose: Although some studies have reported differences in clinicopathological features between left- and right-sided advanced colorectal cancer (CRC), there are few reports regarding early-stage disease. In this study, we aimed to compare the clinicopathological features of left- and right-sided T1 CRC., Methods: Subjects were 1142 cases with T1 CRC undergoing surgical or endoscopic resection between 2001 and 2018 at Showa University Northern Yokohama Hospital. Of these, 776 cases were left-sided (descending colon to rectum) and 366 cases were right-sided (cecum to transverse colon). We compared clinical (patients age, sex, tumor size, morphology, initial treatment) and pathological features (invasion depth, histological grade, lymphatic invasion, vascular invasion, tumor budding) including lymph node metastasis (LNM)., Results: Left-sided T1 CRC showed significantly higher rates of LNM (left-sided 12.0% vs. right-sided 5.4%, P < 0.05) and lymphatic invasion (left-sided 32.7% vs. right-sided 23.2%, P < 0.05). Especially, the sigmoid colon and rectum showed higher rates of LNM (12.4% and 12.1%, respectively) than other locations. Patients with left-sided T1 CRC were younger than those with right-sided T1 CRC (64.9 years ±11.5 years vs. 68.7 ± 11.6 years, P < 0.05), as well as significantly lower rates of poorly differentiated carcinoma/mucinous carcinoma than right-sided T1 CRC (11.6% vs. 16.1%, P < 0.05)., Conclusion: Left-sided T1 CRC, especially in the sigmoid colon and rectum, exhibited higher rates of LNM than right-sided T1 CRC, followed by higher rates of lymphatic invasion. These results suggest that tumor location should be considered in decisions regarding additional surgery after endoscopic resection., Trial Registration: This study was registered with the University Hospital Medical Network Clinical Trials Registry ( UMIN 000032733 ).

Background & Aims: Precise optical diagnosis of colorectal polyps could improve the cost-effectiveness of colonoscopy and reduce polypectomy-related complications. However, it is difficult for community-based non-experts to obtain sufficient diagnostic performance. Artificial intelligence-based systems have been developed to analyze endoscopic images; they identify neoplasms with high accuracy and low interobserver variation. We performed a multi-center study to determine the diagnostic accuracy of EndoBRAIN, an artificial intelligence-based system that analyzes cell nuclei, crypt structure, and microvessels in endoscopic images, in identification of colon neoplasms., Methods: The EndoBRAIN system was initially trained using 69,142 endocytoscopic images, taken at 520-fold magnification, from patients with colorectal polyps who underwent endoscopy at 5 academic centers in Japan from October 2017 through March 2018. We performed a retrospective comparative analysis of the diagnostic performance of EndoBRAIN vs that of 30 endoscopists (20 trainees and 10 experts); the endoscopists assessed images from 100 cases produced via white-light microscopy, endocytoscopy with methylene blue staining, and endocytoscopy with narrow-band imaging. EndoBRAIN was used to assess endocytoscopic, but not white-light, images. The primary outcome was the accuracy of EndoBrain in distinguishing neoplasms from non-neoplasms, compared with that of endoscopists, using findings from pathology analysis as the reference standard., Results: In analysis of stained endocytoscopic images, EndoBRAIN identified colon lesions with 96.9% sensitivity (95% CI, 95.8%-97.8%), 100% specificity (95% CI, 99.6%-100%), 98% accuracy (95% CI, 97.3%-98.6%), a 100% positive-predictive value (95% CI, 99.8%-100%), and a 94.6% negative-predictive (95% CI, 92.7%-96.1%); these values were all significantly greater than those of the endoscopy trainees and experts. In analysis of narrow-band images, EndoBRAIN distinguished neoplastic from non-neoplastic lesions with 96.9% sensitivity (95% CI, 95.8-97.8), 94.3% specificity (95% CI, 92.3-95.9), 96.0% accuracy (95% CI, 95.1-96.8), a 96.9% positive-predictive value, (95% CI, 95.8-97.8), and a 94.3% negative-predictive value (95% CI, 92.3-95.9); these values were all significantly higher than those of the endoscopy trainees, sensitivity and negative-predictive value were significantly higher but the other values are comparable to those of the experts., Conclusions: EndoBRAIN accurately differentiated neoplastic from non-neoplastic lesions in stained endocytoscopic images and endocytoscopic narrow-band images, when pathology findings were used as the standard. This technology has been authorized for clinical use by the Japanese regulatory agency and should be used in endoscopic evaluation of small polyps more widespread clinical settings. UMIN clinical trial no: UMIN000028843., (Copyright © 2020 AGA Institute. Published by Elsevier Inc. All rights reserved.)

Background and Aims: Endocytoscopy, a next-generation endoscopic system, facilitates observation at a maximum magnification of ×520. To our knowledge, no study has reported high-precision diagnosis of colorectal low-grade adenoma, endoscopically. We aimed to reveal which endocytoscopic findings may be used as indicators of low-grade adenoma and to assess whether a "resect and discard" strategy using endocytoscopy is feasible., Methods: Lesions diagnosable with endocytoscopy were examined retrospectively between May 2005 and July 2017. A normal pit-like structure in endocytoscopic images was considered a normal pit (NP) sign and used as an indicator of low-grade adenoma. The primary outcome was the diagnostic accuracy of the NP sign for low-grade adenoma. We evaluated agreement rates between endocytoscopic and pathologic diagnosis for surveillance colonoscopy interval recommendation (SCIR) and performed a validation study to verify the agreement rates., Results: For 748 lesions in 573 cases diagnosed as colorectal adenoma using endocytoscopy, the results were as follows: sensitivity of the NP sign for low-grade adenoma, 85.0%; specificity, 90.7%; positive predictive value, 96.6%; negative predictive value, 66.1%; accuracy, 86.4%; and positive likelihood ratio, 9.2 (P < .001). The agreement rate between endocytoscopic and pathologic diagnosis for SCIR was 94.4% (95% confidence interval [CI], 92.2%-96.1%; P < .001) under United States guidelines and 96.3% (95% CI, 94.5%-97.7%; P < .001) under European Union guidelines. All inter- and intraobserver agreement rates for expert and nonexpert endoscopists had κ values ≥0.8 except one nonexpert pair., Conclusions: Endocytoscopy is an effective modality in determining the differential diagnosis of colorectal low-grade adenoma. (University Hospital Medical Information Network Clinical Trials database registration number: UMIN000018623.)., (Copyright © 2020 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

Background and Aims: Endoscopic submucosal dissection (ESD) is commonly used to treat early-stage digestive cancer because it results in a higher frequency of en-bloc resection and a lower frequency of local recurrence. However, the efficacy and safety of duodenal ESD remain unclear. Therefore, present study is aimed at evaluating clinical outcomes of duodenal ESD., Methods: To evaluate the efficacy and safety of duodenal ESD, electronic databases (MEDLINE, CENTRAL and EMBASE) were searched by two independent reviewers. The authors were contacted for additional information. A meta-analysis was performed to evaluate the efficacy and safety of duodenal ESD., Results: A total of 7 studies (203 patients) were included in the quantitative synthesis analysis. The pooled proportions of the frequencies of en-bloc resection, need for surgical intervention, bleeding, intraoperative perforation and delayed perforation were 87%, 4%, 2%, 15% and 2%, respectively. The quality of evidence regarding on surgical intervention outcomes was rated as moderate, whereas that of en-bloc resection was rated as low because of its marked inconsistency., Conclusions: Duodenal ESD produced acceptable outcomes in terms of the en-bloc R0 resection, but the incidence of procedure-related adverse events is high (PROSPERO register, CRD42017057110)., (Copyright © 2019 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.)

With recent advances in endoscopic treatment, many T1 colorectal carcinomas (CRCs) are resected endoscopically with a negative margin. However, some lesions exhibit skip lymphovascular invasion (SLVI), which is defined as the discontinuous foci of the tumor cells within the colon wall. The aim of the present study was to reveal the clinicopathological features of T1 CRCs with SLVI and validate the Japanese guidelines regarding SLVI. A total of 741 patients with T1 CRCs that were resected surgically between April 2001 and October 2016 in our hospital were divided into two groups: With SLVI and without SLVI. Clinicopathological features compared between the two groups were patient's gender, age, tumor size, location, morphology, lymphovascular invasion, tumor differentiation, tumor budding and lymph node metastasis. The incidence of T1 CRCs with SLVI was 0.9% (7/741). All cases with SLVI were found in the sigmoid colon or rectum. T1 CRCs with SLVI showed significantly higher rates of lymphovascular invasion than those without SLVI (P<0.01). In conclusion, lymphovascular invasion was a significant risk factor for SLVI in T1 CRCs, and for which surgical colectomy was necessary. The Japanese guidelines are appropriate regarding SLVI. Registered in the University Hospital Medical Network Clinical Trials Registry (UMIN000027097).

Background: Computer-aided diagnosis (CAD) for colonoscopy may help endoscopists distinguish neoplastic polyps (adenomas) requiring resection from nonneoplastic polyps not requiring resection, potentially reducing cost., Objective: To evaluate the performance of real-time CAD with endocytoscopes (×520 ultramagnifying colonoscopes providing microvascular and cellular visualization of colorectal polyps after application of the narrow-band imaging [NBI] and methylene blue staining modes, respectively)., Design: Single-group, open-label, prospective study. (UMIN [University hospital Medical Information Network] Clinical Trial Registry: UMIN000027360)., Setting: University hospital., Participants: 791 consecutive patients undergoing colonoscopy and 23 endoscopists., Intervention: Real-time use of CAD during colonoscopy., Measurements: CAD-predicted pathology (neoplastic or nonneoplastic) of detected diminutive polyps (≤5 mm) on the basis of real-time outputs compared with pathologic diagnosis of the resected specimen (gold standard). The primary end point was whether CAD with the stained mode produced a negative predictive value (NPV) of 90% or greater for identifying diminutive rectosigmoid adenomas, the threshold required to "diagnose-and-leave" nonneoplastic polyps. Best- and worst-case scenarios assumed that polyps lacking either CAD diagnosis or pathology were true- or false-positive or true- or false-negative, respectively., Results: Overall, 466 diminutive (including 250 rectosigmoid) polyps from 325 patients were assessed by CAD, with a pathologic prediction rate of 98.1% (457 of 466). The NPVs of CAD for diminutive rectosigmoid adenomas were 96.4% (95% CI, 91.8% to 98.8%) (best-case scenario) and 93.7% (CI, 88.3% to 97.1%) (worst-case scenario) with stained mode and 96.5% (CI, 92.1% to 98.9%) (best-case scenario) and 95.2% (CI, 90.3% to 98.0%) (worst-case scenario) with NBI., Limitation: Two thirds of the colonoscopies were conducted by experts who had each experienced more than 200 endocytoscopies; 186 polyps not assessed by CAD were excluded., Conclusion: Real-time CAD can achieve the performance level required for a diagnose-and-leave strategy for diminutive, nonneoplastic rectosigmoid polyps., Primary Funding Source: Japan Society for the Promotion of Science.