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Background: The resect-and-discard strategy allows endoscopists to replace post-polypectomy pathology with real-time prediction of polyp histology during colonoscopy (optical diagnosis). We aimed to investigate the benefits and harms of implementing computer-aided diagnosis (CADx) for polyp pathology into the resect-and-discard strategy., Methods: In this systematic review and meta-analysis, we searched MEDLINE, Embase, and Scopus from database inception to June 5, 2024, without language restrictions, for diagnostic accuracy studies that assessed the performance of real-time CADx systems, compared with histology, for the optical diagnosis of diminutive polyps (≤5 mm) in the entire colon. We synthesised data for three strategies: CADx-alone, CADx-unassisted, and CADx-assisted; when the endoscopist was involved in the optical diagnosis, we synthesised data exclusively from diagnoses for which confidence in the prediction was reported as high. The primary outcomes were the proportion of polyps that would have avoided pathological assessment (ie, the proportion optically diagnosed with high confidence; main benefit) and the proportion of polyps incorrectly predicted due to false positives and false negatives (main harm), directly compared between CADx-assisted and CADx-unassisted strategies. We used DerSimonian and Laird's random-effects model to calculate all outcomes. We used Higgins I 2 to assess heterogeneity, the Grading of Recommendations, Assessment, Development, and Evaluation approach to rate certainty, and funnel plots and Egger's test to examine publication bias. This study is registered with PROSPERO, CRD42024508440., Findings: We found 1019 studies, of which 11 (7400 diminutive polyps, 3769 patients, and 185 endoscopists) were included in the final meta-analysis. Three studies (1817 patients and 4086 polyps [2148 neoplastic and 1938 non-neoplastic]) provided data to directly compare the primary outcome measures between the CADx-unassisted and CADx-assisted strategies. We found no significant difference between the CADx-assisted and CADx-unassisted strategies for the proportion of polyps that would have avoided pathological assessment (90% [88-93], 3653 [89·4%] of 4086 polyps diagnosed with high confidence vs 90% [95% CI 85-94], 3588 [87·8%] of 4086 polyps diagnosed with high confidence; risk ratio 1·01 [95% CI 0·99-1·04; I 2 =53·49%; low-certainty evidence; Egger's test p=0·18). The proportion of incorrectly predicted polyps was lower with the CADx-assisted strategy than with the CADx-unassisted strategy (12% [95% CI 7-17], 523 [14·3%] of 3653 polyps incorrectly predicted with a CADx-assisted strategy vs 13% [6-20], 582 [16·2%] of 3588 polyps incorrectly diagnosed with a CADx-unassisted strategy; risk ratio 0·88 [95% CI 0·79-0·98]; I 2 =0·00%; low-certainty evidence; Egger's test p=0·18)., Interpretation: CADx did not produce benefit nor harm for the resect-and-discard strategy, questioning its value in clinical practice. Improving the accuracy and explainability of CADx is desired., Funding: European Commission (Horizon Europe), the Japan Society of Promotion of Science, and Associazione Italiana per la Ricerca sul Cancro., Competing Interests: Declaration of interests CHas reports consultancy fees from Fujifilm and Medtronic. YM reports consultancy fees, speaking honoraria, and equipment loan from Olympus, and license fee for the co-developed artificial intelligence medical devices from Cybernet System (in the field of colonoscopy, one of which has been included in the analysis in this Article). AR reports consultancy fees from Fujifilm, Olympus, and Medtronic. DvR reports research grants from Fujifilm, Eberhard & Robert Bosch Elektronik (ERBE), and Boston Scientific; speaker fees from Fujifilm, ERBE, Boston Scientific, and Medtronic; support for attending meetings from Fujifilm and ERBE, and endoscopy device loan from Fujifilm and ERBE. ER reports speaking honoraria from Fujifilm; consultancy fees from Medtronic; and speaker fees from Fujifilm. OP reports speaker fees from Medtronic, Boston Scientific, AbbVie, Falk, Luvos, and Olympus. ED reports consulting fees from Olympus, Fujifilm, Ambu, InterVenn, Norgine, and Exact Science; speaker fees from Olympus, GI Supply, Norgine, IPSEN-Mayoly, and Fujifilm; and endoscopy device loan from Fujifilm. POV reports research grant from European Comission (Horizon Europe 101057099). PS reports research grants from ERBE, Fujifilm, Nippon Electric Company, and Sebela; and consulting fees from Olympus, Boston Scientific, Salix Pharmaceuticals, Cipla, Medtronic, Takeda, Samsung Bioepis, and CDx. DKR reports research grants from Olympus, Sebela Pharmaceuticals, and ERBE; consulting fees from Olympus, Sebela Pharmaceuticals, Boston Scientific, and Laborie Medical; speaker fees from Boston Scientific, Laborie Medical, and Medtronic; and ownership of stock in Satisfai Health. PB reports research grants from NEC-Europe, Boston Scientific, and 3-D matrix and consulting fees from Fujifilm. GA reports research grants from the European Society of Gastrointestinal Endoscopy, consulting fees from Medtronic and Cosmo IMD, and speaker fees from Medtronic. JWL reports speaker fees from Olympus and Fujifilm. MMe reports license fee for the co-developed artificial intelligence medical devices from Cybernet System (in the field of colonoscopy, one of which has been included in the analysis in this Article) and consulting fees and speaker fees from Olympus. S-eK reports license fees for the co-developed artificial intelligence medical devices from Cybernet System (in the field of colonoscopy, one of which has been included in the analysis in this Article) and speaker fees from Olympus. RM reports research grants from ERBE, Fujifilm, Olympus, Pentax, and Boston Scientific. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

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: Neoadjuvant therapy (NAT) before radical surgery are effective treatments for locally advanced rectal cancer. However, the treatment strategy after NAT and surgery is still unclear. It is difficult to accurately evaluate the stage before NAT, as some cases are downstaged by NAT., Objective: We investigated the treatment strategies based on the postoperative pathology of patients with yStage Ⅰ or Ⅱ rectal cancer who underwent NAT and radical resection., Design: They patients were retrospectively evaluated the long-term outcomes. They were divided into patients with yStage I/II receiving NAT and patients with stage I/II patients without NAT (non-NAT). Disease-free survival (DFS) and overall survival (OS) were examined, and the prognosis was compared. Cox proportional hazard model was used to examine the recurrence risk factors in all patients or NAT. We compared the effects of adjuvant therapy in NAT., Patients: Overall, 521 patients histologically diagnosed with yStage I/II or stage I/II who underwent surgery for rectal cancer between April 2001 and July 2019 were eligible., Results: The NAT and non-NAT groups included 80 and 441 patients, respectively. DFS was significantly lower in NAT, but there was no difference in OS between the two groups. All patients had several recurrence risk factors, but none of the NAT had such risk factors. No significant difference in DFS and OS was found between NAT with and without adjuvant chemotherapy., Limitation: This is a single-center retrospective study., Conclusions: NAT had lower DFS than non-NAT, but no difference in OS was observed. No significant recurrence risk factors were observed in NAT. Adjuvant chemotherapy for NAT may have no benefit., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

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.

The emerging role of artificial intelligence (AI) in automated endoscopic diagnosis represents a significant advancement in managing inflammatory bowel disease (IBD). AI technologies are increasingly being applied to endoscopic imaging to enhance the diagnosis, prediction of severity, and progression of IBD and dysplasia-associated colitis surveillance. These AI-assisted endoscopy aim to improve diagnostic accuracy, reduce variability of endoscopy imaging interpretations, and assist clinicians in decision-making processes. By leveraging AI, healthcare providers have the potential to offer more personalized and effective treatments, ultimately improving patient outcomes in IBD care., Competing Interests: Disclosure The authors have no conflicts of interest to declare., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: In the management of ulcerative colitis (UC), histological remission is increasingly recognized as the ultimate goal. The absence of neutrophil infiltration is crucial for assessing remission. This study aimed to develop an artificial intelligence (AI) system capable of accurately quantifying and localizing neutrophils in UC biopsy specimens to facilitate histological assessment., Methods: Our AI system, which incorporates semantic segmentation and object detection models, was developed to identify neutrophils in hematoxylin and eosin-stained whole slide images. The system assessed the presence and location of neutrophils within either the epithelium or lamina propria and predicted components of the Nancy Histological Index and the PICaSSO Histologic Remission Index. We evaluated the system's performance against that of experienced pathologists and validated its ability to predict future clinical relapse risk in patients with clinically remitted UC. The primary outcome measure was the clinical relapse rate, defined as a partial Mayo score of ≥3., Results: The model accurately identified neutrophils, achieving a performance of 0.77, 0.81, and 0.79 for precision, recall, and F-score, respectively. The system's histological score predictions showed a positive correlation with the pathologists' diagnoses (Spearman's ρ = 0.68-0.80; P < .05). Among patients who relapsed, the mean number of neutrophils in the rectum was higher than in those who did not relapse. Furthermore, the study highlighted that higher AI-based PICaSSO Histologic Remission Index and Nancy Histological Index scores were associated with hazard ratios increasing from 3.2 to 5.0 for evaluating the risk of UC relapse., Conclusions: The AI system's precise localization and quantification of neutrophils proved valuable for histological assessment and clinical prognosis stratification., (Copyright © 2024. Published by Elsevier Inc.)

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.)

This systematic review evaluated the current status of AI-assisted colonoscopy to identify histologic remission and predict the clinical outcomes of patients with ulcerative colitis. The use of artificial intelligence (AI) has increased substantially across several medical fields, including gastrointestinal endoscopy. Evidence suggests that it may be helpful to predict histologic remission and relapse, which would be beneficial because current histological diagnosis is limited by the inconvenience of obtaining biopsies and the high cost and time-intensiveness of pathological diagnosis. MEDLINE and the Cochrane Central Register of Controlled Trials were searched for studies published between January 1, 2000, and October 31, 2023. Nine studies fulfilled the selection criteria and were included; five evaluated the prediction of histologic remission, two assessed the prediction of clinical outcomes, and two evaluated both. Seven were prospective observational or cohort studies, while two were retrospective observational studies. No randomized controlled trials were identified. AI-assisted colonoscopy demonstrated sensitivity between 65 %-98 % and specificity values of 80 %-97 % for identifying histologic remission. Furthermore, it was able to predict future relapse in patients with ulcerative colitis. However, several challenges and barriers still exist to its routine clinical application, which should be overcome before the true potential of AI-assisted colonoscopy can be fully realized., Competing Interests: Conflict of interest The authors have no conflicts of interest to declare., (Copyright © 2024 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. 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.)

Precision endoscopy in the management of colorectal polyps and early colorectal cancer has emerged as the standard of care. It includes optical characterization of polyps and estimation of submucosal invasion depth of large nonpedunculated colorectal polyps to select the appropriate endoscopic resection modality. Over time, several imaging modalities have been implemented in endoscopic practice to improve optical performance. Among these, image-enhanced endoscopy systems and magnification endoscopy represent now well-established tools. New advanced technologies, such as endocytoscopy and confocal laser endomicroscopy, have recently shown promising results in predicting the histology of colorectal polyps. In recent years, artificial intelligence has continued to enhance endoscopic performance in the characterization of colorectal polyps, overcoming the limitations of other imaging modes. In this review we retrace the path of precision endoscopy, analyzing the yield of various endoscopic imaging techniques in personalizing management of colorectal polyps and early colorectal cancer., (© 2023 Japan Gastroenterological Endoscopy Society.)

Background: Computer-aided diagnosis (CADx) allows prediction of polyp histology during colonoscopy, which may reduce unnecessary removal of nonneoplastic polyps. However, the potential benefits and harms of CADx are still unclear., Purpose: To quantify the benefit and harm of using CADx in colonoscopy for the optical diagnosis of small (≤5-mm) rectosigmoid polyps., Data Sources: Medline, Embase, and Scopus were searched for articles published before 22 December 2023., Study Selection: Histologically verified diagnostic accuracy studies that evaluated the real-time performance of physicians in predicting neoplastic change of small rectosigmoid polyps without or with CADx assistance during colonoscopy., Data Extraction: The clinical benefit and harm were estimated on the basis of accuracy values of the endoscopist before and after CADx assistance. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. The outcome measure for benefit was the proportion of polyps predicted to be nonneoplastic that would avoid removal with the use of CADx. The outcome measure for harm was the proportion of neoplastic polyps that would be not resected and left in situ due to an incorrect diagnosis with the use of CADx. Histology served as the reference standard for both outcomes., Data Synthesis: Ten studies, including 3620 patients with 4103 small rectosigmoid polyps, were analyzed. The studies that assessed the performance of CADx alone (9 studies; 3237 polyps) showed a sensitivity of 87.3% (95% CI, 79.2% to 92.5%) and specificity of 88.9% (CI, 81.7% to 93.5%) in predicting neoplastic change. In the studies that compared histology prediction performance before versus after CADx assistance (4 studies; 2503 polyps), there was no difference in the proportion of polyps predicted to be nonneoplastic that would avoid removal (55.4% vs. 58.4%; risk ratio [RR], 1.06 [CI, 0.96 to 1.17]; moderate-certainty evidence) or in the proportion of neoplastic polyps that would be erroneously left in situ (8.2% vs. 7.5%; RR, 0.95 [CI, 0.69 to 1.33]; moderate-certainty evidence)., Limitation: The application of optical diagnosis was only simulated, potentially altering the decision-making process of the operator., Conclusion: Computer-aided diagnosis provided no incremental benefit or harm in the management of small rectosigmoid polyps during colonoscopy., Primary Funding Source: European Commission. (PROSPERO: CRD42023402197)., Competing Interests: Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M23-2865.

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.)

Background: The clinicopathological features and prognosis of primary small bowel adenocarcinoma (PSBA), excluding duodenal cancer, remain undetermined due to its rarity in Japan., Methods: We analyzed 354 patients with 358 PSBAs, between January 2008 and December 2017, at 44 institutions affiliated with the Japanese Society for Cancer of the Colon and Rectum., Results: The median age was 67 years (218 males, 61.6%). The average tumor size was 49.9 (7-100) mm. PSBA sites consisted of jejunum (66.2%) and ileum (30.4%). A total of 219 patients (61.9%) underwent diagnostic small bowel endoscopy, including single-balloon endoscopy, double-balloon endoscopy, and capsule endoscopy before treatment. Nineteen patients (5.4%) had Lynch syndrome, and 272 patients (76.8%) had symptoms at the initial diagnosis. The rates for stages 0, I, II, III, and IV were 5.4%, 2.5%, 27.1%, 26.0%, and 35.6%, respectively. The 5-year overall survival rates at each stage were 92.3%, 60.0%, 75.9%, 61.4%, and 25.5%, respectively, and the 5-year disease-specific survival (DSS) rates were 100%, 75.0%, 84.1%, 59.3%, and 25.6%, respectively. Patients with the PSBA located in the jejunum, with symptoms at the initial diagnosis or advanced clinical stage had a worse prognosis. However, multivariate analysis using Cox-hazard model revealed that clinical stage was the only significant predictor of DSS for patients with PSBA., Conclusions: Of the patients with PSBA, 76.8% had symptoms at the initial diagnosis, which were often detected at an advanced stage. Detection during the early stages of PSBA is important to ensure a good prognosis., (© 2024. The Author(s).)

Background and Aim: Computer-aided detection (CADe) systems can efficiently detect polyps during colonoscopy. However, false-positive (FP) activation is a major limitation of CADe. We aimed to compare the rate and causes of FP using CADe before and after an update designed to reduce FP., Methods: We analyzed CADe-assisted colonoscopy videos recorded between July 2022 and October 2022. The number and causes of FPs and excessive time spent by the endoscopist on FP (ET) were compared pre- and post-update using 1:1 propensity score matching., Results: During the study period, 191 colonoscopy videos (94 and 97 in the pre- and post-update groups, respectively) were recorded. Propensity score matching resulted in 146 videos (73 in each group). The mean number of FPs and median ET per colonoscopy were significantly lower in the post-update group than those in the pre-update group (4.2 ± 3.7 vs 18.1 ± 11.1; P < 0.001 and 0 vs 16 s; P < 0.001, respectively). Mucosal tags, bubbles, and folds had the strongest association with decreased FP post-update (pre-update vs post-update: 4.3 ± 3.6 vs 0.4 ± 0.8, 0.32 ± 0.70 vs 0.04 ± 0.20, and 8.6 ± 6.7 vs 1.6 ± 1.7, respectively). There was no significant decrease in the true positive rate (post-update vs pre-update: 95.0% vs 99.2%; P = 0.09) or the adenoma detection rate (post-update vs pre-update: 52.1% vs 49.3%; P = 0.87)., Conclusions: The updated CADe can reduce FP without impairing polyp detection. A reduction in FP may help relieve the burden on endoscopists., (© 2024 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)

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.)

Background & Aims: To date, no regional evidence of long-term colorectal cancer (CRC) risk reduction after endoscopic premalignant lesion removal has been established. We aimed to analyze this over a long-term follow-up evaluation., Methods: This was a prospective cohort study of participants from the Japan Polyp Study conducted at 11 Japanese institutions. Participants underwent scheduled follow-up colonoscopies after a 2-round baseline colonoscopy process. The primary outcome was CRC incidence after randomization. The observed/expected ratio of CRC was calculated using data from the population-based Osaka Cancer Registry. Secondary outcomes were the incidence and characteristics of advanced neoplasia (AN)., Results: A total of 1895 participants were analyzed. The mean number of follow-up colonoscopies and the median follow-up period were 2.8 years (range, 1-15 y) and 6.1 years (range, 0.8-11.9 y; 11,559.5 person-years), respectively. Overall, 4 patients (all males) developed CRCs during the study period. The observed/expected ratios for CRC in all participants, males, and females, were as follows: 0.14 (86% reduction), 0.18, and 0, respectively, and 77 ANs were detected in 71 patients (6.1 per 1000 person-years). Of the 77 ANs detected, 31 lesions (40.3%) were laterally spreading tumors, nongranular type. Nonpolypoid colorectal neoplasms (NP-CRNs), including flat (<10 mm), depressed, and laterally spreading, accounted for 59.7% of all detected ANs. Furthermore, 2 of the 4 CRCs corresponded to T1 NP-CRNs., Conclusions: Endoscopic removal of premalignant lesions, including NP-CRNs, effectively reduced CRC risk. More than half of metachronous ANs removed by surveillance colonoscopy were NP-CRNs. The Japan Polyp Study: University Hospital Medical Information Network Clinical Trial Registry: University Hospital Medical Information Network Clinical Trial Registry, C000000058; cohort study: UMIN000040731., (Copyright © 2024 AGA Institute. Published by Elsevier Inc. All rights reserved.)

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.

Purpose: Limited information is available regarding the characteristics and outcomes of stage IV small bowel adenocarcinoma (SBA) in Japan. This study examined the clinical and pathological characteristics and outcomes according to the treatment strategies in patients with stage IV SBA., Methods: This retrospective observational study used the data of patients with jejunal or ileal adenocarcinoma collected by the Small Bowel Malignant Tumor Project of the Japanese Society for Cancer of the Colon and Rectum. Descriptive statistics were expressed as the mean (standard deviation) or median (range). Survival analysis was performed using Kaplan-Meier curves and pairwise log-rank tests., Results: Data from 128 patients were analyzed. The treatment strategies were chemotherapy alone (26 of 128, 20.3%), surgery alone (including palliative surgery; 21 of 128, 16.4%), surgery + chemotherapy (74 of 128, 57.8%), and best supportive care (7 of 128, 5.5%). The median (range) overall survival was 16 (0-125) months overall, and 11 (1-38) months, 8 (0-80) months, 18 (0-125) months, and 0 (0-1) months for the chemotherapy, surgery, surgery + chemotherapy, and best supportive care groups, respectively. Three main categories of chemotherapeutic regimen were used: a combination of fluoropyrimidine and oxaliplatin (F + Ox), fluoropyrimidine and irinotecan (F + Iri), and single-agent fluoropyrimidine. Among patients treated with chemotherapy, the median (range) OS was 16 (1-106) months overall, and 17 (1-87) months, 29 (7-39) months, and 16 (1-106) months in patients treated with fluoropyrimidine, F + Iri, and F + Ox, respectively., Conclusion: Patients treated with surgery, chemotherapy, or both had a better prognosis than those who received best supportive care. Among patients who received chemotherapy, survival did not differ according to the chemotherapeutic regimen.

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.)

The present study examined the therapeutic effects of preoperative neoadjuvant chemoradiation therapy (NACRT) and predictive factors for complete clinical remission, compared the prognosis and costs of abdominoperineal resection (APR) and the "watch and wait" method (WW), and evaluated the usefulness of WW. In our department, patients with stage II-III lower rectal cancer requiring APR receive NACRT. NACRT was performed as a preoperative treatment (52 Gy + S-1: 80-120 mg/day × 25 days). Eight weeks after the completion of NACRT, rectal examination, endoscopic, computed tomography, and magnetic resonance imaging findings were evaluated to assess its therapeutic effects. APR was indicated for patients in whom endoscopic findings suggested a residual tumor in which a deep ulcer or marginal swelling remained or lymph node metastasis. However, WW was selected for patients who refused APR after informed consent was obtained. In the APR and WW groups, 5- and 20-year treatment costs after CRT were calculated using the Medical Fee Points of Japan in 2020. No significant differences were observed in 3-year disease-free survival rates for either parameter between the two groups. Regarding expenses, treatment costs were lower in the WW group than in the APR group. Organ preservation using active surveillance with CRT for rectal cancer requiring APR is feasible with the achievement of endoluminal complete remission., Competing Interests: Competing InterestsThe authors declare no competing interests., (© The Author(s), under exclusive licence to Indian Association of Surgical Oncology 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

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.)

Background/aim: According to the Tokyo Guidelines 2018, the operation for acute cholecystitis is recommended to be performed as early as possible. However, there are cases in which early surgeries cannot be performed due to complications of patients or facility conditions, resulting in elective surgery. Hence, we retrospectively analyzed elective surgery cases in this study., Patients and Methods: There were 345 patients who were underwent laparoscopic cholecystectomy (LC) at our hospital from January 2019 to December 2020 in this retrospective study. A total of 83 patients underwent LC more than 3 days after conservative treatment. The elective LC patients were divided into the Early group (4-90 days after onset, n=36) and the Delayed group [91 days or more (13 weeks or more) after onset, n=31], excluding 16 patients who underwent percutaneous transhepatic gallbladder drainage., Results: As for operative time, there was a significant difference between the Delayed and Early groups (91.2 vs. 117 minutes, p=0.0108). And also, there was a significant difference in the postoperative hospital stay, which was significantly shorter in the Delayed group than in the Early group (3.4 vs. 5.9 days, p=0.0436). Although there were no significant differences in either conversion rates or complication rates, both of these were decreasing in the Delayed group. In particular, there were no complications in the Delayed group., Conclusion: When the conservative treatment for acute cholecystitis precedes and precludes urgent/early LC within 3 days, delaying LC for at least 91 days (13 weeks or more) after onset could reduce operative time and postoperative hospital stay. Moreover, there would be no complications after LC, and the rates of conversion during LC may be kept low., Competing Interests: All Authors have no conflicts of interest to declare in relation to this study., (Copyright 2023, International Institute of Anticancer Research.)

Competing Interests: MM and SK received speaking honoraria from Olympus Corporation and received licensing fees according to sales of products called the EndoBRAIN series, which is a type of AI-assisted colonoscopy software launched in Japan and some other Asian countries. These licensing fees are not associated with the following patents: SK and MM have patents (Japan patents 6059271 and 6580446) related to AI algorithms, which are licensed to Cybernet Systems and Showa University. Patent-related royalties are assigned to Showa University. YM received speaking honoraria, consultant fees, and device loans from Olympus Corporation and received licensing fees according to sales of the EndoBRAIN series.

Objectives: Endoscopic submucosal dissection (ESD) is an effective procedure for the en bloc resection of colorectal neoplasms. However, risk factors for local recurrence after ESD have not been identified. This study aimed to evaluate such risk factors after ESD for colorectal neoplasms., Methods: This retrospective study included 1344 patients with 1539 consecutive colorectal lesions who underwent ESD between September 2003 and December 2019. We investigated various factors associated with local recurrence in these patients. The main outcomes were the incidence of local recurrence and its relationship with clinicopathological factors during long-term surveillance., Results: The en bloc resection rate was 98.6%, the R0 resection rate was 97.2%, and the histologically complete resection rate was 92.7%. Local recurrence was observed in 7/1344 (0.5%) patients and the median follow-up period was 72 months (range 4-195 months). The incidence of local recurrence was significantly higher in lesions ≥40 mm in diameter (hazard ratio [HR] 15.68 [1.88-130.5]; p = 0.011), piecemeal resection (HR 48.42 [10.7-218.7]; p < 0.001), non-R0 resection (HR 41.05 [9.025-186.7]; p < 0.001), histologically incomplete resection (HR 16.23 [3.627-72.63]; p <0.001), and severe fibrosis (F2; HR 9.523 [1.14-79.3]; p = 0.037)., Conclusions: Five risk factors for local recurrence after ESD were identified. Patients with such factors should undergo careful surveillance colonoscopy., Competing Interests: Masashi Misawa is an Associate Editor of Digestive Endoscopy. The other 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: Meticulous inspection of the mucosa during colonoscopy, represents a lengthier withdrawal time, but has been shown to increase adenoma detection rate (ADR). We investigated if artificial intelligence-aided speed monitoring can improve suboptimal withdrawal time., Methods: We evaluated the implementation of a computer-aided speed monitoring device during colonoscopy at a large academic endoscopy center. After informed consent, patients ≥18 years undergoing colonoscopy between 5 March and 29 April 2021 were examined without the use of the speedometer, and with the speedometer between 29 April and 30 June 2021. All colonoscopies were recorded, and withdrawal time was assessed based on the recordings in a blinded fashion. We compared mean withdrawal time, percentage of withdrawal time ≥6 min, and ADR with and without the speedometer., Results: One hundred sixty-six patients in each group were eligible for analyses. Mean withdrawal time was 9 min and 6.6 s (95% CI: 8 min and 34.8 s to 9 min and 39 s) without the use of the speedometer, and 9 min and 9 s (95% CI: 8 min and 45 s to 9 min and 33.6 s) with the speedometer; difference 2.3 s (95% CI: -42.3-37.7, p  = 0.91). The ADRs were 45.2% (95% CI: 37.6-52.8) without the speedometer as compared to 45.8% (95% CI: 38.2-53.4) with the speedometer ( p  = 0.91). The proportion of colonoscopies with withdrawal time ≥6 min without the speedometer was 85.5% (95% CI: 80.2-90.9) versus 86.7% (95% CI: 81.6-91.9) with the speedometer ( p  = 0.75)., Conclusions: Use of speed monitoring during withdrawal did not increase withdrawal time or ADR in colonoscopy., Clinicaltrials.gov Identifier: NCT04710251.

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.)

Purpose: Endoscopic submucosal dissection (ESD) is a minimally invasive treatment for early gastric cancer. However, perforations may happen and cause peritonitis during ESD. Thus, there is a potential demand for a computer-aided diagnosis system to support physicians in ESD. This paper presents a method to detect and localize perforations from colonoscopy videos to avoid perforation ignoring or enlarging by ESD physicians., Method: We proposed a training method for YOLOv3 by using GIoU and Gaussian affinity losses for perforation detection and localization in colonoscopic images. In this method, the object functional contains the generalized intersection over Union loss and Gaussian affinity loss. We propose a training method for the architecture of YOLOv3 with the presented loss functional to detect and localize perforations precisely., Results: To qualitatively and quantitatively evaluate the presented method, we created a dataset from 49 ESD videos. The results of the presented method on our dataset revealed a state-of-the-art performance of perforation detection and localization, which achieved 0.881 accuracy, 0.869 AUC, and 0.879 mean average precision. Furthermore, the presented method is able to detect a newly appeared perforation in 0.1 s., Conclusions: The experimental results demonstrated that YOLOv3 trained by the presented loss functional were very effective in perforation detection and localization. The presented method can quickly and precisely remind physicians of perforation happening in ESD. We believe a future CAD system can be constructed for clinical applications with the proposed method., (© 2023. CARS.)

The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost-effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO Position Statement: Statement 1.1: Computer-aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short term, use of CADe is likely to increase health-care costs by detecting more adenomas; Statement 1.3: In the long term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe-related cancer prevention; Statement 1.4: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer-aided diagnosis (CADx) for diminutive polyps (≤5 mm), when it has sufficient accuracy, is expected to reduce health-care costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high-quality cost-effectiveness research should be undertaken to understand whether AI implementation benefits populations and societies in different health-care systems., (© 2023 Japan Gastroenterological Endoscopy Society.)

Background and Aims: Artificial intelligence (AI) tools aimed at improving polyp detection have been shown to increase the adenoma detection rate during colonoscopy. However, it is unknown how increased polyp detection rates by AI affect the burden of patient surveillance after polyp removal., Methods: We conducted a pooled analysis of 9 randomized controlled trials (5 in China, 2 in Italy, 1 in Japan, and 1 in the United States) comparing colonoscopy with or without AI detection aids. The primary outcome was the proportion of patients recommended to undergo intensive surveillance (ie, 3-year interval). We analyzed intervals for AI and non-AI colonoscopies for the U.S. and European recommendations separately. We estimated proportions by calculating relative risks using the Mantel-Haenszel method., Results: A total of 5796 patients (51% male, mean 53 years of age) were included; 2894 underwent AI-assisted colonoscopy and 2902 non-AI colonoscopy. When following U.S. guidelines, the proportion of patients recommended intensive surveillance increased from 8.4% (95% CI, 7.4%-9.5%) in the non-AI group to 11.3% (95% CI, 10.2%-12.6%) in the AI group (absolute difference, 2.9% [95% CI, 1.4%-4.4%]; risk ratio, 1.35 [95% CI, 1.16-1.57]). When following European guidelines, it increased from 6.1% (95% CI, 5.3%-7.0%) to 7.4% (95% CI, 6.5%-8.4%) (absolute difference, 1.3% [95% CI, 0.01%-2.6%]; risk ratio, 1.22 [95% CI, 1.01-1.47])., Conclusions: The use of AI during colonoscopy increased the proportion of patients requiring intensive colonoscopy surveillance by approximately 35% in the United States and 20% in Europe (absolute increases of 2.9% and 1.3%, respectively). While this may contribute to improved cancer prevention, it significantly adds patient burden and healthcare costs., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Mucin depletion is one of the histological indicators of clinical relapse among patients with ulcerative colitis (UC). Mucin depletion is evaluated semiquantitatively by pathologists using histological images. Therefore, the interobserver concordance is not extremely high, and an objective evaluation method is needed. This study was conducted to demonstrate that our automated quantitative method using a deep learning-based model is useful in predicting the prognosis of patients with UC., Methods: Deep learning-based models were trained to detect goblet cell mucus area from whole slide images of biopsy specimens. This study involved 114 patients with UC in endoscopic remission with a partial Mayo score of ≤ 1. Biopsy specimens were collected during colonoscopy, and the ratio of goblet cell mucus area to the epithelial cell and goblet cell mucus area was calculated as goblet cell ratio (GCR). The follow-up time was 12 months, and the primary outcome was the relapse rate. Clinical relapse was defined as partial Mayo score of ≥ 3., Results: Sixteen patients (14%) experienced clinical relapse. In the relapsed group, the GCRs of specimens obtained from the cecum, ascending colon, and rectum were significantly lower than those of specimens in the relapse-free group (p = 0.010, p = 0.027, p < 0.01). In the rectum, patients with a GCR of ≤ 12% had a significantly higher relapse rate than those with a GCR of > 12% (45% [10/22] vs. 6.5% [6/92]; p < 0.01)., Conclusions: Quantifying goblet cell mucus areas using a deep learning-based model is useful in predicting the clinical relapse in patients with UC in clinical and endoscopic remission., (© 2022. Japanese Society of Gastroenterology.)

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.)

Purpose: Precise polyp detection and localisation are essential for colonoscopy diagnosis. Statistical machine learning with a large-scale data set can contribute to the construction of a computer-aided diagnosis system for the prevention of overlooking and miss-localisation of a polyp in colonoscopy. We propose new visual explaining methods for a well-trained object detector, which achieves fast and accurate polyp detection with a bounding box towards a precise automated polyp localisation., Method: We refine gradient-weighted class activation mapping for more accurate highlighting of important patterns in processing a convolutional neural network. Extending the refined mapping into multiscaled processing, we define object activation mapping that highlights important object patterns in an image for a detection task. Finally, we define polyp activation mapping to achieve precise polyp localisation by integrating adaptive local thresholding into object activation mapping. We experimentally evaluate the proposed visual explaining methods with four publicly available databases., Results: The refined mapping visualises important patterns in each convolutional layer more accurately than the original gradient-weighted class activation mapping. The object activation mapping clearly visualises important patterns in colonoscopic images for polyp detection. The polyp activation mapping localises the detected polyps in ETIS-Larib, CVC-Clinic and Kvasir-SEG database with mean Dice scores of 0.76, 0.72 and 0.72, respectively., Conclusions: We developed new visual explaining methods for a convolutional neural network by refining and extending gradient-weighted class activation mapping. Experimental results demonstrated the validity of the proposed methods by showing that accurate visualisation of important patterns and localisation of polyps in a colonoscopic image. The proposed visual explaining methods are useful for the interpreting and applying a trained polyp detector., (© 2022. CARS.)

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

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.