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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.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.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.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.

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.

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.

Background and study aims We sometimes encounter colorectal cancer (CRC) that is discovered during the time interval between initial colonoscopy and the recommended follow-up examination. Although several studies reported such cases of CRC, most were based on registry data, which implied that the endoscopic quality was not consistent or guaranteed. We aimed to clarify these clinical and endoscopic characteristics at our high-volume center where a retrospective survey could be precisely performed. Patients and methods We retrospectively analyzed patients with CRC who underwent endoscopic resection or surgery from April 2002 to December 2010, categorizing them into two groups: a “study group” of patients with a negative colonoscopy during the previous 10 years, and a “control group” of patients without a previous colonoscopy or with a previous colonoscopy more than 10 years prior. Results A total of 2042 patients had CRC, among which 55 patients were classified into the study group and the remaining 1989 into the control group. The CRC cases in the study group showed a significant association with smaller ( Conclusions Tumor size and location were associated with CRCs detected within 10 years after the negative examination. In addition, depressed-type T1 CRCs were more common. Therefore, we should pay more attention to small, right-sided, or depressed-type tumors in daily colonoscopy.

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.

OBJECTIVES Ulcerative colitis-associated neoplasias (UCAN) are often flat with an indistinct boundary from surrounding tissues, which makes differentiating UCAN from non-neoplasias difficult. Pit pattern (PIT) has been reported as one of the most effective indicators to identify UCAN. However, regenerated mucosa is also often diagnosed as a neoplastic PIT. Endocytoscopy (EC) allows visualization of cell nuclei. The aim of this retrospective study was to demonstrate the diagnostic ability of combined EC irregularly-formed nuclei with PIT (EC-IN-PIT) diagnosis to identify UCAN. METHODS This study involved patients with ulcerative colitis whose lesions were observed by EC. Each lesion was diagnosed by two independent expert endoscopists, using two types of diagnostic strategies: PIT alone and EC-IN-PIT. We evaluated and compared the diagnostic abilities of PIT alone and EC-IN-PIT. We also examined the difference in the diagnostic abilities of an EC-IN-PIT diagnosis according to endoscopic inflammation severity. RESULTS We analyzed 103 lesions from 62 patients; 23 lesions were UCAN and 80 were non-neoplastic. EC-IN-PIT diagnosis had a significantly higher specificity and accuracy compared with PIT alone: 84% versus 58% (P

Background and Aims The use of artificial intelligence (AI) during colonoscopy is attracting attention as an endoscopist-independent tool to predict the histological disease activity of ulcerative colitis (UC). However, no study has evaluated the real-time use of AI to directly predict clinical relapse of UC. Hence, it is unclear whether the real-time use of AI during colonoscopy helps clinicians to make real-time decisions regarding treatment interventions for patients with UC. This study aimed to establish the role of real-time AI in stratifying the relapse risk of patients with UC in clinical remission. Methods This open-label, prospective, cohort study was conducted in a referral center. The cohort comprised 145 consecutive patients with UC in clinical remission who underwent AI-assisted colonoscopy with a contact-microscopy function. We classified patients into either the Healing group or the Active group based on the AI outputs during colonoscopy. The primary outcome measure was clinical relapse of UC (defined as a partial Mayo score > 2) during 12 months of follow-up after colonoscopy. Results Overall, 135 patients completed the 12-month follow-up after AI-assisted colonoscopy. AI-assisted colonoscopy classified 61 as the Healing group and 74 as the Active group. The relapse rate was significantly higher in the AI-Active group (28.4%; 21/74; 95% confidence interval, 18.5%–40.1%) than the AI-Healing group (4.9%; 3/61; 95% confidence interval, 1.0%–13.7%; P Conclusion Real-time use of AI predicts the risk of clinical relapse in patients with UC in clinical remission, which helps clinicians make real-time decisions regarding treatment interventions.

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.

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 P P P 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 and study aims Mucosal healing is a current treatment target in ulcerative colitis (UC), while histological remission is another target. The aim of this study was to evaluate the efficiency of magnified narrow band imaging (NBI) findings of mucosal healing and their relationship with histological activity and prognosis. Patients and methods Patients with UC who underwent total colonoscopy between January 2010 and December 2012 with left-sided or total-colitis type UC and achieved clinical remission with an endoscopic Mayo score of 0 or 1 were included. Each colon section was observed with white light and magnified NBI, with the colonoscopy being repeated at 1-year follow-up. We assessed the relationships of magnified NBI with histological disease activity and prognosis. Magnified NBI findings were divided into three categories; honeycomb-like blood vessels (BV-H), blood vessels shaped like bare branches (BV-BB), and blood vessels shaped like vines (BV-V). Results Fifty-two patients were included. The percentage of remitted mucosa with BV-BB was 37 %, while that of mucosa with scars with BV-H was 35 %. BV-H and BV-BB did not show pathological activity (12/292 and 8/299, respectively), while BV-V showed high pathological activity (27/33, 81 %). There was a correlation between magnified NBI findings and pathological findings (P Conclusion Magnified NBI findings showed a good relationship with histological activity. This suggests that we could estimate histological activity without biopsy, and also the possibility of predicting relapse over the following year.

Background and study aims Capsule endoscopy (CE) has become a routine means of diagnosing obscure gastrointestinal bleeding (OGIB) in the small intestine. Capsules using novel blue-enhanced white light-emitting diodes are expected to acquire clearer contrast images (CIs) of the small bowel vasculature. We conducted a pilot study to examine whether CIs facilitate visualization of small bowel erosions, ulcers, and areas of angioectasia compared with standard white light images (WLIs). Patients and methods A total of 24 patients with OGIB were recruited in this study. The main outcome measure was visibility of lesions on CIs compared with WLIs. We also examined the color difference between lesions and normal mucosa (ΔE) with each imaging modality. Results Three experienced physicians retrospectively evaluated 138 images of small bowel lesions (107 erosions, or ulcers, and 31 areas of angioectasia) obtained from 24 CE examinations. The endoscopists judged that compared with WLIs, CIs afforded easier identification of erosions or ulcers in 29 of 107 cases (27.1 %), were non-inferior in 68 of 107 cases (63.6 %), and were inferior in 10 of 107 cases (9.3 %). Identification of angioectasia was judged to be easier with CIs in 15 of 31 cases (48.4 %), non-inferior in 13 of 31 cases (41.9 %), and inferior in 3 of 31 cases (9.7 %). ΔE was significantly higher for CIs than WLIs, especially for angioectasia, potentially explaining why lesions were easier to visualize. Conclusions CIs obtained by CE appear to facilitate identification of small bowel erosions, ulcers, and areas of angioectasia compared with WLIs.

Image-enhanced endoscopy is useful for diagnosing and identifying lesions in the gastrointestinal tract. Recently, image-enhanced endoscopy has become a breakthrough technology that has attracted significant attention. This image enhancing technology is available for capsule endoscopy, which is an effective tool for small intestinal lesions and has been applied in flexible spectral color enhancement technology and in contrast capsule like narrow-band imaging. In this field, most researchers focus on improving the visibility and detection of small intestinal lesions. This review summarizes previous studies on image-enhanced capsule endoscopy and aims to evaluate the efficacy of this technology.

Real-time characterization of colorectal lesions during colonoscopy is important for reducing medical costs, given that the need for a pathological diagnosis can be omitted if the accuracy of the diagnostic modality is sufficiently high. However, it is sometimes difficult for community-based gastroenterologists to achieve the required level of diagnostic accuracy. In this regard, we developed a computer-aided diagnosis (CAD) system based on endocytoscopy (EC) to evaluate cellular, glandular, and vessel structure atypia in vivo. The purpose of this study was to compare the diagnostic ability and efficacy of this CAD system with the performances of human expert and trainee endoscopists. We developed a CAD system based on EC with narrow-band imaging that allowed microvascular evaluation without dye (ECV-CAD). The CAD algorithm was programmed based on texture analysis and provided a two-class diagnosis of neoplastic or non-neoplastic, with probabilities. We validated the diagnostic ability of the ECV-CAD system using 173 randomly selected EC images (49 non-neoplasms, 124 neoplasms). The images were evaluated by the CAD and by four expert endoscopists and three trainees. The diagnostic accuracies for distinguishing between neoplasms and non-neoplasms were calculated. ECV-CAD had higher overall diagnostic accuracy than trainees (87.8 vs 63.4%; $$P=0.01$$ ), but similar to experts (87.8 vs 84.2%; $$P=0.76$$ ). With regard to high-confidence cases, the overall accuracy of ECV-CAD was also higher than trainees (93.5 vs 71.7%; $$P