Artificial intelligence-assisted video colonoscopy for disease monitoring of ulcerative colitis: A prospective study.

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.

A novel artificial intelligence-assisted "vascular healing" diagnosis for prediction of future clinical relapse in patients with ulcerative colitis: a prospective cohort study (with video).

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.

Impact of computer-aided characterization for diagnosis of colorectal lesions, including sessile serrated lesions: Multireader, multicase study.

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.

Whole slide image-based prediction of lymph node metastasis in T1 colorectal cancer using unsupervised artificial intelligence.

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_view.cgi?recptno=R000053590).

Relaxin contributes to the elevation of monocytic myeloid-derived suppressor cells in peripheral blood of pregnant canines.

Tolerance towards fetal alloantigens in the maternal immune system is essential for maintaining pregnancy. Myeloid-derived suppressor cells (MDSCs) are immature myeloid cells characterized by their ability to suppress immune activity and maintain maternal-fetal immune tolerance. However, the mechanisms underlying MDSC induction have not been elucidated. Herein, we investigated the myeloid-derived suppressor cells (MDSCs) in the peripheral blood of pregnant canines and its induction mechanism. By analyzing the concentration of MDSCs in the peripheral blood of pregnant canines, elevation of MDSCs has been observed during pregnancy. In addition, MDSCs from pregnant canines inhibit T cell activation. These results suggest that the elevated MDSCs in canine pregnancy may contribute to reduces maternal immune activity. To clarify the cause of MDSCs elevation in canine pregnancy, we analyzed the relationship between pregnancy-related hormones (estradiol, progesterone, and relaxin) and MDSCs. Serum relaxin levels, but not estradiol and progesterone, were correlated with the ratio of monocyte MDSCs. Additionally, relaxin induced monocytic MDSCs as well as inhibited T cell activation in vitro. Therefore, relaxin contributes to the elevation of monocytic MDSCs in the peripheral blood of pregnant canines. Our findings highlight the novel role of relaxin in pregnancy and contribute to a better understanding of maternal-fetal immune tolerance.

Molecular and clinicopathological differences between depressed and protruded T2 colorectal cancer.

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.

Use of advanced endoscopic technology for optical characterization of neoplasia in patients with ulcerative colitis: Systematic review.

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.

Changes in halitosis value before and after Helicobacter pylori eradication: A single-institutional prospective study.

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.

Combined endocytoscopy with pit pattern diagnosis in ulcerative colitis-associated neoplasia: Pilot study.

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 < 0.001), and 88% versus 67% (P < 0.01), respectively. The specificity and accuracy were significantly higher for Mayo endoscopic score (MES) 0-1 than MES 2-3: 93% versus 68% (P < 0.001) and 95% versus 74% (P < 0.001), respectively. CONCLUSIONS: Our novel EC-IN-PIT strategy had a better diagnostic ability than PIT alone to predict UCAN from suspected and initially detected lesions using conventional colonoscopy. UMIN clinical trial (UMIN000040698).

Current status and future perspective on artificial intelligence for lower endoscopy.

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.

Endocytoscopic intramucosal capillary network changes and crypt architecture abnormalities can predict relapse in patients with an ulcerative colitis Mayo endoscopic score of 1.

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).

Depressed Colorectal Cancer: A New Paradigm in Early Colorectal Cancer.

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.

GTF2IRD1 on chromosome 7 is a novel oncogene regulating the tumor-suppressor gene TGFßR2 in colorectal cancer.

Chromosome 7q (Ch.7q) is clonally amplified in colorectal cancer (CRC). We aimed to identify oncogenes on Ch.7q that are overexpressed through DNA copy number amplification and determine the biological and clinical significance of these oncogenes in CRC. We identified general transcription factor 2I repeat domain-containing protein 1 (GTF2IRD1) as a potential oncogene using a CRC dataset from The Cancer Genome Atlas with a bioinformatics approach. We measured the expression of GTF2IRD1 in 98 patients with CRC using immunohistochemistry and RT-quantitative PCR (RT-qPCR). The biological effects of GTF2IRD1 expression were explored by gene set enrichment analysis (GSEA). Next, we undertook in vitro cell proliferation and cell cycle assays using siGTF2IRD1-transfected CRC cells. We further investigated the oncogenic mechanisms through which GTF2IRD1 promoted CRC progression. Finally, we assessed the clinical significance of GTF2IRD1 expression by RT-qPCR. GTF2IRD1 was overexpressed in tumor cells and liver metastatic lesions. The GSEA revealed a positive correlation between GTF2IRD1 expression and cell cycle progression-related genes. GTF2IRD1 knockdown inhibited cell proliferation and induced cell cycle arrest in Smad4-mutated CRC. GTF2IRD1 downregulated the expression of the gene encoding transforming growth factor ß receptor 2 (TGFßR2), a tumor-suppressor gene in Smad4-mutated CRC. On multivariate analysis, high GTF2IRD1 expression was an independent poor prognostic factor. Clinicopathological analysis showed that GTF2IRD1 expression was positively correlated with liver metastasis. In conclusion, GTF2IRD1 promoted CRC progression by downregulating TGFßR2 and could be a prognostic biomarker on Ch.7q in CRC. GTF2IRD1 could also be a novel oncogene in CRC.

Endocytoscopy for the differential diagnosis of colorectal low-grade adenoma: a novel possibility for the "resect and discard" strategy.

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.).

Oncogenic splicing abnormalities induced by DEAD-Box Helicase 56 amplification in colorectal cancer.

Alternative splicing, regulated by DEAD-Box Helicase (DDX) families, plays an important role in cancer. However, the relationship between the DDX family and cancer has not been fully elucidated. In the present study, we identified a candidate oncogene DDX56 on Ch.7p by a bioinformatics approach using The Cancer Genome Atlas (TCGA) dataset of colorectal cancer (CRC). DDX56 expression was measured by RT-qPCR and immunochemical staining in 108 CRC patients. Clinicopathological and survival analyses were carried out using three CRC datasets. Biological roles of DDX56 were explored by gene set enrichment analysis (GSEA), and cell proliferation in vitro and in vivo, cell cycle assays, and using DDX56-knockdown or overexpressed CRC cells. RNA sequencing was carried out to elucidate the effect of DDX56 on mRNA splicing. We found that DDX56 expression was positively correlated with the amplification of DDX56 and was upregulated in CRC cells. High DDX56 expression was associated with lymphatic invasion and distant metastasis and was an independent poor prognostic factor. In vitro analysis, in vivo analysis and GSEA showed that DDX56 promoted proliferation ability through regulating the cell cycle. DDX56 knockdown reduced intron retention and tumor suppressor WEE1 expression, which functions as a G2-M DNA damage checkpoint. We have identified DDX56 as a novel oncogene and prognostic biomarker of CRC that promotes alternative splicing of WEE1.

Real-Time Use of Artificial Intelligence in Identification of Diminutive Polyps During Colonoscopy: A Prospective Study.

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.

Identification of UHRF2 as a Negative Regulator of Epithelial-Mesenchymal Transition and Its Clinical Significance in Esophageal Squamous Cell Carcinoma.

OBJECTIVE: The involvement of epithelial-mesenchymal transition (EMT) in esophageal squamous cell carcinoma (ESCC) has not been fully elucidated. Here, we aimed to identify EMT-related genes associated with TGF-ß in ESCC and to clarify the role of these genes in the progression of ESCC. METHODS: EMT-related genes associated with TGF-ß expression were identified in patients with ESCC using microarray analysis and public datasets. The effects of ubiquitin-like with PHD and ring finger domains 2 (UHRF2) expression were analyzed in ESCC cell lines. Cell proliferation and invasion were measured using MTT and invasion assays, respectively. UHRF2 mRNA expression was also analyzed in 75 ESCC specimens to determine the clinical significance of UHRF2 in ESCC. RESULTS: Treatment of ESCC cell lines with TGF-ß increased UHRF2 expression. UHRF2 overexpression increased CDH1 (E-cadherin) expression and decreased invasive capacity. The 75 ESCC specimens were divided into the UHRF2 high-expression group (n = 61) and the UHRF2 low-expression group (n = 14). Low UHRF2 expression was significantly correlated with vascular invasion (p = 0.034) and was an independent prognostic factor for poor prognosis (p = 0.005). CONCLUSION: UHRF2 may be a negative regulator of EMT and a novel prognostic biomarker for ESCC.

Use of endocytoscopy for identification of sessile serrated adenoma/polyps and hyperplastic polyps by quantitative image analysis of the luminal areas.

BACKGROUND AND STUDY AIMS: Recent studies that used magnifying chromoendoscopy and endocytoscopy (EC) to investigate endoscopic features of sessile serrated adenoma/polyps (SSA/Ps) suggested that a dilated crypt opening was an important indicator of SSA/Ps. However, no studies to date have measured the actual extent of dilatation. Hence, we investigated retrospectively the luminal areas using EC to determine a cutoff value for differentiating SSA/Ps from hyperplastic polyps (HPs). PATIENTS AND METHODS: A total of 101 lesions, including 25 SSA/Ps, 66 HPs, and 10 normal mucosal samples, assessed by an integrated-type EC were collected. For each lesion, 1 image that showed the widest lumen was selected and the average area of the contiguous 3 lumens were calculated. The cutoff value differentiating SSAPs from HPs was determined by receiver operating curve (ROC) analysis. RESULTS: The mean luminal areas of SSA/Ps and HPs were 4152 µm 2 and 2117 µm 2 , respectively. ROC analysis found that a luminal area cutoff of 3068 µm 2 had a sensitivity of 80.0 %, a specificity of 77.3 %, an accuracy of 78.0 %, and an area under the ROC curve of 0.865. Furthermore, a cutoff of ≥ 556 µm 2 was found to accurately distinguish between HPs and normal mucosa (sensitivity 98.5 %, specificity 100 %, accuracy 98.7 %, and AUC 0.998). CONCLUSIONS: EC analysis of the luminal area is useful for differentiating between SSAPs and HPs. This approach could be adapted for computer-aided diagnosis of SSA/P.