Routine image-enhanced endoscopic surveillance for metachronous esophageal squamous cell neoplasms in head and neck cancer patients.

BACKGROUND: Esophageal squamous cell neoplasms (ESCNs) are common second primary tumors in patients with head and neck cancer. Image-enhanced endoscopy (IEE) with Lugol chromoendoscopy or magnifying narrow-band imaging both increase the detection of early ESCNs. No evidence-based ESCN surveillance program for head and neck cancer patients without a history of synchronous ESCNs exists. We aimed to evaluate the performance of an IEE surveillance program with magnifying narrow-band imaging endoscopy and Lugol chromoendoscopy. METHODS: From April 2016, we routinely used IEE with magnifying narrow-band imaging and Lugol chromoendoscopy to evaluate patients with head and neck cancer history. All patients who were negative for ESCNs at the first surveillance endoscopy and received at least 2 IEEs through December 2019 were included. Demographic profiles, clinical data, cancer characteristics, IEE results and pathology reports were analyzed. RESULTS: A total of 178 patients were included. Only 4 patients (2.2%) developed metachronous ESCNs during follow-up, all of whom received curative resection treatment. The interval for the development of metachronous ESCNs was 477 to 717 days. In multivariate Firth logistic regression and Kaplan‒Meier survival curve analysis, Lugol's voiding lesion type C had an increased risk of esophageal cancer development (adjusted odds ratio = 15.71; 95% confidence interval, 1.33-185.87, p = 0.029). Eight patients died during the study period, and none of them had metachronous ESCNs. CONCLUSIONS: IEE with magnifying narrow-band imaging and Lugol chromoendoscopy is an effective surveillance program in head and neck cancer patients without a history of ESCNs. Annual surveillance can timely detect early ESCNs with low ESCN-related mortality.

Microarchitectures of Barrett's esophagus associated with DNA methylation status.

Aim: DNA methylation is involved in esophageal adenocarcinoma (EAC) and Barrett's esophagus (BE). Microarchitectures of on-neoplastic BE associated with DNA methylation status were examined using magnifying narrow-band imaging (NBI) endoscopy. Patients and methods: Using biopsies from non-neoplastic BE without cancer (n = 66; N group), with EAC (n = 27; ADJ group) and EAC tissue (n = 22; T group), methylation of N33, DPYS, SLC16A12, miR124a3 and miR34bc genes were quantified. Magnifying NBI features of non-neoplastic BE were classified according to their morphologies. Results: The ADJ and T groups presented higher DNA methylation compared with the N group. Magnifying NBI endoscopic features of non-neoplastic BE also correlated with DNA methylation as an independent factor. Conclusion: Microarchitectures of BE visualized by magnifying NBI endoscopy correlated with DNA methylation.

Low-magnification narrow-band imaging for small gastric neoplasm detection on screening endoscopy.

Background and Aims: Microsurface patterns of the gastric mucosa can be observed using magnifying narrow-band imaging (M-NBI). However, the efficacy of M-NBI at low-magnification (LM-NBI) screening for detecting small gastric neoplasms is unclear. Methods: This prospective study was conducted at a single institution. LM-NBI, defined as minimal magnification that could reveal the microsurface pattern of the gastric mucosa, was performed after routine white-light imaging (WLI) observation of the stomach. Depending on the phase in which the neoplastic lesions were initially found, they were divided into the WLI group and the LM-NBI group, and the characteristics of these neoplastic lesions were investigated accordingly. Results: Sixty-five epithelial lesions (adenomas or noninvasive carcinomas) of 20 mm or less in diameter were identified in this study. Sixteen lesions were detected only with LM-NBI. Smaller lesions were detected using LM-NBI (P = .01). WLI took about 160 to 260 seconds, while LM-NBI required about 70 to 80 seconds. All lesions in the LM-NBI group had a background of map-like redness (n = 5) or atrophic/metaplastic mucosa (n = 11). Conclusions: LM-NBI was able to detect lesions overlooked by WLI, especially those in areas of map-like redness or atrophic/metaplastic mucosa of the stomach. Approximately one-quarter of newly diagnosed neoplasms were retrieved on routine examination during an extra 1.5 minutes.

Demarcation Line Determination for Diagnosis of Gastric Cancer Disease Range Using Unsupervised Machine Learning in Magnifying Narrow-Band Imaging.

BACKGROUND AND AIMS: It is important to determine an accurate demarcation line (DL) between the cancerous lesions and background mucosa in magnifying narrow-band imaging (M-NBI)-based diagnosis. However, it is difficult for novice endoscopists. We aimed to automatically determine the accurate DL using a machine learning method. METHODS: We used an unsupervised machine learning approach to determine the DLs. Our method consists of the following four steps: (1) an M-NBI image is segmented into superpixels using simple linear iterative clustering; (2) the image features are extracted for each superpixel; (3) the superpixels are grouped into several clusters using the k-means method; and (4) the boundaries of the clusters are extracted as DL candidates. The 23 M-NBI images of 11 cases were used for performance evaluation. The evaluation investigated the similarity of the DLs identified by endoscopists and our method, and the Euclidean distance between the two DLs was calculated. For the single case of 11 cases, the histopathological examination was also conducted to evaluate the proposed system. RESULTS: The average Euclidean distances for the 11 cases were 10.65, 11.97, 7.82, 8.46, 8.59, 9.72, 12.20, 9.06, 22.86, 8.45, and 25.36. The results indicated that the proposed method could identify similar DLs to those identified by experienced doctors. Additionally, it was confirmed that the proposed system could generate pathologically valid DLs by increasing the number of clusters. CONCLUSIONS: Our proposed system can support the training of inexperienced doctors as well as enrich the knowledge of experienced doctors in endoscopy.

Solitary Rectal Ulcer Syndrome Is Not Always Ulcerated: A Case Report.

Solitary rectal ulcer syndrome (SRUS) is a benign and chronic disorder well known in young adults that is characterized by a series of symptoms such as rectal bleeding, copious mucus discharge, prolonged excessive straining, perineal and abdominal pain, a feeling of incomplete defecation, constipation and, rarely, rectal prolapse. The etiology of this syndrome remains obscure, and the diagnosis is easily confused with that of other diseases, contributing to difficulties in treatment. We present a case of a 37-year-old male with a nonulcerated rectal lesion grossly resembling a superficial depressed rectal cancer misdiagnosed in another hospital and describe its appearance on endoscopy and in the analysis of its pathological manifestations. The aim of this case report is to report an easily misdiagnosed case of SRUS, which needs to be distinguished from superficial rectal cancer, which should be educational for endoscopists.

Standard vs magnifying narrow-band imaging endoscopy for diagnosis of Helicobacter pylori infection and gastric precancerous conditions.

BACKGROUND: Advances in endoscopic imaging enable the identification of patients at high risk of gastric cancer. However, there are no comparative data on the utility of standard and magnifying narrow-band imaging (M-NBI) endoscopy for diagnosing Helicobacter pylori (H. pylori) infection, gastric atrophy, and intestinal metaplasia. AIM: To compare the diagnostic performance of standard and M-NBI endoscopy for H. pylori gastritis and precancerous conditions. METHODS: In 254 patients, standard endoscopy findings were classified into mosaic-like appearance (type A), diffuse homogenous redness (type B), and irregular redness with groove (type C). Gastric mucosal patterns visualized by M-NBI were classified as regular round pits with polygonal sulci (type Z-1), more dilated and linear pits without sulci (type Z-2), and loss of gastric pits with coiled vessels (type Z-3). RESULTS: The diagnostic accuracy of standard and M-NBI endoscopy for H. pylori gastritis was 93.3% and 96.1%, respectively. Regarding gastric precancerous conditions, the accuracy of standard and M-NBI endoscopy was 72.0% vs 72.6% for moderate to severe atrophy, and 61.7% vs. 61.1% for intestinal metaplasia in the corpus, respectively. Compared to type A and Z-1, types B+C and Z-2+Z-3 were significantly associated with moderate to severe atrophy [odds ratio (OR) = 5.56 and 8.67] and serum pepsinogen I/II ratio of ≤ 3 (OR = 4.48 and 5.69). CONCLUSION: Close observation of the gastric mucosa by standard and M-NBI endoscopy is useful for the diagnosis of H. pylori gastritis and precancerous conditions.

Role of magnifying endoscopy with narrow-band imaging in the diagnosis of noninvasive gastric neoplasia.

BACKGROUND AND AIM: There are no globally approved, distinguishing criteria enabling the classification of gastric adenomas and intramucosal carcinomas for differential diagnosis of noninvasive neoplasia (NIN). METHODS: Next-generation sequencing of 50 cancer-related genes was undertaken on 68 pathologically diagnosed microdissected gastric neoplasms (25 adenomas, 27 intramucosal carcinomas, and 16 submucosal carcinomas) obtained during endoscopic submucosal dissection. Findings from magnifying endoscopy with narrow-band imaging (M-NBI) of 52 NINs (the 25 adenomas and 27 intramucosal carcinomas) were compared with these data. RESULTS: Among all 68 neoplasms, the most frequently mutated genes were APC (76% in adenoma, 11.1% in intramucosal carcinoma, and 0% in submucosal carcinoma; P < 0.001) and TP53 in intramucosal and submucosal carcinomas (8% in adenoma, 48.1% in intramucosal carcinoma, and 75% in submucosal carcinoma; P < 0.001). Dividing the NIN neoplasms into five groups according to their mutational status (A1: APC mutation, A2: APC + α mutation, B: APC + TP53 mutation, C: TP53 mutation, D: no mutation in either APC or TP53) resulted in almost identical diagnoses by pathology and M-NBI for groups A1 (12/13, 92%), C (12/13, 92%), and D (16/17, 94%) but not for groups A2 (3/7, 43%) or B (0/2, 0%). This finding implies that NINs with the APC + α mutation have carcinoma-like endoscopic features despite most being judged as adenomas by pathology. CONCLUSION: A diagnosis of NINs by pathology or M-NBI in the subset of gastric tumors classified by cancer-related mutations is not completely identical, suggesting the possible additional role of M-NBI in diagnosing NINs. Further studies are needed to confirm this.

Long-term relapse-free treatment with endoscopic submucosal dissection combined with magnifying narrow-band imaging for a pregnant patient with flat-type condyloma acuminatum: a case report.

Condyloma acuminatum, in the form of genital warts, usually results from an infection by human papillomavirus, one of the most common causes of sexually transmitted diseases. It develops after an incubation period of 3 weeks to 8 months after infection; flat lesions are significantly rare. Condyloma acuminatum is prevalent in the genitals, particularly in the anus of immunodeficient patients. This also occurs in women during menstrual period and pregnancy. Although a common treatment option for rectal and anal lesions, surgical resection is highly invasive and results in a high rate of recurrence. Recently, endoscopic submucosal dissection has been performed for anorectal lesions, but data on its long-term follow-up are not available. We report the case of an immunocompromised patient due to pregnancy who remained recurrence-free 27 months after en-bloc resection by endoscopic submucosal dissection, with adequate visualisation of the flat lesion's safety margin, combined with magnifying narrow-band imaging.

Exploration of an effective training system for diagnosis of superficial esophageal squamous cell carcinoma with magnifying narrow-band imaging: Prospective research.

BACKGROUND AND AIMS: The aim was to explore an effective training system for diagnosis of superficial esophageal squamous cell carcinoma (SESCC) and its staging with magnifying narrow-band imaging (M-NBI). PATIENTS AND METHODS: Fifteen endoscopists with no or less M-NBI experience participated in this training, which consisted of four stages and five teaching methods (M-NBI classification criterion, case analysis, hands-on operation, error correction and SESCC pathological knowledge). M-NBI images were evaluated and diagnostic accuracy was analyzed. RESULTS: After training, the accuracy of distinguishing neoplastic esophageal from non-neoplastic (0.58 ± 0.16 vs. 0.95 ± 0.05, P = 0.000) and diagnosing SESCC staging (0.25 ± 0.26 vs. 0.89 ± 0.08, P = 0.000) with M-NBI were significantly increased. Participants with no M-NBI experience achieve equivalent diagnostic accuracy with less experienced trainees after the training (0.91 ± 0.08 vs. 0.92 ± 0.04, P = 0.816). Besides, diagnosis of MM (muscularis mucosa)/SM1 (submucosal) staging tumors (Stage I, 0.47 ± 0.15; Stage II-III-IV, 0.76 ± 0.12) with M-NBI was difficult for trainees and should be the focus of this training. Every teaching method could improve the diagnostic accuracy for esophageal lesions, especially for case analysis (from 0.59 ± 0.10 to 0.85 ± 0.08, P = 0.000). In addition, the average operation score for trainees was significantly increased after hands-on teaching (60.40 ± 11.11 vs. 91.80 ± 4.28, P = 0.0001). CONCLUSIONS: For novices, this training system showed efficient performance for diagnosing SESCC staging with M-NBI. Diagnosing MM/SM1 staging SESCC was difficult for beginners, and should be the focus of training.

Comparison of the diagnostic effect of early gastric cancer between magnifying blue laser imaging model and magnifying narrow-band imaging model based on deep learning / 中华消化杂志

Objective:To develop early gastric cancer (EGC) detection system of magnifying blue laser imaging (ME-BLI) model and magnifying narrow-band imaging (ME-NBI) model based on deep convolutional neural network, to compare the performance differences of the two models and to explore the effects of training methods on the accuracy.Methods:The images of benign gastric lesions and EGC under ME-BLI and ME-NBI were respectively collected. A total of five data sets and three test sets were collected. Data set 1 included 2 024 noncancerous lesions and 452 EGC images under ME-BLI. Data set 2 included 2 024 noncancerous lesions and 452 EGC images under ME-NBI. Data set 3 was the combination of data set 1 and 2 (a total of 4 048 noncancerous lesions and 904 EGC images under ME-BLI and ME-NBI). Data set 4: on the basis of data set 2, another 62 noncancerous lesions and 2 305 EGC images under ME-NBI were added (2 086 noncancerous lesions and 2 757 EGC images under ME-NBI). Data set 5: on the basis of data set 3, another 62 noncancerous lesions and 2 305 EGC images under ME-NBI were added(4 110 noncancerous lesions and 3 209 EGC images under ME-NBI and ME-BLI). Test set A included 422 noncancerous lesions and 197 EGC images under ME-BLI. Test set B included 422 noncancerous lesions and 197 EGC images under ME-NBI. Test set C was the combination of test set A and B (844 noncancerous and 394 EGC images under ME-BLI and ME-NBI). Five models were constructed according to these five data sets respectively and their performance was evaluated in the three test sets. Per-lesion video was collected and used to compare the performance of deep convolutional neural network models under ME-BLI and ME-NBI for the detection of EGC in clinical environment, and compared with four senior endoscopy doctors. The primary endpoint was the diagnostic accuracy of EGG, sensitivity and specificity. Chi-square test was used for statistical analysis.Results:The performance of model 1 was the best in test set A with the accuracy, sensitivity and specificity of 76.90% (476/619), 63.96% (126/197) and 82.94% (350/422), respectively. The performance of model 2 was the best in test set B with the accuracy, sensitivity and specificity of 86.75% (537/619), 92.89% (183/197) and 83.89% (354/422), respectively. The performance of model 3 was the best in test set B with the accuracy, sensitivity and specificity of 86.91% (538/619), 84.26% (166/197) and 88.15% (372/422), respectively. The performance of model 4 was the best in test set B with the accuracy, sensitivity and specificity of 85.46% (529/619), 95.43% (188/197) and 80.81% (341/422), respectively. The performance of model 5 was the best in test set B, with the accuracy, sensitivity and specificity of 83.52% (517/619), 96.95% (191/197) and 77.25% (326/422), respectively. In terms of image recognition of EGC, the accuracy of models 2 to 5 was higher than that of model 1, and the differences were statistically significant ( χ2=147.90, 149.67, 134.20 and 115.30, all P<0.01). The sensitivity and specificity of models 2 and 3 were higher than those of model 1, the specificity of model 2 was lower than that of model 3, and the differences were statistically significant ( χ2=131.65, 64.15, 207.60, 262.03 and 96.73, all P < 0.01). The sensitivity of models 4 and 5 was higher than those of models 1 to 3, and the specificity of models 4 and 5 was lower than those of models 1 to 3, and the differences were statistically significant ( χ2=151.16, 165.49, 71.35, 112.47, 132.62, 153.14, 176.93, 74.62, 14.09, 15.47, 6.02 and 5.80, all P<0.05). The results of video test based on lesion showed that the average accuracy of doctors 1 to 4 was 68.16%. And the accuracy of models 1 to 5 was 69.47% (66/95), 69.47% (66/95), 70.53% (67/95), 76.84% (73/95) and 80.00% (76/95), respectively. There were no significant differences in the accuracy among models 1 to 5 and between models 1 to 5 and doctors 1 to 4 (all P>0.05). Conclusions:ME-BLI EGC recognition model based on deep learning has good accuracy, but the diagnostic effecacy is sligntly worse than that of ME-NBI model. The effects of EGC recognition model of ME-NBI combined with ME-BLI is better than that of a single model. A more sensitive ME-NBI model can be obtained by increasing the number of ME-NBI images, especially the images of EGG, but the specificity is worse.

Histological subtype of gastric adenocarcinoma: two cases of mixed fundic and pyloric mucosa-type adenocarcinoma.

Adenocarcinomas with differentiation towards fundic or pyloric glands are rare histological subtypes. We herein describe two cases of new histological subtypes: mixed fundic and pyloric mucosa-type adenocarcinoma detected in Helicobacter pylori uninfected patients. The first patient was a woman in her 40s. A glossy, reddish, nodular lesion with a flat elevated whitish area was detected at the gastric fundus. When the nodular lesion was visualised with magnifying narrow-band imaging (M-NBI), an absent microvascular pattern plus an irregular microsurface pattern with a demarcation line was observed. The second patient was a woman in her 60s. A glossy, reddish, elevated lesion was detected at the gastric body. M-NBI finding was a regular microvascular pattern plus a regular microsurface pattern with a demarcation line. Histological examination of the resected specimens from both cases showed a very well- to well-differentiated adenocarcinoma which has differentiation towards the mixed fundic and pyloric mucosa. The histological and serological findings of both cases indicated the absence of H. pylori infection. The present two cases demonstrate further evidence of a new histological subtype of gastric adenocarcinoma: mixed fundic and pyloric mucosa-type adenocarcinoma, which has distinct characteristic endoscopic findings.

Intelligent diagnosis of gastric intestinal metaplasia based on convolutional neural network and limited number of endoscopic images.

BACKGROUND: Gastric intestinal metaplasia (GIM) is a precancerous lesion of gastric cancer. Currently, diagnosis of GIM is based on the experience of a physician, which is liable to interobserver variability. Thus, an intelligent diagnostic (ID) system, based on narrow-band and magnifying narrow-band images, was constructed to provide objective assistance in the diagnosis of GIM. METHOD: We retrospectively collected 1880 endoscopic images (1048 GIM and 832 non-GIM) via biopsy from 336 patients confirmed histologically as GIM or non-GIM, from the Kiang Wu Hospital, Macau. We developed an ID system with these images using a modified convolutional neural network algorithm. A separate test dataset containing 477 pathologically confirmed images (242 GIM and 235 non-GIM) from 80 patients was used to test the performance of the ID system. Experienced endoscopists also examined the same test dataset, for comparison with the ID system. One of the challenges faced in this study was that it was difficult to obtain a large number of training images. Thus, data augmentation and transfer learning were applied together. RESULTS: The area under the receiver operating characteristic curve was 0.928 for the pre-patient analysis of the ID system, while the sensitivities, specificities, and accuracies of the ID system against those of the human experts were (91.9% vs. 86.5%, p-value = 1.000) (86.0% vs. 81.4%, p-value = 0.754), and (88.8% vs. 83.8%, p-value = 0.424), respectively. Even though the three indices of the ID system were slightly higher than those of the human experts, there were no significant differences. CONCLUSIONS: In this pilot study, a novel ID system was developed to diagnose GIM. This system exhibits promising diagnostic performance. It is believed that the proposed system has the potential for clinical application in the future.

Additional effect of magnifying narrow-band imaging on estimating the invasion depth of superficial esophageal cancer.

BACKGROUND AND AIM: To investigate whether assessment by magnifying narrow-band imaging (M-NBI) based on the classification of the Japan Esophageal Society provides additional value to the estimation of the invasion depth of superficial esophageal squamous cell carcinoma (SCC) compared with assessment by white light endoscopy (WLE) alone. METHODS: Endoscopic images of 211 consecutive superficial esophageal SCCs resected by endoscopic submucosal dissection were separated into WLE and M-NBI images. Depth estimation was performed independently by five evaluators using the numerical depth estimation scale (0 = epithelium (EP)/lamina propria (LPM), 1 = EP/LPM > muscularis mucosa (MM)/shallow submucosa (SM1), 2 = MM/SM1 > EP/LPM, 3 = MM/SM1, 4 = MM/SM1 > deep submucosa (SM2), 5 = SM2 > MM/SM1, 6 = SM2), using primarily WLE images (step 1), and subsequently both WLE and M-NBI images (step 2). The discordance scores, determined by the average of the five evaluators' difference between the estimated score (from 0 to 6) and pathological score (0 for histologically proven EP/LPM, 3 for MM/SM1, and 6 for SM2), were analyzed in steps 1 and 2. RESULTS: The discordance scores significantly decreased in step 2 (0.53 ± 0.06) compared with those in step 1 (0.79 ± 0.07) (P < 0.001). When the discordance score < 1.5 was regarded as a clinically correct diagnosis, the rate of the clinically correct diagnosis significantly increased in step 2 compared with that in step 1 (81% to 91%, P < 0.001). CONCLUSION: M-NBI has an additive value for estimating the invasion depth of superficial esophageal SCCs.

A case of celiac disease with type I enteropathy-associated T-cell lymphoma in a Japanese male patient.

A 45-year-old Japanese male patient who was diagnosed with celiac disease (CeD) developed type I enteropathy-associated T-cell lymphoma (EATL). In 2013, the patient was admitted to our hospital with worsening of diarrhea and weight loss. Pathological examination of biopsy specimens from the duodenum and ileum led to a diagnosis of suspected EATL. A previous total colonoscopy (TCS) indicated villous atrophy in the terminal ileum. The patient was changed to a gluten-free diet, and the nutritional status gradually improved. In September 2014, he experienced acute right lower abdominal pain. He underwent urgent surgery, and a perforation was identified in the ileum. A diagnosis of type I EATL was made following histopathological examination. After eight courses of CHOP therapy, the patient entered complete remission. TCS and esophagogastroduodenoscopy with magnifying narrow-band imaging performed in 2015 identified villous regrowth in the distal ileum and duodenum. Capsule endoscopy also found villous regrowth in the entire small intestine. To our knowledge, this is the first case of type I EATL following CeD with villous atrophy before EATL occurrence in a Japanese HLA-DQ2 carrier. The possibility of type I EATL occurring after CeD should be recognized, although CeD is quite rare in Japan.

Efficacy of Magnifying Narrow Band Imaging for Delineating Horizontal Margins of Early Gastric Cancer.

BACKGROUND/AIMS: The aim of this study was to evaluate the diagnostic accuracy of magnifying narrow-band imaging (M-NBI) with histopathological confirmation in identifying the demarcation line (DL) of early gastric cancer (EGC). METHODS: EGCs resected by endoscopic submucosal dissection after identifying the DL using M-NBI following histopathological confirmation were included. After determining the DL for the entire EGC lesion using M-NBI, at least 4 biopsies were taken from non-cancerous tissues outside the EGC lesion for histopathological confirmation. RESULTS: A total of 330 EGCs were analyzed in this study. The rate of biopsy-negative and negative horizontal margin were 96.7% (319/330) and 97.9% (323/330) in EGC respectively. Tumors larger than 20 mm showed a higher risk for showing remnant cancer cells on biopsies taken outside the DL. Risk factors for a positive horizontal resection margin were tumor size > 20 mm and moderately or poorly differentiated adenocarcinomas. CONCLUSION: The assessment of demarcation of EGC using M-NBI was excellent in well-differentiated (WD) adenocarcinoma and lesions below 20 mm in size. However, histopathological confirmation is needed to assess the demarcation of non-WD adenocarcinomas and EGC over 20 mm in size.

Prediction of colorectal tumor grade and invasion depth through narrow-band imaging scoring.

AIM: To determine the usefulness of assigning narrow-band imaging (NBI) scores for predicting tumor grade and invasion depth in colorectal tumors. METHODS: A total of 161 colorectal lesions were analyzed from 138 patients who underwent endoscopic or surgical resection after conventional colonoscopy and magnifying endoscopy with NBI. The relationships between the surface and vascular patterns of the lesions, as visualized with NBI, and the tumor grade and depth of submucosa (SM) invasion were determined histopathologically. Scores were assigned to distinct features of the surface microstructures of tubular and papillary-type lesions. Using a multivariate analysis, a model was developed for predicting the tumor grade and depth of invasion based on NBI-finding scores. RESULTS: NBI findings that correlated with a high tumor grade were associated with the "regular/irregular" (P < 0.0001) surface patterns and the "avascular area" pattern (P = 0.0600). The vascular patterns of "disrupted vessels" (P = 0.0714) and "thick vessels" (P = 0.0133) but none of the surface patterns were associated with a depth of invasion of ≥ 1000 µm. In our model, a total NBI-finding score ≥ 1 was indicative of a high tumor grade (sensitivity: 0.97; specificity: 0.24), and a total NBI-finding score ≥ 9 (sensitivity: 0.56; specificity: 1.0) was predictive of a SM invasion depth ≥ 1000 µm. Scores less than these cutoff values signified adenomas and a SM invasion depth < 1000 µm, respectively. Associations were also noted between selected NBI findings and tumor tissue architecture and histopathology. CONCLUSION: Our multivariate statistical model for predicting tumor grades and invasion depths from NBI-finding scores may help standardize the diagnosis of colorectal lesions and inform therapeutic strategies.

Diagnostic performance of routine esophagogastroduodenoscopy using magnifying endoscope with narrow-band imaging for gastric cancer.

BACKGROUND AND AIM: In Japan, an increase in the number of routine esophagogastroduodenoscopy procedures is expected because several studies have reported that endoscopy screening has reduced gastric cancer mortality. Magnifying narrow-band imaging has been reported to be effective for accurate diagnosis of gastric abnormalities such as cancers, adenomas, and intestinal metaplasia. However, the efficacy of this method in routine esophagogastroduodenoscopy has not been clarified. METHODS: We divided 3763 patients into two groups. The non-magnification group included 1842 patients who underwent endoscopy screening using GIF-H260/LUCERA-SPECTRUM between October 2014 and February 2015, whereas the magnification group included 1921 patients who underwent screening using GIF-H290Z/LUCERA-ELITE between March 2015 and May 2015. In the magnification group, diagnosis of cancer was conducted using the VS classification system. We did not carry out a biopsy when results were confirmed as non-cancer using magnifying narrow-band imaging. If cancer was diagnosed, or when a cancer or non-cancer diagnosis was difficult, we carried out a biopsy. We analyzed and compared the diagnostic performance between the two groups. RESULTS: Gastric biopsy rate was significantly lower in the magnification group (29%) than in the non-magnification group (41%) (P < 0.001). Positive predictive value (PPV) for gastric cancer was significantly higher in the magnification group (5.5%) than in the non-magnification group (2.5%) (P < 0.001). Furthermore, PPV for gastric epithelial neoplasia was significantly higher in the magnification group (7.9%) than in the non-magnification group (3.2%) (P < 0.001). CONCLUSION: Magnifying narrow-band imaging improves the diagnostic performance of routine esophagogastroduodenoscopy.

Usefulness of confocal laser endomicroscopy to diagnose ulcerative colitis-associated neoplasia.

Chromoendoscopy, narrow-band imaging (NBI), and confocal laser endomicroscopy (CLE) have been introduced in ulcerative colitis (UC)-associated neoplasia surveillance. We aimed to determine the ability of CLE to differentiate among UC-associated neoplasia (differentiated type or undifferentiated type), sporadic adenoma, and circumscribed regenerative lesions. Of 665 patients with UC, we carried out probe-based CLE (pCLE) on 12 patients with suspected UC-associated neoplasia in addition to magnifying chromoendoscopy with crystal violet and NBI. We compared pCLE findings with pathological diagnoses. pCLE could differentiate UC-associated differentiated cancer from other pathologies such as solitary adenoma and non-neoplastic circumscribed regenerative lesions on the basis of back-to-back orientation of crypts (P = 0.048), and UC-associated undifferentiated cancer from other pathologies on the basis of dark trabecular architecture (P = 0.015). Sensitivity, specificity, and accuracy of combination of back-to-back orientation of crypts and dark trabecular architecture for carcinoma or dysplasia were 100%, 83%, and 92%, respectively. In vivo microscopic observation with pCLE was helpful to evaluate the suspected UC-associated neoplasia.

Association between white opaque substance under magnifying colonoscopy and lipid droplets in colorectal epithelial neoplasms.

AIM: To examine the association between white opaque substance (WOS) and histologically verified lipid droplets in colorectal epithelial neoplasms. METHODS: We reviewed colonoscopy records at our institution from 2014 to 2016 and identified cases of endoscopically or surgically resected colorectal epithelial neoplasms observed by magnifying narrow-band imaging (M-NBI) colonoscopy. Immunohistochemistry was used to stain tumors with a monoclonal antibody specific to adipophilin as a marker of lipids. The expression and distribution of adipophilin were compared between WOS-positive and WOS-negative lesions and among tumors classified by histologic type and depth of invasion. RESULTS: Under M-NBI colonoscopy, 81 lesions were positive for WOS and 48 lesions were negative for WOS. The rate of adipophilin expression was significantly higher in WOS-positive lesions (95.1%) than in WOS-negative lesions (68.7%) (P = 0.0001). The incidence of deep adipophilin expression was higher in WOS-positive lesions (24.7%) than in WOS-negative lesions (4.2%) (P = 0.001). The incidence of deep expression was predominant among cancers with massive submucosal invasion (62.5%) compared to adenoma (7.2%) and high-grade dysplasia or cancers with slight submucosal invasion (12.7%) (P = 0.0001). CONCLUSION: The distribution of lipid droplets may be closely associated with the visibility of WOS under M-NBI colonoscopy, and with histologic grade and depth of tumor invasion.

An alternative option for "resect and discard" strategy, using magnifying narrow-band imaging: a prospective "proof-of-principle" study.

BACKGROUND: The "resect and discard" strategy is beneficial for cost savings on screening and surveillance colonoscopy, but it has the risk to discard lesions with advanced histology or small invasive cancer (small advanced lesion; SALs). The aim of this study was to prove the principle of new "resect and discard" strategy with consideration for SALs using magnifying narrow-band imaging (M-NBI). METHODS: Patients undergoing colonoscopy at a tertiary center were involved in this prospective trial. For each detected polyp <10 mm, optical diagnosis (OD) and virtual management ("leave in situ", "discard" or "send for pathology") were independently made using non-magnifying NBI (N-NBI) and M-NBI, and next surveillance interval were predicted. Histological and optical diagnosis results of all polyps were compared. RESULTS: While the management could be decided in 82% of polyps smaller than 10 mm, 24/31 (77%) SALs including two small invasive cancers were not discarded based on OD using M-NBI. The sensitivity [90% confidence interval (CI)] of M-NBI for SALs was 0.77 (0.61-0.89). The risk for discarding SALs using N-NBI was significantly higher than that using M-NBI (53 vs. 23%, p = 0.02). The diagnostic accuracy (95% CI) of M-NBI in distinguishing neoplastic from non-neoplastic lesions [0.88 (0.86-0.90)] was significantly better than that of N-NBI [0.84 (0.82-0.87)] (p = 0.005). CONCLUSIONS: The results of our study indicated that our "resect and discard" strategy using M-NBI could work to reduce the risk for discarding SALs including small invasive cancer (UMIN-CTR, UMIN000003740).