Narrow-band imaging without high magnification to differentiate polyps during real-time colonoscopy: improvement with experience

Endoscopic Assessment of Colorectal Polyps

Colorectal cancer is the third most common cancer among men and the second among women. In the United States alone, there are 150,000 cases diagnosed each year. Colonoscopy remains the best method for identifying, evaluating, and intervening on patients with precancerous lesions. Multiple guidelines and techniques are available to assist the endoscopist with accurate diagnosis of these lesions. These include the Paris, Narrow-Band Imaging (NBI) International Colorectal Endoscopic (NICE), Japan NBI Expert Team (JNET), Kudo, Hiroshima, and Shudo classifications which utilize techniques such as chromoendoscopy, narrow-band imaging, and endocytoscopy to evaluate pit pattern and surface morphology. Utilization of these tools can help the endoscopist predict the cytology of a colonic lesion and select the most appropriate method for resection while maximizing organ preservation.

Artificial Intelligence in endoscopy: A future poll

Artificial Intelligence [AI] has been a trendy topic in recent years, with many developed medical applications. In gastrointestinal endoscopy, AI systems include computer-assisted detection [CADe] for lesion detection as bleedings and polyps and computer-assisted diagnosis [CADx] for optical biopsy and lesion characterization. The technology behind these systems is based on a computer algorithm that is trained for a specific function. This function could be to recognize or characterize target lesions such as colonic polyps. Moreover, AI systems can offer technical assistance to improve endoscopic performance as scope insertion guidance. Currently, we believe that such technologies still lack legal and regulatory validations as a large sector of doctors and patients have concerns. However, there is no doubt that these technologies will bring significant improvement in the endoscopic management of patients as well as save money and time.

Economic impact of implementing optical diagnosis with a "resect and discard" strategy within the English Bowel Cancer Screening Programme: findings from the DISCARD3 study

BACKGROUND AND AIMS

Advances in endoscopic technology, such as narrow-band imaging and high-definition colonoscopes, offer the potential for optical diagnosis (OD) with a "resect and discard" (RD) strategy for diminutive (≤5 mm) and small (6-9 mm) colorectal polyps. This could help alleviate the huge cost and time burden required for histopathology. The aim of this study was to conduct an economic analysis of an RD strategy within the English Bowel Cancer Screening Programme (BCSP).

METHODS

A decision tree was designed to compare an RD strategy with standard histopathology for patients included in the DISCARD3 study (Detect InSpect ChAracterise Resect and Discard 3) and was extrapolated to a national BCSP patient cohort.

RESULTS

Of the 525 patients in the DISCARD3 study, 354 were assessed for surveillance intervals (after excluding cases with colorectal cancer and at least 1 polyp >10 mm). Of 354 patients, 269 had polyps, of which 182 had only diminutive polyps, 77 had both small and diminutive polyps, and 10 had only small polyps. Surveillance interval concordance was 97.9% in patients with at least 1 diminutive polyp and 98.7% in patients with at least 1 diminutive or small polyp. In DISCARD3, an RD approach was found to reduce overall direct healthcare costs by $44,285.63 (-72.3%) for patients with diminutive polyps or by $66,129.13 (-75.0%) for patients with diminutive or small polyps. When extrapolated to the entire English BCSP, the annual savings were almost $3 million for patients with diminutive polyps or $4.3 million for patients with diminutive or small polyps, after adjusting for the costs of an OD quality assurance process.

CONCLUSIONS

OD with an RD strategy for diminutive and small polyps during BCSP colonoscopy would offer substantial cost savings without adversely affecting surveillance interval concordance.

Updates in narrow-band imaging for colorectal polyps: Narrow-band imaging generations, detection, diagnosis, and artificial intelligence

Narrow-band imaging (NBI) is an optical digital enhancement method that allows the observation of vascular and surface structures of colorectal lesions. Its usefulness in the detection and diagnosis of colorectal polyps has been demonstrated in several clinical trials and the diagnostic algorithms have been simplified after the establishment of endoscopic classifications such as the Japan NBI Expert Team classification. However, there were issues including lack of brightness in the earlier models, poor visibility under insufficient bowel preparation, and the incompatibility of magnifying endoscopes in certain endoscopic platforms, which had impeded NBI from becoming standardized globally. Nonetheless, NBI continued its evolution and the newest endoscopic platform launched in 2020 offers significantly brighter and detailed images. Enhanced visualization is expected to improve the detection of polyps while universal compatibility across all scopes including magnifying endoscopy will promote the global standardization of magnifying diagnosis. Therefore, knowledge related to magnifying colonoscopy will become essential as magnification becomes standardly equipped in future models, although the advent of computer-aided diagnosis and detection may greatly assist endoscopists to ensure quality of practice. Given that most endoscopic departments will be using both old and new models, it is important to understand how each generation of endoscopic platforms differ from each other. We reviewed the advances in the endoscopic platforms, artificial intelligence, and evidence related to NBI essential for the next generation of endoscopic practice.

Implementation of optical diagnosis with a "resect and discard" strategy in clinical practice: DISCARD3 study

BACKGROUND AND AIMS

Optical diagnosis (OD) of polyps can be performed with advanced endoscopic imaging. For high-confidence diagnoses, a "resect and discard" strategy could offer significant histopathology time and cost savings. The implementation threshold is a ≥90% OD-histology surveillance interval concordance. Here we assessed the OD learning curve and feasibility of a resect and discard strategy for ≤5-mm and <10-mm polyps in a bowel cancer screening setting.

METHODS

In this prospective feasibility study, 8 bowel cancer screening endoscopists completed a validated OD training module and performed procedures. All <10-mm consecutive polyps had white-light and narrow-band images taken and were given high- or low-confidence diagnoses until 120 high-confidence ≤5-mm polyp diagnoses had been performed. All polyps had standard histology. High-confidence OD errors underwent root-cause analysis. Histology and OD-derived surveillance intervals were calculated.

RESULTS

Of 565 invited patients, 525 patients were included. A total of 1560 <10-mm polyps underwent OD and were resected and retrieved (1329 ≤5 mm and 231 6-9 mm). There were no <10-mm polyp cancers. High-confidence OD was accurate in 81.5% of ≤5-mm and 92.8% of 6-9-mm polyps. Sensitivity for OD of a ≤5-mm adenoma was 93.0% with a positive predictive value of 90.8%. OD-histology surveillance interval concordance for ≤5-mm OD was 91.3% (209/229) for U.S. Multi-Society Task Force, 98.3% (225/229) for European Society of Gastrointestinal Endoscopy, and 98.7% (226/229) for British Society of Gastroenterology guidelines, respectively.

CONCLUSIONS

A resect and discard strategy for high-confidence ≤5-mm polyp OD in a group of bowel cancer screening colonoscopists is feasible and safe, with performance exceeding the 90% surveillance interval concordance required for implementation in clinical practice. (Clinical trial registration number: NCT04710693.).

Performance of Computer-Aided Detection and Diagnosis of Colorectal Polyps Compares to That of Experienced Endoscopists

BACKGROUND

Differential diagnosis of neoplasms and non-neoplasms is crucial in ensuring appropriate and proper medical management for patients undergoing colonoscopy. Diagnostic ability can vary, depending on the colonoscopist's experience. To overcome this issue, artificial intelligence (AI) may be effective.

AIMS

To assess the performance of a computer-aided detection (CADe) and a computer-aided diagnosis (CADx) system for the detection and characterization of colorectal polyps by comparing their data with those of experienced endoscopists.

METHODS

This retrospective, still image-based validation study was conducted at three Japanese medical centers. A total of 579 white-light images (WLIs) and 605 linked color images (LCIs) were used for testing the CADe and 308 WLIs and 296 blue laser/light images (BLIs) for testing the CADx. The performances of the CADe and CADx systems were assessed and compared with the correct answers provided by three experienced endoscopists.

RESULTS

CADe in WLI demonstrated a sensitivity of 94.5% (95% confidence interval (CI), 92.0-96.9%) and a specificity of 87.2% (84.5-89.9%). CADe in LCI demonstrated a sensitivity of 96.0% (93.9-98.1%) and a specificity of 85.1% (82.3-87.9%). CADx in WLI demonstrated a sensitivity of 95.5% (92.9-98.1%) and a specificity of 84.4% (73.4-91.5%), resulting in an accuracy of 93.2% (90.4-96.0%). CADx in BLI showed a sensitivity of 96.3% (93.9-98.7%) and a specificity of 88.7% (77.1-95.1%), resulting in an accuracy of 94.9% (92.4-97.4%).

CONCLUSIONS

CADe and CADx demonstrated sufficient diagnostic performance to support the use of an AI system.

Accuracy and inter-observer agreement of the nice and kudo classifications of superficial colonic lesions: a comparative study

PURPOSE

For superficial colonic lesions, the NICE and Kudo classifications are used in the in vivo prediction of histology and as guide to therapy. The NICE system derives information from unmagnified NBI endoscopic images. The Kudo one necessitates a magnification, but, as this tool is not commonly available, it is applied also to characterize unmagnified pictures to compare their diagnostic performances.

METHODS

We conducted a prospective comparison of the NICE versus the Kudo classification for the differential diagnosis of colonic polyps taking histology as the gold standard. The inter-observer agreement for both classifications among 11 colonoscopists was also evaluated. Short unmagnified NBI videoclips of 64 colonic polyps were sent twice to the participants. In the first round, they classified the lesions according to the NICE classification; 4 months later, the same videos were assessed with the Kudo system. The diagnosis provided by the participants was grouped in non-neoplastic, non-invasive neoplasia, invasive neoplasia.

RESULTS

Overall, the diagnostic accuracy was 82% (95%CI: 79-85) with the NICE system and 81% (95%CI: 78-84) with the Kudo one (ρ = 0.78). The accuracy of the NICE classification for non-neoplastic lesions was greater compared with the Kudo's (ρ = 0.03). Sensitivity sub-analyses revealed a higher ability of the NICE in distinguishing between neoplastic vs. non-neoplastic lesions (ρ = 0.01). The overall inter-rater agreement did not differ when the classifications were compared.

CONCLUSION

The NICE and the Kudo classifications might be considered comparable. Our data could allow the use of the NBI Kudo classification even in those centers where magnification is not available.

Training methods in optical diagnosis and characterization of colorectal polyps: a systematic review and meta-analysis

Background and study aims  Correct optical diagnosis of colorectal polyps is crucial to implement a resect and discard strategy. Training methods have been proposed to reach recommended optical diagnosis thresholds. The aim of our study was to present a systematic review and meta-analysis on optical diagnosis training. Methods  PubMed/Medline and Cochrane databases were searched between 1980 and October 2019 for studies reporting outcomes on optical diagnosis training of colorectal polyps. The primary outcome was optical diagnosis accuracy compared to histological analysis pre-training and post-training intervention. Subgroup analyses of experienced/trainee endoscopists, training methods, and small/diminutive polyps were included. Results  Overall, 16 studies met inclusion criteria, analyzing the impact of training on 179 endoscopists. Pre-training accuracy was 70.3 % (6416/9131 correct diagnoses) whereas post-training accuracy was 81.6 % (7416/9213 correct diagnoses) (risk ratio [RR] 1.17; 95 % confidence interval [CI]: 1.09-1.24, P  < 0.001). In experienced endoscopists, accuracy improved from 69.8 % (3771/5403 correct diagnoses) to 82.4 % (4521/5485 correct diagnoses) (RR 1.20; 95 % CI: 1.11-1.29, P  < 0.001). Among trainees, accuracy improved from 69.6 % (2645/3803 correct diagnoses) to 78.8 % (2995/3803 correct diagnoses) (RR 1.14; 95 % CI 1.06-1.24, P  < 0.001). In the small/diminutive polyp subgroup, accuracy improved from 68.1 % (3549/5214 correct diagnoses) to 77.1 % (4022/5214 correct diagnoses) in (RR 1.16 95 % CI 1.08-1.24 P  < 0.001). On meta-regression analysis, the improvement in accuracy did not differ between computerized vs. didactic training approaches for experienced ( P  = 0.792) and trainee endoscopists ( P  = 0.312). Conclusions  Optical diagnosis training is effective in improving accuracy of histology prediction in colorectal polyps. Didactic and computer-based training show comparable effectiveness in improving diagnostic accuracy.

Artificial Intelligence in Colorectal Polyp Detection and Characterization

BACKGROUND

Over the past 20 years, the advancement of artificial intelligence (AI) and deep learning (DL) has allowed for fast sorting and analysis of large sets of data. In the field of gastroenterology, colorectal screening procedures produces an abundance of data through video and imaging. With AI and DL, this information can be used to create systems where automatic polyp detection and characterization is possible. Convoluted Neural Networks (CNNs) have proven to be an effective way to increase polyp detection and ultimately adenoma detection rates. Different methods of polyp characterization of being hyperplastic vs. adenomatous or non-neoplastic vs. neoplastic has also been investigated showing promising results.

FINDINGS

The rate of missed polyps on colonoscopy can be as high as 25%. At the beginning of the 2000s, hand-crafted machine learning (ML) algorithms were created and trained retrospectively on colonoscopy images and videos, achieving high sensitivity, specificity, and accuracy of over 90% in many of the studies. Over time, the advancement of DL and CNNs has allowed algorithms to be trained on non-medical images and applied retrospectively to colonoscopy videos and images with similar results. Within the past few years, these algorithms have been applied in real-time colonoscopies and has shown mixed results, one showing no difference while others showing increased polyp detection.Various methods of polyp characterization have also been investigated. Through AI, DL, and CNNs polyps can be identified has hyperplastic/adenomatous or non-neoplastic/neoplastic with high sensitivity, specificity, and accuracy. One of the research areas in polyp characterization is how to capture the polyp image. This paper looks at different modalities of characterizing polyps such as magnifying narrow band imaging (NBI), endocytoscopy, laser-induced florescent spectroscopy, auto-florescent endoscopy, and white-light endoscopy.

CONCLUSIONS

Overall, much progress has been made in automatic detection and characterization of polyps in real time. Barring ethical or mass adoption setbacks, it is inevitable that AI will be involved in the field of GI, especially in colorectal polyp detection and identification.

The value of three narrow-band imaging model in the diagnosis of small colorectal polyps

This prospective study was aimed to evaluate the clinical value of narrow-band imaging (NBI), magnification endoscopy with narrow-band imaging (NBIME) and magnification endoscopy with acetic acid enhancement and narrow-band imaging (AA-NBIME) in the diagnosis of small colorectal polyps. We studied 261 small colorectal polyps from 122 patients with the use of above three techniques. Lesions were resected for histopathological analysis. The endoscopic images were independently reviewed by three experts and three non-experts and the diagnostic accuracy and image definition were compared among the modalities. The “experts-agreed” diagnostic accuracy was 87.7% for NBI versus 91.6% for NBIME versus 94.6% for AA-NBIME. The “non-experts-agreed” diagnostic accuracy was 80.1% for NBI versus 84.3% for NBIME versus 89.3% for AA-NBIME. All experts and non-experts diagnosed the small colorectal polyps statistically more accurately with AA-NBIME than NBI (P < 0.05). In all three modalities, the expert group’s diagnostic accuracies were statistically significantly higher compared with the non-expert group. For experts, the Kappa values for AA-NBIME, NBIME and NBI diagnosis were 0.962 (0.892–1.032), 0.577 (0.507–0.647) and 0.567 (0.497–0.637), respectively; while for nonexperts, 0.818 (0.748–0.888), 0.532 (0.462–0.602) and 0.530 (0.460–0.600). This demonstrated a good reproducibility of AA-NBIME diagnosis. The average scores (experts and non-experts) of images acquired using AA-NBIME were significantly higher than those acquired using NBIME and ME (P < 0.05). AA-NBIME is a promising tool to clearly visualize the mucosal pit pattern (PP) of colorectal polyps for better differentiating neoplastic polyps from non-neoplastic ones.

ESD and Pit Pattern Diagnosis: Lessons from a Japanese Endoscopist Working in the United States

Endoscopic submucosal dissection (ESD) was developed in 2000s to overcome the limitations of endoscopic mucosal resection (EMR), especially to accomplish en-bloc resection, and it has been accepted worldwide in the past decades. Many ESD devices and diagnosis modalities are currently available, which include pit pattern and narrow band imaging (NBI) diagnoses to evaluate the depth of the tumor preoperatively with sensitivities of 70 to 90%. Depending on the Japanese colorectal guideline, the intramucosal cancer and shallow invasion of the submucosal layer are the main good indications of ESD; however, the ESD practices between Japan and Western countries still vary, including pathologic definition of cancer, tumor/node/metastasis classification, and handling of ESD specimen. In the United States, despite the large demand for treatment of colorectal neoplasm, pit pattern and magnified NBI diagnoses are not widely accepted yet, and piecemeal EMR is still the major method in most of the institutions. Moreover, the specific guideline of ESD is also not available yet. More new technologies are being developed other than conventional ESD methods in Eastern and Western countries, and ESD is now expected to change in the next generation. It is recommended that not only gastroenterologists but also colorectal surgeons have appropriate knowledge of colorectal lesions and their management to ensure current treatments is applied to patients.

Diagnostic efficacy of the Japan Narrow-band-imaging Expert Team and Pit pattern classifications for colorectal lesions: A meta-analysis

BACKGROUND

Pit pattern classification using magnifying chromoendoscopy is the established method for diagnosing colorectal lesions. The Japan Narrow-band-imaging (NBI) Expert Team (JNET) classification is a novel NBI magnifying endoscopic classification that focuses on the vessel, and surface patterns.

AIM

To determine the diagnostic efficacy of each category of the JNET and Pit pattern classifications for colorectal lesions.

METHODS

A systematic literature search was performed using PubMed, Embase, the Cochrane Library, and Web of Science databases. The pooled sensitivity, specificity, diagnostic odds ratio, and area under the summary receiver operating characteristic curve of each category of the JNET and Pit pattern classifications were calculated.

RESULTS

A total of 19227 colorectal lesions in 31 studies were included. The diagnostic performance of the JNET classification was equivalent to the Pit pattern classification in each corresponding category. The pooled sensitivity, specificity, and area under the curve (AUC) for each category of the JNET classification were as follows: 0.73 (95%CI: 0.55-0.85), 0.99 (95%CI: 0.97-1.00), and 0.97 (95%CI: 0.95-0.98), respectively, for Type 1; 0.88 (95%CI: 0.78-0.94), 0.72 (95%CI: 0.64-0.79), and 0.84 (95%CI: 0.81-0.87), respectively, for Type 2A; 0.56 (95%CI: 0.47-0.64), 0.91 (95%CI: 0.79-0.96), and 0.72 (95%CI: 0.68-0.76), respectively, for Type 2B; 0.51 (95%CI: 0.42-0.61), 1.00 (95%CI: 1.00-1.00), and 0.90 (95%CI: 0.87-0.93), respectively, for Type 3.

CONCLUSION

This meta-analysis suggests that the diagnostic efficacy of the JNET classification may be equivalent to that of the Pit pattern classification. However, due to its simpler and clearer clinical application, the JNET classification should be promoted for the classification of colorectal lesions, and to guide the treatment strategy.

Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations

BACKGROUND & AIMS

Narrow-band imaging (NBI) can be used to determine whether colorectal polyps are adenomatous or hyperplastic. We investigated whether an artificial intelligence (AI) system can increase the accuracy of characterizations of polyps by endoscopists of different skill levels.

METHODS

We developed convolutional neural networks (CNNs) for evaluation of diminutive colorectal polyps, based on efficient neural architecture searches via parameter sharing with augmentation using NBIs of diminutive (≤5 mm) polyps, collected from October 2015 through October 2017 at the Seoul National University Hospital, Healthcare System Gangnam Center (training set). We trained the CNN using images from 1100 adenomatous polyps and 1050 hyperplastic polyps from 1379 patients. We then tested the system using 300 images of 180 adenomatous polyps and 120 hyperplastic polyps, obtained from January 2018 to May 2019. We compared the accuracy of 22 endoscopists of different skill levels (7 novices, 4 experts, and 11 NBI-trained experts) vs the CNN in evaluation of images (adenomatous vs hyperplastic) from 180 adenomatous and 120 hyperplastic polyps. The endoscopists then evaluated the polyp images with knowledge of the CNN-processed results. We conducted mixed-effect logistic and linear regression analyses to determine the effects of AI assistance on the accuracy of analysis of diminutive colorectal polyps by endoscopists (primary outcome).

RESULTS

The CNN distinguished adenomatous vs hyperplastic diminutive polyps with 86.7% accuracy, based on histologic analysis as the reference standard. Endoscopists distinguished adenomatous vs hyperplastic diminutive polyps with 82.5% overall accuracy (novices, 73.8% accuracy; experts, 83.8% accuracy; and NBI-trained experts, 87.6% accuracy). With knowledge of the CNN-processed results, the overall accuracy of the endoscopists increased to 88.5% (P < .05). With knowledge of the CNN-processed results, the accuracy of novice endoscopists increased to 85.6% (P < .05). The CNN-processed results significantly reduced endoscopist time of diagnosis (from 3.92 to 3.37 seconds per polyp, P = .042).

CONCLUSIONS

We developed a CNN that significantly increases the accuracy of evaluation of diminutive colorectal polyps (as adenomatous vs hyperplastic) and reduces the time of diagnosis by endoscopists. This AI assistance system significantly increased the accuracy of analysis by novice endoscopists, who achieved near-expert levels of accuracy without extra training. The CNN assistance system can reduce the skill-level dependence of endoscopists and costs.

Feasibility of using narrow band imaging international colorectal endoscopic classification for diagnosing colorectal neoplasia in China: A multicenter pilot observational study

OBJECTIVE

We aimed to investigate whether Chinese endoscopists without narrow-band imaging (NBI) experiences could achieve high accuracy in the real-time diagnosis of colorectal polyps using NBI International Colorectal Endoscopic (NICE) classification after web-based training.

METHODS

Altogether 15 endoscopists from five centers with no NBI experiences followed a short, web-based training program on the NICE classification and took web-based test. Their performances were compared with 15 matched experienced endoscopists with no NBI experience who received no NBI training. These 15 trained endoscopists then made real-time diagnoses of colorectal neoplasia. A logistic regression was used to assess potential predictors of diagnostic performance.

RESULTS

Compared with those who received no training, trained endoscopists achieved comparable overall accuracy (85.3% vs 83.1%, P = 0.408) and accuracy at a high-confidence level (87.0% vs 86.0%, P = 0.670), but had a higher confidence rate (86.1% vs 83.7%, P = 0.004) for the diagnosis of neoplasia. Real-time diagnostic accuracy, sensitivity and specificity were 94.3% (95% confidence interval [CI] 91.5%-96.2%), 96.2% (95% CI 93.4%-97.9%) and 85.3% (95% CI 74.8%-92.1%) at high-confidence level. The high-confidence level was the strongest predictor of real-time diagnostic accuracy (odds ratio 12.66, P < 0.001).

CONCLUSIONS

Web-based training can improve the confidence level of endoscopists in accurately diagnosing colorectal polyps using the NICE classification. Chinese endoscopists can achieve high accuracy in diagnosing colorectal neoplasia at a high confidence level (ClinicalTrials ID: NCT02033980).

Optical Technologies for Endoscopic Real-Time Histologic Assessment of Colorectal Polyps: A Meta-Analysis

OBJECTIVES

Accurate, real-time, endoscopic risk stratification of colorectal polyps would improve decision-making and optimize clinical efficiency. Technologies to manipulate endoscopic optical outputs can be used to predict polyp histology in vivo; however, it remains unclear how accuracy has progressed and whether it is sufficient for routine clinical implementation.

METHODS

A meta-analysis was conducted by searching MEDLINE, Embase, and the Cochrane Library. Studies were included if they prospectively deployed an endoscopic optical technology for real-time in vivo prediction of adenomatous colorectal polyps. Polyposis and inflammatory bowel diseases were excluded. Bayesian bivariate meta-analysis was performed, presenting 95% confidence intervals (CI).

RESULTS

One hundred two studies using optical technologies on 33,123 colorectal polyps were included. Digital chromoendoscopy differentiated neoplasia (adenoma and adenocarcinoma) from benign polyps with sensitivity of 92.2% (90.6%-93.9% CI) and specificity of 84.0% (81.5%-86.3% CI), with no difference between constituent technologies (narrow-band imaging, Fuji intelligent Chromo Endoscopy, iSCAN) or with only diminutive polyps. Dye chromoendoscopy had sensitivity of 92.7% (90.1%-94.9% CI) and specificity of 86.6% (82.9%-89.9% CI), similarly unchanged for diminutive polyps. Spectral analysis of autofluorescence had sensitivity of 94.4% (84.0%-99.1% CI) and specificity of 50.9% (13.2%-88.8% CI). Endomicroscopy had sensitivity of 93.6% (85.3%-98.3% CI) and specificity of 92.5% (81.8%-98.1% CI). Computer-aided diagnosis had sensitivity of 88.9% (74.2%-96.7% CI) and specificity of 80.4% (52.6%-95.7% CI). Prediction confidence and endoscopist experience alone did not significantly improve any technology. The only subgroup to demonstrate a negative predictive value for adenoma above 90% was digital chromoendoscopy, making high confidence predictions of diminutive recto-sigmoid polyps. Chronologic meta-analyses show a falling negative predictive value over time. A significant publication bias exists.

DISCUSSION

This novel approach to meta-analysis demonstrates that existing optical technologies are increasingly unlikely to allow safe "resect and discard" strategies and that step-change innovation may be required. A "diagnose and leave" strategy may be supported for diminutive recto-sigmoid polyps diagnosed with high confidence; however, limitations exist in the evidence base for this cohort.

Endoscopic submucosal dissection for colorectal laterally spreading tumors with the Dual knife only

Introduction

The knives for endoscopic submucosal dissection (ESD) have their strengths as well as shortcomings. They need to be used in combination in most cases. The Dual knife is a relatively novel type of ESD knife produced in 2009, which can be used for completing the whole procedure of ESD.

Aim

Colorectal laterally spreading tumors (LSTs) are a special subtype of colorectal neoplasms. We aimed to evaluate the clinical features and outcomes of ESD for colorectal LSTs only using the Dual knife from our experience.

Material and methods

This retrospective study included 162 patients (each patient had 1 lesion) with colorectal LSTs treated by ESD with the Dual knife by a single endoscopist at our hospital between June 2015 and January 2018. We analyzed the clinical features and outcomes after resection.

Results

We obtained the en bloc ESD of the colorectal LSTs and the complete histological assessment in all patients. The mean age of the patients was 53.9 years. The mean diameter of lesions was 46 mm. The most common location of LSTs was the rectum. The most common histological type was tubular adenoma with 63 cases. The mean operating time was 56 min. Perforation and bleeding rates were 0.6% and 0.6%, respectively. No cases of local persistence or recurrence were observed at a follow-up endoscopy 6 to 31 months after the en bloc resection.

Conclusions

The ESD using the Dual knife only for colorectal LSTs has the advantages of safety, efficiency, and minimally invasiveness. It is worthy of widespread clinical application.

Real-Time Optical Diagnosis of Colorectal Polyps in the Routine Clinical Practice Using the NICE and WASP Classifications in a Nonacademic Setting

Background

Narrow-band imaging (NBI) allows "in vivo" classification of colorectal polyps.

Objectives

We evaluated the optical diagnosis by nonexpert community-based endoscopists in routine clinical practice, the impact of training, and whether the endoscopists could achieve the threshold for the "do not resect" policy.

Methods

This was an observational study performed in two periods (P1 and P2). Endoscopists had no prior experience in NBI in P1 and applied the technique on a daily basis for 1 year before participation in P2. Lesions were classified by applying the NBI International Colorectal Endoscopic (NICE) and Workgroup serrAted polypS and Polyposis (WASP) classifications, simultaneously.

Results

A total of 290 polyps were analyzed. The overall accuracy of optical diagnosis was 0.75 (95% CI 0.68-0.81) in P1, with an increase to 0.82 (95% CI 0.73-0.89) in P2 (p = 0.260). The accuracy of the NICE/WASP classifications to differentiate adenomatous from nonadenomatous histology was 0.78 (95% CI 0.72-0.84) in P1 and 0.86 (95% CI 0.77-0.92) in P2 (p = 0.164); assignments made with a high confidence level achieved statistical significance (13% improvement, 95% CI 3-22%; p = 0.022). The negative predictive value for adenomatous histology of diminutive rectosigmoid polyps was 81% (95% CI 64-93%) and 80% (95% CI 59-93%) in P1 and P2, respectively.

Conclusions

Nonexpert endoscopists achieved moderate accuracy for real-time optical diagnosis of colorectal lesions with the NICE/WASP classifications. The overall performance of the endoscopists improved after sustained use of optical diagnosis, but did not achieve the standards for the implementation of the "do not resect" strategy.

Artificial intelligence in gastrointestinal endoscopy: The future is almost here

Artificial intelligence (AI) enables machines to provide unparalleled value in a myriad of industries and applications. In recent years, researchers have harnessed artificial intelligence to analyze large-volume, unstructured medical data and perform clinical tasks, such as the identification of diabetic retinopathy or the diagnosis of cutaneous malignancies. Applications of artificial intelligence techniques, specifically machine learning and more recently deep learning, are beginning to emerge in gastrointestinal endoscopy. The most promising of these efforts have been in computer-aided detection and computer-aided diagnosis of colorectal polyps, with recent systems demonstrating high sensitivity and accuracy even when compared to expert human endoscopists. AI has also been utilized to identify gastrointestinal bleeding, to detect areas of inflammation, and even to diagnose certain gastrointestinal infections. Future work in the field should concentrate on creating seamless integration of AI systems with current endoscopy platforms and electronic medical records, developing training modules to teach clinicians how to use AI tools, and determining the best means for regulation and approval of new AI technology.

Endoscopic submucosal dissection in the West: Current status and future directions

Endoscopic submucosal dissection (ESD) was first conceptually described almost 30 years ago in Japan and is now widely practiced throughout East Asia. ESD expands the boundaries of endoscopic resection (ER) by allowing en bloc resection of large early neoplastic lesions within the gastrointestinal tract (GIT). This offers advantages over other ER techniques by facilitating definitive histological staging and curative treatment of early cancer in selected cases. Indeed, the experience of ESD in Eastern countries is significant, and excellent outcomes from high-volume centers are reported. The potential benefits of ESD are recognized by Western endoscopists, but its adoption has been limited. A number of factors contribute to this, including epidemiological differences in GIT neoplasia between Western and Eastern populations and limitations in training opportunities. In this review, we discuss the role of ESD, its current status and the future in Western endoscopic practice.

Accurate Classification of Diminutive Colorectal Polyps Using Computer-Aided Analysis

BACKGROUND & AIMS

Narrow-band imaging is an image-enhanced form of endoscopy used to observed microstructures and capillaries of the mucosal epithelium which allows for real-time prediction of histologic features of colorectal polyps. However, narrow-band imaging expertise is required to differentiate hyperplastic from neoplastic polyps with high levels of accuracy. We developed and tested a system of computer-aided diagnosis with a deep neural network (DNN-CAD) to analyze narrow-band images of diminutive colorectal polyps.

METHODS

We collected 1476 images of neoplastic polyps and 681 images of hyperplastic polyps, obtained from the picture archiving and communications system database in a tertiary hospital in Taiwan. Histologic findings from the polyps were also collected and used as the reference standard. The images and data were used to train the DNN. A test set of images (96 hyperplastic and 188 neoplastic polyps, smaller than 5 mm), obtained from patients who underwent colonoscopies from March 2017 through August 2017, was then used to test the diagnostic ability of the DNN-CAD vs endoscopists (2 expert and 4 novice), who were asked to classify the images of the test set as neoplastic or hyperplastic. Their classifications were compared with findings from histologic analysis. The primary outcome measures were diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic time. The accuracy, sensitivity, specificity, PPV, NPV, and diagnostic time were compared among DNN-CAD, the novice endoscopists, and the expert endoscopists. The study was designed to detect a difference of 10% in accuracy by a 2-sided McNemar test.

RESULTS

In the test set, the DNN-CAD identified neoplastic or hyperplastic polyps with 96.3% sensitivity, 78.1% specificity, a PPV of 89.6%, and a NPV of 91.5%. Fewer than half of the novice endoscopists classified polyps with a NPV of 90% (their NPVs ranged from 73.9% to 84.0%). DNN-CAD classified polyps as neoplastic or hyperplastic in 0.45 ± 0.07 seconds-shorter than the time required by experts (1.54 ± 1.30 seconds) and nonexperts (1.77 ± 1.37 seconds) (both P < .001). DNN-CAD classified polyps with perfect intra-observer agreement (kappa score of 1). There was a low level of intra-observer and inter-observer agreement in classification among endoscopists.

CONCLUSIONS

We developed a system called DNN-CAD to identify neoplastic or hyperplastic colorectal polyps less than 5 mm. The system classified polyps with a PPV of 89.6%, and a NPV of 91.5%, and in a shorter time than endoscopists. This deep-learning model has potential for not only endoscopic image recognition but for other forms of medical image analysis, including sonography, computed tomography, and magnetic resonance images.

Virtual chromoendoscopy for the real-time assessment of colorectal polyps in vivo: a systematic review and economic evaluation

BACKGROUND

Current clinical practice is to remove a colorectal polyp detected during colonoscopy and determine whether it is an adenoma or hyperplastic by histopathology. Identifying adenomas is important because they may eventually become cancerous if untreated, whereas hyperplastic polyps do not usually develop into cancer, and a surveillance interval is set based on the number and size of adenomas found. Virtual chromoendoscopy (VCE) (an electronic endoscopic imaging technique) could be used by the endoscopist under strictly controlled conditions for real-time optical diagnosis of diminutive (≤ 5 mm) colorectal polyps to replace histopathological diagnosis.

OBJECTIVE

To assess the clinical effectiveness and cost-effectiveness of the VCE technologies narrow-band imaging (NBI), flexible spectral imaging colour enhancement (FICE) and i-scan for the characterisation and management of diminutive (≤ 5 mm) colorectal polyps using high-definition (HD) systems without magnification.

DESIGN

Systematic review and economic analysis.

PARTICIPANTS

People undergoing colonoscopy for screening or surveillance or to investigate symptoms suggestive of colorectal cancer.

INTERVENTIONS

NBI, FICE and i-scan.

MAIN OUTCOME MEASURES

Diagnostic accuracy, recommended surveillance intervals, health-related quality of life (HRQoL), adverse effects, incidence of colorectal cancer, mortality and cost-effectiveness of VCE compared with histopathology.

DATA SOURCES

Electronic bibliographic databases including MEDLINE, EMBASE, The Cochrane Library and Database of Abstracts of Reviews of Effects were searched for published English-language studies from inception to June 2016. Bibliographies of related papers, systematic reviews and company information were screened and experts were contacted to identify additional evidence.

REVIEW METHODS

Systematic reviews of test accuracy and economic evaluations were undertaken in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Meta-analyses were conducted, where possible, to inform the independent economic model. A cost-utility decision-analytic model was developed to estimate the cost-effectiveness of VCE compared with histopathology. The model used a decision tree for patients undergoing endoscopy, combined with estimates of long-term outcomes (e.g. incidence of colorectal cancer and subsequent morbidity and mortality) derived from University of Sheffield School of Health and Related Research's bowel cancer screening model. The model took a NHS perspective, with costs and benefits discounted at 3.5% over a lifetime horizon. There were limitations in the data on the distribution of adenomas across risk categories and recurrence rates post polypectomy.

RESULTS

Thirty test accuracy studies were included: 24 for NBI, five for i-scan and three for FICE (two studies assessed two interventions). Polyp assessments made with high confidence were associated with higher sensitivity and endoscopists experienced in VCE achieved better results than those without experience. Two economic evaluations were included. NBI, i-scan and FICE are cost-saving strategies compared with histopathology and the number of quality-adjusted life-years gained was similar for histopathology and VCE. The correct surveillance interval would be given to 95% of patients with NBI, 94% of patients with FICE and 97% of patients with i-scan.

LIMITATIONS

Limited evidence was available for i-scan and FICE and there was heterogeneity among the NBI studies. There is a lack of data on longer-term health outcomes of patients undergoing VCE for assessment of diminutive colorectal polyps.

CONCLUSIONS

VCE technologies, using HD systems without magnification, could potentially be used for the real-time assessment of diminutive colorectal polyps, if endoscopists have adequate experience and training.

FUTURE WORK

Future research priorities include head-to-head randomised controlled trials of all three VCE technologies; more research on the diagnostic accuracy of FICE and i-scan (when used without magnification); further studies evaluating the impact of endoscopist experience and training on outcomes; studies measuring adverse effects, HRQoL and anxiety; and longitudinal data on colorectal cancer incidence, HRQoL and mortality.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016037767.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Polyp characterization at colonoscopy: Clinical implications

Although advancements in endoscopic imaging of colorectal mucosa have outstripped the pace of research in the field, the potential clinical applications of these novel technologies are promising. Chief among these is the ability to diagnose colorectal polyps in vivo. This feature appears most applicable to diminuitive polyps, which have very little malignant potential yet represent over 70% of resected polyps. In an ideal application, the capability to predict diminutive hyperplastic polyp histology in vivo precludes the need for excision whereas dimunitive adenomas do require excision, but not necessarily histopathologic analysis if the diagnosis is made in vivo with adequate confidence. However, the vast array of new advanced imaging modalities and polyp classification tools have been difficult to reconcile. We aim to highlight the current status of real-time colorectal polyp diagnosis and identify the barriers that remain to its widespread implementation.

Morphological classifications of gastrointestinal lesions

In the era of spreading adoption of gastrointestinal endoscopy screening worldwide, endoscopists encounter an increasing number of complex lesions in the gastrointestinal tract. For decision-making on optimal treatment, precise lesion characterization is crucial. Especially the assessment of potential submucosal invasion is of utmost importance as this determines whether endoscopic removal is an option and which technique should be used. To describe a lesion and stratify for the risk of submucosal invasion, several morphological classification systems have been developed. In this manuscript, we thoroughly discuss a systematic approach for the endoscopic assessment of a lesion, which include location, size, Paris classification, lateral spreading tumor classification if applicable and evaluation of the surface pattern with advanced endoscopic imaging techniques. The use of advanced imaging techniques improves the characterization of mucosal surface patterns and helps to determine whether lesions are amenable to endoscopic resection.

AGA White Paper: Training and Implementation of Endoscopic Image Enhancement Technologies

Endoscopic image-enhancement technologies provide opportunities to visualize normal and abnormal tissues within the gastrointestinal (GI) tract in a manner that complements conventional white light endoscopic imaging. The additional information that is obtained enables the endoscopist to better identify, delineate, and characterize lesions and can facilitate targeted biopsies or, in some cases, eliminate the need to send samples for histologic analysis. Some of these technologies have been available for more than a decade, but despite this fact, there is limited use of these technologies by endoscopists. Lack of formalized training in their use and a scarcity of guidelines on implementation of these technologies into clinical practice are contributing factors. In November 2014, the American Gastroenterological Association's Center for GI Innovation and Technology conducted a 2-day workshop to discuss endoscopic image-enhancement technologies. This article represents the third of 3 separate documents generated from the workshop and discusses the published literature pertaining to training and outlines a proposed framework for the implementation of endoscopic image-enhancement technologies in clinical practice. There was general agreement among participants in the workshop on several key considerations. Training and competency assessment for endoscopic image-enhancement technologies should incorporate competency-based education paradigms. To facilitate successful training, multiple different educational models that can cater to variations in learning styles need to be developed, including classroom-style and self-directed programs, in-person and web-based options, image and video atlases, and endoscopic simulator programs. To ensure safe and appropriate use of these technologies over time, refresher courses, skill maintenance programs, and options for competency reassessment should be established. Participants also generally agreed that although early adopters of novel endoscopic image-enhancement modalities can successfully implement these technologies by pursuing training and ensuring self-competency, widespread implementation is likely to require support from GI societies and buy-in from other key stakeholders including payors/purchasers and patients. Continued work by manufacturers and the GI societies in providing training programs and patient education, working with payors and purchasers, and creating environments and policies that motivate endoscopists to adopt new practices is essential in creating widespread implementation.

Narrow band imaging optical diagnosis of small colorectal polyps in routine clinical practice: the Detect Inspect Characterise Resect and Discard 2 (DISCARD 2) study

BACKGROUND

Accurate optical characterisation and removal of small adenomas (<10 mm) at colonoscopy would allow hyperplastic polyps to be left in situ and surveillance intervals to be determined without the need for histopathology. Although accurate in specialist practice the performance of narrow band imaging (NBI), colonoscopy in routine clinical practice is poorly understood.

METHODS

NBI-assisted optical diagnosis was compared with reference standard histopathological findings in a prospective, blinded study, which recruited adults undergoing routine colonoscopy in six general hospitals in the UK. Participating colonoscopists (N=28) were trained using the NBI International Colorectal Endoscopic (NICE) classification (relating to colour, vessel structure and surface pattern). By comparing the optical and histological findings in patients with only small polyps, test sensitivity was determined at the patient level using two thresholds: presence of adenoma and need for surveillance. Accuracy of identifying adenomatous polyps <10 mm was compared at the polyp level using hierarchical models, allowing determinants of accuracy to be explored.

FINDINGS

Of 1688 patients recruited, 722 (42.8%) had polyps <10 mm with 567 (78.5%) having only polyps <10 mm. Test sensitivity (presence of adenoma, N=499 patients) by NBI optical diagnosis was 83.4% (95% CI 79.6% to 86.9%), significantly less than the 95% sensitivity (p<0.001) this study was powered to detect. Test sensitivity (need for surveillance) was 73.0% (95% CI 66.5% to 79.9%). Analysed at the polyp level, test sensitivity (presence of adenoma, N=1620 polyps) was 76.1% (95% CI 72.8% to 79.1%). In fully adjusted analyses, test sensitivity was 99.4% (95% CI 98.2% to 99.8%) if two or more NICE adenoma characteristics were identified. Neither colonoscopist expertise, confidence in diagnosis nor use of high definition colonoscopy independently improved test accuracy.

INTERPRETATION

This large multicentre study demonstrates that NBI optical diagnosis cannot currently be recommended for application in routine clinical practice. Further work is required to evaluate whether variation in test accuracy is related to polyp characteristics or colonoscopist training.

TRIAL REGISTRATION NUMBER

The study was registered with clinicaltrials.gov (NCT01603927).

Clinical impact and characteristics of the narrow-band imaging magnifying endoscopic classification of colorectal tumors proposed by the Japan NBI Expert Team

BACKGROUND AND AIMS

The Japan NBI Expert Team (JNET) was established in 2011 and has proposed a universal narrow-band imaging (NBI) magnifying endoscopic classification of colorectal tumors. The aim of this study was to evaluate the clinical usefulness of the JNET classification for colorectal lesions.

METHODS

We analyzed 2933 colorectal lesions, which were diagnosed by NBI magnifying observation before endoscopic treatment or surgery. The colorectal lesions consisted of 136 hyperplastic polyps/sessile serrated polyps (HPs/SSPs), 1926 low-grade dysplasia (LGD), 571 high-grade dysplasia (HGD), 87 superficial submucosal invasive (SM-s) carcinomas, and 213 deep submucosal invasive (SM-d) carcinomas. We evaluated the relationship between the JNET classification and the histologic findings of these lesions.

RESULTS

The sensitivity, specificity, positive and negative predictive values, and accuracy of Type 1 lesions for the diagnosis of HP/SSP were, respectively, 87.5%, 99.9%, 97.5%, 99.4%, and 99.3%; of Type 2A lesions for the diagnosis of LGD were 74.3%, 92.7%, 98.3%, 38.7%, and 77.1%; of Type 2B lesions for the diagnosis of HGD/SM-s carcinoma were 61.9%, 82.8%, 50.9%, 88.2%, and 78.1%; for Type 3 lesions for the diagnosis of SM-d carcinoma were 55.4%, 99.8%, 95.2%, 96.6%, and 96.6%, respectively.

CONCLUSIONS

Types 1, 2A, and 3 of the JNET classification were very reliable indicators for HP/SSP, LGD, and SM-d carcinoma, respectively. However, the specificity and positive predictive value of Type 2B were relatively lower than those of others. Therefore, an additional examination such as pit pattern diagnosis using chromoagents is necessary for accurate diagnosis of Type 2B lesions.

Narrow Band Imaging, Magnifying Chromoendoscopy, and Gross Morphological Features for the Optical Diagnosis of T1 Colorectal Cancer and Deep Submucosal Invasion: A Systematic Review and Meta-Analysis

OBJECTIVES

Optical diagnosis of T1 colorectal cancer (CRC) and T1 CRC with deep submucosal invasion is important in guiding the treatment strategy. The use of advanced imaging is not standard clinical practice in Western countries. A systematic review and meta-analysis were conducted comparing the accuracy of narrow band imaging (NBI), magnifying chromoendoscopy (MCE), and gross morphological features (GMF) seen with conventional view for the optical diagnosis of T1 CRC and deep submucosal invasion.

METHODS

A literature search identified studies on the optical diagnosis of T1 CRC and deep invasion using NBI, MCE, or GMF. Pooled estimates (PE) of sensitivity and specificity across studies reporting on NBI or MCE were compared using a random effects bivariate meta-regression approach, and a paired analysis focusing on studies that performed both techniques within the same patient was performed.

RESULTS

Thirty-three studies with 31,568 polyps were included. For the optical diagnosis of T1 CRC, both NBI (4 studies; PE 0.85, 95% confidence interval (CI) 0.75-0.91) and MCE (5 studies; PE 0.90, 95% CI 0.83-0.94) yielded higher sensitivity as compared with GMF (3 studies; range 0.21-0.46). No significant preference for NBI or MCE was found (sensitivity relative risk (RR) 0.93, 95% CI 0.79-1.09, P=0.37; specificity RR 0.98, 95% CI 0.86-1.11, P=0.74). Similarly, for the optical diagnosis of deep invasion, both NBI (13 studies; PE 0.77, 95% CI 0.68-0.84) and MCE (17 studies; PE 0.81, 95% 0.75-0.87) yielded higher sensitivity as compared with GMF (6 studies; range 0.18-0.88), and no significant preference for either NBI or MCE was found (sensitivity RR 0.92, 95% CI 0.76-1.11, P=0.36; specificity RR 1.00, 95% CI 0.96-1.04, P=0.92).

CONCLUSIONS

This review supports the use of advanced imaging techniques in preference to GMF to reduce the risk of performing piecemeal resection for T1 CRCs or unnecessary surgical referral for lesions amendable to endoscopic resection. A preference for either NBI or MCE could not be observed.

Can optical diagnosis of small colon polyps be accurate? Comparing standard scope without narrow banding to high definition scope with narrow banding

AIM: To study the accuracy of using high definition (HD) scope with narrow band imaging (NBI) vs standard white light colonoscope without NBI (ST), to predict the histology of the colon polyps, particularly those < 1 cm.

METHODS: A total of 147 African Americans patients who were referred to Howard University Hospital for screening or, diagnostic or follow up colonoscopy, during a 12-mo period in 2012 were prospectively recruited. Some patients had multiple polyps and total number of polyps was 179. Their colonoscopies were performed by 3 experienced endoscopists who determined the size and stated whether the polyps being removed were hyperplastic or adenomatous polyps using standard colonoscopes or high definition colonoscopes with NBI. The histopathologic diagnosis was reported by pathologists as part of routine care.

RESULTS: Of participants in the study, 55 (37%) were male and median (interquartile range) of age was 56 (19-80). Demographic, clinical characteristics, past medical history of patients, and the data obtained by two instruments were not significantly different and two methods detected similar number of polyps. In ST scope 89% of polyps were < 1 cm vs 87% in HD scope (P = 0.7). The ST scope had a positive predictive value (PPV) and positive likelihood ratio (PLR) of 86% and 4.0 for adenoma compared to 74% and 2.6 for HD scope. There was a trend of higher sensitivity for HD scope (68%) compare to ST scope (53%) with almost the same specificity. The ST scope had a PPV and PLR of 38% and 1.8 for hyperplastic polyp (HPP) compared to 42% and 2.2 for HD scope. The sensitivity and specificity of two instruments for HPP diagnosis were similar.

CONCLUSION: Our results indicated that HD scope was more sensitive in diagnosis of adenoma than ST scope. Clinical diagnosis of HPP with either scope is less accurate compared to adenoma. Colonoscopy diagnosis is not yet fully matched with pathologic diagnosis of colon polyp. However with the advancement of both imaging and training, it may be possible to increase the sensitivity and specificity of the scopes and hence save money for eliminating time and the cost of Immunohistochemistry/pathology.

Effectiveness of systematic training in the application of narrow-band imaging international colorectal endoscopic (NICE) classification for optical diagnosis of colorectal polyps: Experience from a single center in China

BACKGROUND AND AIM

To evaluate the effectiveness of systematic training in the application of narrow-band imaging (NBI) International Colorectal Endoscopic (NICE) classification for the prediction of the histology of colorectal polyps.

METHODS

This is a single-center study. In total, 260 still images of colorectal polyps from 225 patients were included. Two series of 130 images obtained using NBI and white light without magnification were distributed to 10 endoscopists-five highly experienced endoscopists (HEE group) and five less experienced endoscopists (LEE group)-for assessment using the NICE classification, before and after systematic training.

RESULTS

Before systematic training, accuracy in both groups was 79.54% and specificity was relatively poor (HEE: 62.46%, LEE: 69.23%, P = 0.297). After systematic training, specificity significantly improved (HEE: 96.61%, LEE: 97.54%, P = 0.000 and P = 0.013, respectively). Accuracy also significantly increased to 94.93% and 96.46% in the HEE and LEE groups, respectively. Sensitivity and negative predictive value did not significantly improve in the post-test; however, both were high in both the pre- and post-test. The κ-values in both groups were excellent (HEE: 0.93, LEE: 0.91). Among the components of the NICE classification, surface pattern yielded the highest performance, whereas color yielded the lowest.

CONCLUSION

Systematic, feedback-based, training programs can help achieve high accuracy and good interobserver agreement in the application of the NICE classification for the prediction of the histology of colorectal polyps by endoscopists with different levels of experience.

Role of magnifying colonoscopy for diagnosis of colorectal neoplasms: From the perspective of Japanese colonoscopists

Colorectal cancer is the third leading cause of cancer-related death. As the therapeutic strategy for colorectal cancer depends on the clinical stage of the tumor, precise and accurate staging is necessary prior to treatment decision-making. Colonoscopy is an essential tool for detection and prevention of colorectal cancer, as it also allows for removal of adenomatous lesions. Using conventional endoscopy, however, it is sometimes difficult to differentiate neoplastic lesions from non-neoplastic lesions. Several new endoscopic technologies have been developed to provide a more precise diagnosis. Magnifying chromoendoscopy and narrow-band imaging endoscopy with or without magnification are invaluable not only for distinction of colorectal neoplastic lesions from non-neoplastic lesions, but also for the accurate diagnosis of invasion depth in colorectal cancers. Based on an accumulation of a large number of clinical data, the use of magnifying colonoscopy has become inevitable for the prediction of histology and the diagnosis of invasion depth of colorectal neoplasms in Japan.

Differential diagnosis of colorectal polyps with narrow band imaging colonoscopy without magnification

BACKGROUND/AIMS

Narrow band imaging (NBI) endoscopy can be used for gross differentiation between the types of colonic polyps. This study was conducted as a retrospective study for estimation of the interobserver and intra-observer agreement of the pit pattern of the mucosal surface and the accuracy of histology prediction.

METHODS

A total of 159 patients underwent complete colonoscopy and 219 polyps examined by NBI endoscopy without magnification were assessed. Interobserver and intra-observer agreement were calculated by investigators in each group for determination of the surface pattern and prediction of histology based on the modified Kudo's classification using intraclass correlation coefficient.

RESULTS

Interobserver agreement for the surface pit pattern and prediction of polyp type was 0.84 and 0.73 in experienced endoscopists, and 0.86 and 0.62 in trainees, respectively. Intra-observer agreement for the surface pit patterns and prediction of polyp type was 0.81, 0.83, 0.85, 0.83, 0.56, 0.84, 0.51, 0.83, and 0.71; and 0.71, 0.70, 0.82, 0.54, 0.72, 0.37, 0.51, 0.34, and 0.30, respectively. The diagnostic accuracy for prediction of polyp type was 69.4% for experienced endoscopists and 72.9% for trainees.

CONCLUSIONS

NBI endoscopy without magnification showed fairly good inter and intra-observer agreement for the pit pattern of the mucosal surface and the accuracy of histology prediction; however, it had some limitation for differentiation of colon polyp histologic type. Training and experience with NBI is needed for improvement of accuracy.

A Randomized Controlled Clinical Study Comparing the Diagnostic Accuracy of the Histologic Prediction for Colorectal Polyps Depending on the Use of Either Magnified or Nonmagnified Narrow Band Imaging

Background/Aims:

The aim of this study was to compare the diagnostic capabilities of narrow band imaging (NBI) colonoscopy with and without optical magnification in differentiating neoplastic from nonneoplastic colorectal polyps.

Methods:

Between April 2012 and March 2013, 122 patients with colorectal polyps detected by using diagnostic conventional colonoscopy were prospectively enrolled. A total of 236 polyps were evaluated with NBI, in vivo in real time during therapeutic colonoscopy, by one experienced endoscopist. Whether magnification was used or not was determined by randomization. After an in vivo real-time endoscopic prediction of histology, all lesions were endoscopically excised. Surgical pathologic reports were used as the criterion standards. The sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) of identifying neoplastic polyps were calculated.

Results:

A total of 236 lesions with an average size of 5.6 mm in 122 patients were assessed (159 neoplastic, 77 nonneoplastic). The Sn, Sp, PPV, and NPV in differentiating neoplastic from nonneoplastic lesions with the magnified NBI were 97.5%, 83.3%, 94.0%, and 92.6%, respectively, whereas those of the nonmagnified NBI group were 97.5%, 85.1%, 91.7%, and 95.2%, respectively.

Conclusions:

Nonmagnified NBI colonoscopy distinguishes neoplastic from nonneoplastic colorectal polyps as accurately as does magnified NBI colonoscopy.

High-definition endoscopy with digital chromoendoscopy for histologic prediction of distal colorectal polyps

BACKGROUND

Distal diminutive colorectal polyps are common and accurate endoscopic prediction of hyperplastic or adenomatous polyp histology could reduce procedural time, costs and potential risks associated with the resection. Within this study we assessed whether digital chromoendoscopy can accurately predict the histology of distal diminutive colorectal polyps according to the ASGE PIVI statement.

METHODS

In this prospective cohort study, 224 consecutive patients undergoing screening or surveillance colonoscopy were included. Real time histology of 121 diminutive distal colorectal polyps was evaluated using high-definition endoscopy with digital chromoendoscopy and the accuracy of predicting histology with digital chromoendoscopy was assessed.

RESULTS

The overall accuracy of digital chromoendoscopy for prediction of adenomatous polyp histology was 90.1 %. Sensitivity, specificity, positive and negative predictive values were 93.3, 88.7, 88.7, and 93.2 %, respectively. In high-confidence predictions, the accuracy increased to 96.3 % while sensitivity, specificity, positive and negative predictive values were calculated as 98.1, 94.4, 94.5, and 98.1 %, respectively. Surveillance intervals with digital chromoendoscopy were correctly predicted with >90 % accuracy.

CONCLUSIONS

High-definition endoscopy in combination with digital chromoendoscopy allowed real-time in vivo prediction of distal colorectal polyp histology and is accurate enough to leave distal colorectal polyps in place without resection or to resect and discard them without pathologic assessment. This approach has the potential to reduce costs and risks associated with the redundant removal of diminutive colorectal polyps.

TRIAL REGISTRATION

ClinicalTrials NCT02217449.

Comparison of Narrow Band Imaging and Fujinon Intelligent Color Enhancement in Predicting Small Colorectal Polyp Histology

BACKGROUND

There are limited data on the performance of narrow band imaging (NBI) and Fujinon intelligent color enhancement (FICE) for differentiating polyp histologies.

AIMS

The aim of this study was to compare the diagnostic performances of NBI and FICE in differentiating neoplastic from non-neoplastic colorectal polyps <10 mm during screening colonoscopy.

METHODS

A total of 955 average-risk adults undergoing screening colonoscopies were randomly allocated to NBI or FICE groups. Four board-certified staff endoscopists without prior experience using NBI or FICE participated. The main outcomes of this study were overall accuracy, sensitivity, and specificity of FICE and NBI in identifying neoplastic polyps.

RESULTS

There was no significant difference in the number of subjects with adenoma between the NBI (143/475, 30.1 %) and FICE groups (139/480, 29.0 %) (after excluding adenoma ≥1 cm) (P > 0.05). The overall accuracy of NBI was 81.0 %, compared with 81.4 % for FICE (P = 0.867). The overall sensitivity and specificity of NBI and FICE were 84.6 and 78.0 % (P = 0.054); 75.1 and 86.5 % (P = 0.009), respectively. For polyps measuring ≤5 mm, the accuracy was 79.4 % for NBI and 80.1 % for FICE (P = 0.835; sensitivity 81.9 vs. 74.5 %, P = 0.064; specificity 75.7 vs. 88.4 %, P = 0.006).

CONCLUSIONS

The overall accuracy of NBI and FICE was similar for differentiating small polyp histologies during screening colonoscopy. However, better results should be achieved before using NBI or FICE as real-time optical biopsy of colorectal polyps in screening colonoscopy.

New paradigms in polypectomy: resect and discard, diagnose and disregard

Polypectomy at colonoscopy has been shown to reduce the subsequent risk of colorectal cancer. With the advent of national screening programs, the number of colonoscopies performed has increased worldwide. In addition, the recent drive for quality improvement combined with advances in colonoscopic technology has resulted in increased numbers of polyps detected, resected, and sent for histopathology leading to spiraling costs associated with the procedure. Being able to diagnose small polyps in vivo (optical diagnosis) would allow for adenomas to be resected and discarded without the need to retrieve them or send them for formal histopathology.

ASGE Technology Committee systematic review and meta-analysis assessing the ASGE PIVI thresholds for adopting real-time endoscopic assessment of the histology of diminutive colorectal polyps

In vivo real-time assessment of the histology of diminutive (≤5 mm) colorectal polyps detected at colonoscopy can be achieved by means of an "optical biopsy" by using currently available endoscopic technologies. This systematic review and meta-analysis was performed by the American Society for Gastrointestinal Endoscopy (ASGE) Technology Committee to specifically assess whether acceptable performance thresholds outlined by an ASGE Preservation and Incorporation of Valuable endoscopic Innovations (PIVI) document for clinical adoption of these technologies have been met. We conducted direct meta-analyses calculating the pooled negative predictive value (NPV) for narrow-band imaging (NBI), i-SCAN, and Fujinon Intelligent Color Enhancement (FICE)-assisted optical biopsy for predicting adenomatous polyp histology of small/diminutive colorectal polyps. We also calculated the pooled percentage agreement with histopathology when assigning postpolypectomy surveillance intervals based on combining real-time optical biopsy of colorectal polyps 5 mm or smaller with histopathologic assessment of polyps larger than 5 mm. Random-effects meta-analysis models were used. Statistical heterogeneity was evaluated by means of I(2) statistics. Our meta-analyses indicate that optical biopsy with NBI, exceeds the NPV threshold for adenomatous polyp histology, supporting a "diagnose-and-leave" strategy for diminutive predicted nonneoplastic polyps in the rectosigmoid colon. The pooled NPV of NBI for adenomatous polyp histology by using the random-effects model was 91% (95% confidence interval [CI], 88-94). This finding was associated with a high degree of heterogeneity (I(2) = 89%). Subgroup analysis indicated that the pooled NPV was greater than 90% for academic medical centers (91.8%; 95% CI, 89-94), for experts (93%; 95% CI, 91-96), and when the optical biopsy assessment was made with high confidence (93%; 95% CI, 90-96). Our meta-analyses also indicate that the agreement in assignment of postpolypectomy surveillance intervals based on optical biopsy with NBI of diminutive colorectal polyps is 90% or greater in academic settings (91%; 95% CI, 86-95), with experienced endoscopists (92%; 95% CI, 88-96) and when optical biopsy assessments are made with high confidence (91%; 95% CI, 88-95). Our systematic review and meta-analysis confirms that the thresholds established by the ASGE PIVI for real-time endoscopic assessment of the histology of diminutive polyps have been met, at least with NBI optical biopsy, with endoscopists who are expert in using this advanced imaging technology and when assessments are made with high confidence.

Electronic chromoendoscopy

Electronic chromoendoscopy technologies provide image enhancement and may improve the diagnosis of mucosal lesions. Although strides have been made in standardization of image characterization, especially with NBI, further image-to-pathology correlation and validation are required. There is promise for the development of a resect and discard policy for diminutive adenomas by using electronic chromoendoscopy; however, before this can be adopted, further community-based studies are needed. Further validated training tools for NBI, FICE, and i-SCAN will also be required for the use of these techniques to become widespread.

Low magnification narrow band imaging by inexperienced endoscopists has a high accuracy in differentiation of colon polyp histology

BACKGROUND/OBJECTIVE

Several studies have shown that NBI can predict the colorectal polyp histology with moderate to high accuracy. Most of them were conducted by highly experienced endoscopists at academic centers by using high magnification colonoscopes. We evaluated the accuracy of standard definition low magnification NBI in predicting the real time histology of colorectal polyps when used by inexperienced endoscopists and whether it can meet the thresholds recently defined for discard, resect and discard strategies of diminutive polyps by ASGE.

METHODS

The study was a prospective observational trial and involved 430 patients who underwent colonoscopy. A total of 214 polyps were detected in 317 patients. Colonoscopies were performed by a gastroenterology attending physician and two fellows who had no experience in NBI. Standard definition low magnification colonoscopes were used. The endoscopists recorded the size, Paris classification, and location of polyps under white light and consecutively described the superficial mucosal architecture and vascular pattern based on NBI International Colorectal Endoscopic criteria.

RESULTS

The overall accuracy of NBI in predicting adenomatous histology was 93.4%. The negative predictive value for diagnosing adenomatous histology in diminutive rectosigmoid polyps (93.3%) and the accuracy in predicting the colonoscopy surveillance interval (92.3%) were above the threshold levels defined by ASGE.

CONCLUSIONS

Low magnification NBI by inexperienced endoscopists has a high accuracy in predicting in vivo colorectal polyp histology encouraging its use in routine clinical practice.

High definition plus colonoscopy combined with i-scan tone enhancement vs. high definition colonoscopy for colorectal neoplasia: A randomized trial

BACKGROUND

High definition endoscopy is the accepted standard in colonoscopy. However, an important problem is missed polyps.

AIMS

Our objective was to assess the additional adenoma detection rate between high definition colonoscopy with tone enhancement (digital chromoendoscopy) vs. white light high definition colonoscopy.

METHODS

In this prospective randomized trial patients were included to undergo a tandem colonoscopy. The first exam was a white light colonoscopy with removal of all visualized polyps. The second examination was randomly assigned in a 1:1 ratio as either again white light colonoscopy (Group A) or colonoscopy with tone enhancement (Group B). Primary endpoint was the adenoma detection rate during the second withdrawal (sample size calculation - 40 per group).

RESULTS

67 lesions (Group A: n=34 vs. Group B: n=33) in 80 patients (mean age 61 years, male 64%) were identified on the first colonoscopy. The second colonoscopy detected 78 additional lesions: n=60 with tone enhancement vs. n=18 with white light endoscopy (p<0.001). Tone enhancement found more additional adenomas (A n=20 vs. B n=6, p=0.006) and identified significantly more missed adenomas per subject (0.5 vs. 0.15, p=0.006).

CONCLUSIONS

High definition plus colonoscopy with tone enhancement detected more adenomas missed by white light colonoscopy.

Kudo’s pit pattern classification for colorectal neoplasms: A meta-analysis

AIM: To analyze the current available evidence of Kudo’s pit pattern classification for diagnosing colorectal neoplasms.

METHODS: A search was performed on Pubmed/Embase to identify studies reporting the outcomes of the pit pattern classification in colorectal polyps. Retrieved records were evaluated and selected by two independent investigators. The number of patients, polyps and diagnostic performance of Kudo’s pit pattern classification were retrieved from suitable studies. Pooled sensitivities and specificities were calculated using fixed or random effect models according to their heterogeneity. Publication bias was evaluated using funnel plot, Egger’s test, and Begg’s test. Sensitivity analysis was performed by omitting one study at a time and selecting a subgroup consisting of 11 magnifying chromoendoscopy studies.

RESULTS: 20 eligible studies were included in which a total of 5111 colorectal lesions in 3418 patients were identified for the differentiation of neoplastic and non-neoplastic polyps. Pit pattern classification in all the studies of mucosal patterns with magnification resulted in a pooled sensitivity of 89.0% (95%CI: 85.2-91.9) and pooled specificity of 85.7% (95%CI: 81.3-89.2) and the area under the SROC curve was 0.9354. There was significant publication bias (P = 0.038 and 0.006 for sensitivity and specificity using Egger’s test, P = 0.035 and 0.139 for sensitivity and specificity using Begg’s test, respectively). No single study significantly affected the pooled result, and the magnifying chromoendoscopy subgroup yielded a sensitivity of 92.7% (95%CI: 89.2-95.2) and specificity of 87.3% (95%CI: 81.6-91.4).

CONCLUSION: Kudo’s pit pattern classification is an accurate diagnostic method for the differentiation of neoplastic colorectal lesions. Publication bias is significant in the current available literature.

Narrow band imaging vs. high definition colonoscopy for detection of colorectal adenomas in patients with positive faecal occult blood test: a randomised trial

BACKGROUND

The impact of narrow band imaging in improving the adenoma detection rate in a screening scenario is still unclear.

AIM

To evaluate whether narrow band imaging compared with high definition white light colonoscopy can enhance the adenoma detection rate during screening colonoscopy.

METHODS

Consecutive patients presenting for screening colonoscopy were included into this study and were randomly assigned to the narrow band imaging group (Group 1) or standard colonoscopy group (Group 2). Primary end point was the adenoma detection rate and secondary aim was the detection rate of advanced adenomas.

RESULTS

Overall, 117 patients were allocated to Group 1 and 120 to Group 2. Both the adenoma detection rate and the detection rate of advanced adenomas were not significantly different between the two groups (respectively, 52.1% vs. 55%, RR=0.95, 95% CI 0.75-1.20; 32.5% vs. 44.2%, RR=0.74, 95% CI 0.53-1.02). No significant difference between the proportions of polypoid and flat adenomas was found. Male gender, no prior history of screening, and endoscopist's adenoma detection rate were independent predictive factors of higher advanced adenoma detection rate.

CONCLUSIONS

In a screening scenario, narrow band imaging did not improve the adenoma nor advanced adenoma detection rates compared to high definition white light colonoscopy.

Colonic polyps: Is it useful to characterize them with advanced endoscopy?

There have been major developments in endoscopic imaging techniques in recent years. Endoscopes with high definition and magnification can provide high quality images that allow for the histological estimation of lesions in vivo and in situ when combined with ancillary enhancement techniques such as chromoendoscopy (CE) and virtual CE (narrow band imaging fujinon intelligent chromoendoscopy, or i-Scan). Despite the enormous potential for these advanced techniques, their value and feasibility in the clinic are still doubted, particularly in cases of colonic polyps that are slated for removal, where in vivo characterization may be deemed unnecessary. However, there are several advantages offered by such advanced endoscopic imaging. CE with or without magnification demonstrates highly accurate histology and invasion depth prediction, and virtual CE is a feasible and less cumbersome alternative to CE in terms of histological estimation, though not sufficiently accurate for depth invasion prediction. Furthermore, the supplementary information provided by advanced imaging systems can assist the endoscopist in the selection of a strategic approach, such as in deciding whether a colonic lesion should be resected, left in situ, or requires more intensive surgical treatment. Lastly, advanced high-resolution imaging techniques may be more cost effective, such that histopathology of low-risk lesions following resection can be eliminated. The results of these evaluations and comparisons with traditional CE are presented and discussed. Taken together, the benefits provided by these advanced capabilities justify their development, and advocates their use for the treatment and management of colonic polyps.

The learning curve for narrow-band imaging in the diagnosis of precancerous gastric lesions by using Web-based video

BACKGROUND

A simplified narrow-band imaging (NBI) endoscopy classification of gastric precancerous and cancerous lesions was derived and validated in a multicenter study. This classification comes with the need for dissemination through adequate training.

OBJECTIVE

To address the learning curve of this classification by endoscopists with differing expertise and to assess the feasibility of a YouTube-based learning program to disseminate it.

DESIGN

Prospective study.

SETTING

Five centers.

PARTICIPANTS

Six gastroenterologists (3 trainees, 3 fully trained endoscopists [FTs]).

INTERVENTIONS

Twenty tests provided through a Web-based program containing 10 randomly ordered NBI videos of gastric mucosa were taken. Feedback was sent 7 days after every test submission.

MAIN OUTCOME MEASUREMENTS

Measures of accuracy of the NBI classification throughout the time.

RESULTS

From the first to the last 50 videos, a learning curve was observed with a 10% increase in global accuracy, for both trainees (from 64% to 74%) and FTs (from 56% to 65%). After 200 videos, sensitivity and specificity of 80% and higher for intestinal metaplasia were observed in half the participants, and a specificity for dysplasia greater than 95%, along with a relevant likelihood ratio for a positive result of 7 to 28 and likelihood ratio for a negative result of 0.21 to 0.82, were achieved by all of the participants. No constant learning curve was observed for the identification of Helicobacter pylori gastritis and sensitivity to dysplasia. The trainees had better results in all of the parameters, except specificity for dysplasia, compared with the FTs. Globally, participants agreed that the program's structure was adequate, except on the feedback, which should have consisted of a more detailed explanation of each answer.

LIMITATIONS

No formal sample size estimate.

CONCLUSION

A Web-based learning program could be used to teach and disseminate classifications in the endoscopy field. In this study, an NBI classification for gastric mucosal features seems to be easily learned for the identification of gastric preneoplastic lesions.