Blue-light imaging has an additional value to white-light endoscopy in visualization of early Barrett's neoplasia: an international multicenter cohort study

Third-Generation High-Vision Ultrathin Endoscopy Using Texture and Color Enhancement Imaging and Narrow-Band Imaging to Evaluate Barrett's Esophagus

It remains unclear whether texture- and color-enhancement imaging (TXI) and narrow-band imaging (NBI) provide an advantage over white-light imaging (WLI) in Barrett’s esophagus. We compared endoscopic findings and color differences between WLI and image-enhanced endoscopy (IEE) using a third-generation ultrathin endoscope. We retrospectively enrolled 40 patients who evaluated Barrett’s esophagus using WLI, TXI, and NBI. Color differences determined using the International Commission on Illumination 1976 (L∗, a∗, b∗) color space among Barrett’s epithelium, esophageal, and gastric mucosa were compared among the endoscopic findings. As the secondary outcome, we assessed the subjective visibility score among three kinds of endoscopic findings. The prevalence of Barrett’s esophagus and gastroesophageal reflux disease (GERD) in WLI was 82.5% and 47.5%, respectively, and similar among WLI, TXI, and NBI. Color differences between Barrett’s epithelium and esophageal or gastric mucosa on NBI were significantly greater than on WLI (all p < 0.05). However, the color difference between Barrett’s epithelium and esophageal mucosa was significantly greater on NBI than TXI (p < 0.001), and the visibility score of Barrett’s epithelium detection was significantly greater on TXI than NBI (p = 0.022), and WLI (p = 0.016). High-vision, third-generation ultrathin endoscopy using NBI and TXI is useful for evaluating Barrett’s epithelium and GERD compared with WLI alone.

Using texture and colour enhancement imaging to evaluate gastrointestinal diseases in clinical practice: a review

White light imaging (WLI) is the most common endoscopic technique used for screening of gastrointestinal diseases. However, despite the advent of a new processor that offers sufficient clear illumination and other advanced developments in endoscopic instrumentation, WLI alone is inadequate for detecting all gastrointestinal diseases with abnormalities in mucosal discoloration and morphological changes to the mucosal surface. The recent development of image-enhanced endoscopy (IEE) has dramatically improved the detection of gastrointestinal diseases. Texture and colour enhancement imaging (TXI) is a new type of IEE that enhances brightness, surface irregularities, such as elevations or depressions, and subtle colour changes. TXI with two modes, namely modes 1 and 2, can selectively enhance brightness in dark areas of an endoscopic image and subtle tissue differences such as slight morphological or colour changes while simultaneously preventing over-enhancement. Several clinical studies have investigated the efficacy of TXI for detecting and visualizing gastrointestinal diseases, including oesophageal squamous cell carcinoma (ESCC), Barret's epithelium, gastric cancer, gastric mucosal atrophy and intestinal metaplasia. Although TXI is often more useful for detecting and visualizing gastrointestinal diseases than WLI, it remains unclear whether TXI outperforms other IEEs, such as narrow-band imaging (NBI), in similar functions, and whether the performance of TXI modes 1 and 2 are comparable. Therefore, large-scale prospective studies are needed to compare the efficacy of TXI to WLI and other IEEs for endoscopic evaluation of patients undergoing screening endoscopy. Here, we review the characteristics and efficacy of TXI for the detection and visualization of gastrointestinal diseases.Key MessagesTXI mode 1 can improve the visibility of gastrointestinal diseases and qualitative diagnosis, especially for diseases associated with colour changes.The enhancement of texture and brightness with TXI mode 2 enables the detection of diseases, and is ideal for use in the first screening of gastrointestinal tract.

Linked color imaging improves identification of early gastric cancer lesions by expert and non-expert endoscopists

BACKGROUND AND AIMS

Early gastric cancer (EGC) lesions are often subtle and endoscopically poorly visible. The aim of this study is to evaluate the additive effect of linked color imaging (LCI) next to white-light endoscopy (WLE) for identification of EGC, when assessed by expert and non-expert endoscopists.

METHODS

Forty EGC cases were visualized in corresponding WLE and LCI images. Endoscopists evaluated the cases in 3 assessment phases: Phase 1: WLE images only; Phase 2: LCI images only; Phase 3: WLE and LCI images side-to-side. First, 3 expert endoscopists delineated all cases. A high level of agreement between the expert delineations corresponded with a high AND/OR ratio. Subsequently, 62 non-experts indicated their preferred biopsy location. Outcomes of the study are as follows: (1) difference in expert AND/OR ratio; (2) accuracy of biopsy placement by non-expert endoscopists; and (3) preference of imaging modality by non-expert endoscopists.

RESULTS

Quantitative agreement between experts increased significantly when LCI was available (0.58 vs. 0.46, p = 0.007). This increase was more apparent for the more challenging cases (0.21 vs. 0.47, p < 0.001). Non-experts placed the biopsy mark more accurately with LCI (82.3% vs. 87.2%, p < 0.001). Again this increase was more profound for the more challenging cases (70.4% vs. 83.4%, p < 0.001). Non-experts indicated to prefer LCI over WLE.

CONCLUSION

The addition of LCI next to WLE improves visualization of EGC. Experts reach higher consensus on discrimination between neoplasia and inflammation when using LCI. Non-experts improve their targeted biopsy placement with the use of LCI. LCI therefore appears to be a useful tool for identification of EGC.

Kyoto international consensus report on anatomy, pathophysiology and clinical significance of the gastro-oesophageal junction

OBJECTIVE

An international meeting was organised to develop consensus on (1) the landmarks to define the gastro-oesophageal junction (GOJ), (2) the occurrence and pathophysiological significance of the cardiac gland, (3) the definition of the gastro-oesophageal junctional zone (GOJZ) and (4) the causes of inflammation, metaplasia and neoplasia occurring in the GOJZ.

DESIGN

Clinical questions relevant to the afore-mentioned major issues were drafted for which expert panels formulated relevant statements and textural explanations.A Delphi method using an anonymous system was employed to develop the consensus, the level of which was predefined as ≥80% of agreement. Two rounds of voting and amendments were completed before the meeting at which clinical questions and consensus were finalised.

RESULTS

Twenty eight clinical questions and statements were finalised after extensive amendments. Critical consensus was achieved: (1) definition for the GOJ, (2) definition of the GOJZ spanning 1 cm proximal and distal to the GOJ as defined by the end of palisade vessels was accepted based on the anatomical distribution of cardiac type gland, (3) chemical and bacterial (Helicobacter pylori) factors as the primary causes of inflammation, metaplasia and neoplasia occurring in the GOJZ, (4) a new definition of Barrett's oesophagus (BO).

CONCLUSIONS

This international consensus on the new definitions of BO, GOJ and the GOJZ will be instrumental in future studies aiming to resolve many issues on this important anatomic area and hopefully will lead to better classification and management of the diseases surrounding the GOJ.

Enhanced Vascular Features in Porcine Gastrointestinal Endoscopy Using Multispectral Imaging

Endoscopic investigation is a predominant stan-dard while assessing the gastrointestinal tract. Even though it has been rigorously used in diagnostics for many decades, a high miss rate has been recorded. Advanced endoscopic imaging still has not found solutions to problems like early cancer detection, polyp generality, disease classification, etc. One of the less explored techniques to study early cancer detection is spectral imaging which deals with the absorption and reflection spectra of various wavelengths of light by different layers of tissue. To study tissues under various illumination, a multi-spectral light source unit that can be used along with an endoscopy system was developed with 10 different LEDs of very narrow bandwidths. Using this light source, a feasibility study was per-formed on an animal in which the upper GI tract of a porcine model was imaged and sample images were taken for processing from five different sections. Some wavelengths showed better contrast enhancements for visualization of vascular structures. Wavelength 420 nm (violet light) showed better contrast and the gradient of the line profile histogram showed the highest intensity change between the blood vessels and the surrounding mucosa. These enhancements showed that spectral imaging can potentially help in studying tissues for early cancer detection and improved visualization of the G I tract using endoscopy.

Advanced imaging and artificial intelligence for Barrett's esophagus: What we should and soon will do

Barrett’s esophagus (BE) is a well-established risk factor for esophageal adenocarcinoma. It is recommended that patients have regular endoscopic surveillance, with the ultimate goal of detecting early-stage neoplastic lesions before they can progress to invasive carcinoma. Detection of both dysplasia or early adenocarcinoma permits curative endoscopic treatments, and with this aim, thorough endoscopic assessment is crucial and improves outcomes. The burden of missed neoplasia in BE is still far from being negligible, likely due to inappropriate endoscopic surveillance. Over the last two decades, advanced imaging techniques, moving from traditional dye-spray chromoendoscopy to more practical virtual chromoendoscopy technologies, have been introduced with the aim to enhance neoplasia detection in BE. As witnessed in other fields, artificial intelligence (AI) has revolutionized the field of diagnostic endoscopy and is set to cover a pivotal role in BE as well. The aim of this commentary is to comprehensively summarize present evidence, recent research advances, and future perspectives regarding advanced imaging technology and AI in BE; the combination of computer-aided diagnosis to a widespread adoption of advanced imaging technologies is eagerly awaited. It will also provide a useful step-by-step approach for performing high-quality endoscopy in BE, in order to increase the diagnostic yield of endoscopy in clinical practice.

First-in-human pilot study of snapshot multispectral endoscopy for early detection of Barrett's-related neoplasia

SIGNIFICANCE

The early detection of dysplasia in patients with Barrett's esophagus could improve outcomes by enabling curative intervention; however, dysplasia is often inconspicuous using conventional white-light endoscopy.

AIM

We sought to determine whether multispectral imaging (MSI) could be applied in endoscopy to improve detection of dysplasia in the upper gastrointestinal (GI) tract.

APPROACH

We used a commercial fiberscope to relay imaging data from within the upper GI tract to a snapshot MSI camera capable of collecting data from nine spectral bands. The system was deployed in a pilot clinical study of 20 patients (ClinicalTrials.gov NCT03388047) to capture 727 in vivo image cubes matched with gold-standard diagnosis from histopathology. We compared the performance of seven learning-based methods for data classification, including linear discriminant analysis, k-nearest neighbor classification, and a neural network.

RESULTS

Validation of our approach using a Macbeth color chart achieved an image-based classification accuracy of 96.5%. Although our patient cohort showed significant intra- and interpatient variance, we were able to resolve disease-specific contributions to the recorded MSI data. In classification, a combined principal component analysis and k-nearest-neighbor approach performed best, achieving accuracies of 95.8%, 90.7%, and 76.1%, respectively, for squamous, non-dysplastic Barrett's esophagus and neoplasia based on majority decisions per-image.

CONCLUSIONS

MSI shows promise for disease classification in Barrett's esophagus and merits further investigation as a tool in high-definition "chip-on-tip" endoscopes.

Current Status of Image-Enhanced Endoscopy for Early Identification of Esophageal Neoplasms

Advanced esophageal cancer is known to have a poor prognosis. The early detection of esophageal neoplasms, including esophageal dysplasia and early esophageal cancer, is highly important for the accurate treatment of the disease. However, esophageal dysplasia and early esophageal cancer are usually subtle and can be easily missed. In addition to the early detection, proper pretreatment evaluation of the depth of invasion of esophageal cancer is very important for curative treatment. The progression of non-invasive diagnosis via image-enhanced endoscopy techniques has been shown to aid the early detection and estimate the depth of invasion of early esophageal cancer and, as a result, may provide additional opportunities for curative treatment. Here, we review the advancement of image-enhanced endoscopy-related technologies and their role in the early identification of esophageal neoplasms.

Inter-observer variability of experts and trainees for the diagnosis of reflux esophagitis: Comparison of linked color imaging, blue laser imaging, and white light imaging

OBJECTIVES

Diagnosis of reflux esophagitis according to the Los Angeles classification minimal change (LA-M) has a low inter-observer agreement. We aimed to investigate whether the inter-observer agreement of reflux esophagitis was better when expert endoscopists read the endoscopic images, or when the linked color imaging (LCI) or blue laser imaging (BLI)-bright mode was used. In addition, whether the inclusion of LA-M in the definition of reflux esophagitis affected the consistency of the diagnosis was investigated.

METHODS

During upper endoscopy, endoscopic images of the gastroesophageal junction were taken using white light imaging (WLI), BLI-bright, and LCI modes. Four expert endoscopists and four trainees reviewed the images to diagnose reflux esophagitis according to the modified LA classification.

RESULTS

The kappa values for the inter-observer variability for the diagnosis of reflux esophagitis were poor to fair among the experts (κ =  0.22, 0.17, and 0.27 for WLI, BLI-bright, and LCI, respectively) and poor among the trainees (κ =  0.18, 0.08, and 0.14 for WLI, BLI-bright, and LCI). The inter-observer variabilities for the diagnosis of reflux esophagitis excluding LA-M were fair to moderate (κ =  0.42, 0.35, and 0.42 for WLI, BLI-bright, and LCI) among the expert endoscopists and moderate among the trainees (κ = 0.48, 0.43, and 0.51 for WLI, BLI-bright, and LCI).

CONCLUSIONS

The inter-observer agreement for the diagnosis of reflux esophagitis was very low for both the expert endoscopists and the trainees, even using BLI-bright or LCI mode. However, when reflux esophagitis LA-M was excluded from the diagnosis of esophagitis, the degree of inter-observer agreement increased.

Spectral Endoscopy Enhances Contrast for Neoplasia in Surveillance of Barrett's Esophagus

Early detection of esophageal neoplasia enables curative endoscopic therapy, but the current diagnostic standard of care has low sensitivity because early neoplasia is often inconspicuous with conventional white-light endoscopy. Here, we hypothesized that spectral endoscopy could enhance contrast for neoplasia in surveillance of patients with Barrett's esophagus. A custom spectral endoscope was deployed in a pilot clinical study of 20 patients to capture 715 in vivo tissue spectra matched with gold standard diagnosis from histopathology. Spectral endoscopy was sensitive to changes in neovascularization during the progression of disease; both non-dysplastic and neoplastic Barrett's esophagus showed higher blood volume relative to healthy squamous tissue (P = 0.001 and 0.02, respectively), and vessel radius appeared larger in neoplasia relative to non-dysplastic Barrett's esophagus (P = 0.06). We further developed a deep learning algorithm capable of classifying spectra of neoplasia versus non-dysplastic Barrett's esophagus with high accuracy (84.8% accuracy, 83.7% sensitivity, 85.5% specificity, 78.3% positive predictive value, and 89.4% negative predictive value). Exploiting the newly acquired library of labeled spectra to model custom color filter sets identified a potential 12-fold enhancement in contrast between neoplasia and non-dysplastic Barrett's esophagus using application-specific color filters compared with standard-of-care white-light imaging (perceptible color difference = 32.4 and 2.7, respectively). This work demonstrates the potential of endoscopic spectral imaging to extract vascular properties in Barrett's esophagus, to classify disease stages using deep learning, and to enable high-contrast endoscopy. SIGNIFICANCE: The results of this pilot first-in-human clinical trial demonstrate the potential of spectral endoscopy to reveal disease-associated vascular changes and to provide high-contrast delineation of neoplasia in the esophagus. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/12/3415/F1.large.jpg.

Can Coupling Multiple Complementary Methods Improve the Spectroscopic Based Diagnosis of Gastrointestinal Illnesses? A Proof of Principle Ex Vivo Study Using Celiac Disease as the Model Illness

Spectroscopic methods are a promising approach for providing a point-of-care diagnostic method for gastrointestinal mucosa associated illnesses. Such a tool is desired to aid immediate decision making and to provide a faster pathway to appropriate treatment. In this pilot study, Raman, near-infrared, low frequency Raman, and autofluoresence spectroscopic methods were explored alone and in combination for the diagnosis of celiac disease. Duodenal biopsies (n = 72) from 24 participants were measured ex vivo using the full suite of studied spectroscopic methods. Exploratory principal component analysis (PCA) highlighted the origin of spectral differences between celiac and normal tissue with celiac biopsies tending to have higher protein relative to lipid signals and lower carotenoid spectral signals than the samples with normal histology. Classification of the samples based on the histology and overall diagnosis was carried out for all combinations of spectroscopic methods. Diagnosis based classification (majority rule of class per participant) yielded sensitivities of 0.31 to 0.77 for individual techniques, which was increased up to 0.85 when coupling multiple techniques together. Likewise, specificities of 0.50 to 0.67 were obtained for individual techniques, which was increased up to 0.78 when coupling multiple techniques together. It was noted that the use of antidepressants contributed to false positives, which is believed to be associated with increased serotonin levels observed in the gut mucosa in both celiac disease and the use of selective serotonin reuptake inhibitors (SSRIs); however, future work with greater numbers is required to confirm this observation. Inclusion of two additional spectroscopic methods could improve the accuracy of diagnosis (0.78) by 7% over Raman alone (0.73). This demonstrates the potential for further exploration and development of a multispectroscopic system for disease diagnosis.

Barrett's esophagus: current standards in advanced imaging

Esophageal adenocarcinoma (EAC) continues to be one of the fastest rising incident cancers in the Western population with the majority of patients presenting with late stage disease and associated with a dismal 5-year survival rate. Barrett's esophagus (BE) is the only identifiable precursor lesion to EAC. Strategies to screen for and survey BE are critical to detect earlier cancers and reduce morbidity and mortality related to EAC. A high-quality endoscopic examination with careful inspection of the Barrett's segment and adherence to the Seattle protocol for tissue sampling are critical. Advanced imaging modalities offer the potential to improve dysplasia detection, predict histopathology in real time and guide endoscopic eradication therapy (EET). Several technologies have been studied and although most are not yet recommended for routine clinical practice, high definition white light endoscopy (HD-WLE) as well as chromoendoscopy (including virtual chromoendoscopy) improved dysplasia detection in numerous studies supporting their use. Future studies should evaluate the role of artificial intelligence in optimizing detection of dysplasia in BE patients.

Advanced Imaging and Sampling in Barrett's Esophagus: Artificial Intelligence to the Rescue?

Because the current Barrett's esophagus (BE) surveillance protocol suffers from sampling error of random biopsies and a high miss-rate of early neoplastic lesions, many new endoscopic imaging and sampling techniques have been developed. None of these techniques, however, have significantly increased the diagnostic yield of BE neoplasia. In fact, these techniques have led to an increase in the amount of visible information, yet endoscopists and pathologists inevitably suffer from variations in intra- and interobserver agreement. Artificial intelligence systems have the potential to overcome these endoscopist-dependent limitations.

Endoscopic eradication therapy for Barrett's oesophagus: state of the art

PURPOSE OF REVIEW

Barrett's oesophagus is the only identifiable precursor lesion to oesophageal adenocarcinoma. The stepwise progression of Barrett's oesophagus to dysplasia and invasive carcinoma provides the opportunity to intervene and reduce the morbidity and mortality associated with this lethal cancer. Several studies have demonstrated the efficacy and safety of endoscopic eradication therapy (EET) for the management of Barrett's oesophagus related neoplasia. The primary goal of EET is to achieve complete eradication of intestinal metaplasia (CE-IM) followed by enrolment of patients in surveillance protocols to detect recurrence of Barrett's oesophagus and Barrett's oesophagus related neoplasia.

RECENT FINDINGS

EET depends on early and accurate detection and diagnosis of Barrett's oesophagus related neoplasia. All visible lesions should be resected followed by ablation of the remaining Barrett's epithelium. After treatment, patients should be enrolled in endoscopic surveillance programmes. For nondysplastic Barrett's oesophagus, surveillance alone is recommended. For low-grade dysplasia, both surveillance and ablation are reasonable options and should be decided on an individual basis according to patient risk factors and preferences. EET is preferred for high-grade dysplasia and intramucosal carcinoma. For T1b oesophageal adenocarcinoma, esophagectomy remains the standard of care, but endoscopic therapy can be considered in select cases.

SUMMARY

EET is now standard of care and endorsed by societal guidelines for the treatment of Barrett's oesophagus related neoplasia. Future studies should focus on risk stratification models using a combination of clinical data and biomarkers to identify ideal candidates for EET, and to predict recurrence. Optimal therapy for T1b cancer and surveillance strategy after CE-IM are topics that require further study.

Blue-light imaging and linked-color imaging improve visualization of Barrett's neoplasia by nonexpert endoscopists

BACKGROUND AND AIMS

Endoscopic recognition of early Barrett's neoplasia is challenging. Blue-light imaging (BLI) and linked-color imaging (LCI) may assist endoscopists in appreciation of neoplasia. Our aim was to evaluate BLI and LCI for visualization of Barrett's neoplasia in comparison with white-light endoscopy (WLE) alone, when assessed by nonexpert endoscopists.

METHODS

In this web-based assessment, corresponding WLE, BLI, and LCI images of 30 neoplastic Barrett's lesions were delineated by 3 expert endoscopists to establish ground truth. These images were then scored and delineated by 76 nonexpert endoscopists from 3 countries and with different levels of expertise, in 4 separate assessment phases with a washout period of 2 weeks. Assessments were as follows: assessment 1, WLE only; assessment 2, WLE + BLI; assessment 3, WLE + LCI; assessment 4, WLE + BLI + LCI. The outcomes were (1) appreciation of macroscopic appearance and ability to delineate lesions (visual analog scale [VAS] scores); (2) preferred technique (ordinal scores); and (3) assessors' delineation performance in terms of overlap with expert ground truth.

RESULTS

Median VAS scores for phases 2 to 4 were significantly higher than in phase 1 (P < .001). Assessors preferred BLI and LCI over WLE for appreciation of macroscopic appearance (P < .001) and delineation (P < .001). Linear mixed-effect models showed that delineation performance increased significantly in phase 4.

CONCLUSIONS

The use of BLI and LCI has significant additional value for the visualization of Barrett's neoplasia when used by nonexpert endoscopists. Assessors appreciated the addition of BLI and LCI better than the use of WLE alone. Furthermore, this addition led to improved delineation performance, thereby allowing for better acquisition of targeted biopsy samples. (The Netherlands Trial Registry number: NL7541.).

Endoscopic submucosal dissection/endoscopic mucosal resection guidelines for esophageal cancer

The Japan Gastroenterological Endoscopy Society has developed endoscopic submucosal dissection/endoscopic mucosal resection guidelines. These guidelines present recommendations in response to 18 clinical questions concerning the preoperative diagnosis, indications, resection methods, curability assessment, and surveillance of patients undergoing endoscopic resection for esophageal cancers based on a systematic review of the scientific literature.

Deep-Learning System Detects Neoplasia in Patients With Barrett's Esophagus With Higher Accuracy Than Endoscopists in a Multistep Training and Validation Study With Benchmarking

BACKGROUND & AIMS

We aimed to develop and validate a deep-learning computer-aided detection (CAD) system, suitable for use in real time in clinical practice, to improve endoscopic detection of early neoplasia in patients with Barrett's esophagus (BE).

METHODS

We developed a hybrid ResNet-UNet model CAD system using 5 independent endoscopy data sets. We performed pretraining using 494,364 labeled endoscopic images collected from all intestinal segments. Then, we used 1704 unique esophageal high-resolution images of rigorously confirmed early-stage neoplasia in BE and nondysplastic BE, derived from 669 patients. System performance was assessed by using data sets 4 and 5. Data set 5 was also scored by 53 general endoscopists with a wide range of experience from 4 countries to benchmark CAD system performance. Coupled with histopathology findings, scoring of images that contained early-stage neoplasia in data sets 2-5 were delineated in detail for neoplasm position and extent by multiple experts whose evaluations served as the ground truth for segmentation.

RESULTS

The CAD system classified images as containing neoplasms or nondysplastic BE with 89% accuracy, 90% sensitivity, and 88% specificity (data set 4, 80 patients and images). In data set 5 (80 patients and images) values for the CAD system vs those of the general endoscopists were 88% vs 73% accuracy, 93% vs 72% sensitivity, and 83% vs 74% specificity. The CAD system achieved higher accuracy than any of the individual 53 nonexpert endoscopists, with comparable delineation performance. CAD delineations of the area of neoplasm overlapped with those from the BE experts in all detected neoplasia in data sets 4 and 5. The CAD system identified the optimal site for biopsy of detected neoplasia in 97% and 92% of cases (data sets 4 and 5, respectively).

CONCLUSIONS

We developed, validated, and benchmarked a deep-learning computer-aided system for primary detection of neoplasia in patients with BE. The system detected neoplasia with high accuracy and near-perfect delineation performance. The Netherlands National Trials Registry, Number: NTR7072.

Development and validation of the international Blue Light Imaging for Barrett's Neoplasia Classification

BACKGROUND AND AIMS

Detecting subtle Barrett's neoplasia during surveillance endoscopy can be challenging. Blue-light imaging (BLI) is a novel advanced endoscopic technology with high-intensity contrast imaging that may improve the identification of Barrett's neoplasia. The aim of this study was to develop and validate the first classification to enable characterization of neoplastic and non-neoplastic Barrett's esophagus using BLI.

METHODS

In phase 1, descriptors pertaining to neoplastic and non-neoplastic Barrett's esophagus were identified to form the classification, named the Blue Light Imaging for Barrett's Neoplasia Classification (BLINC). Phase 2 involved validation of these component criteria by 10 expert endoscopists assessing 50 BLI images. In phase 3, a web-based training module was developed to enable 15 general (nonexpert) endoscopists to use BLINC. They then validated the classification with an image assessment exercise in phase 4, and their pre- and post-training results were compared.

RESULTS

In phase 1 the descriptors were grouped into color, pit, and vessel pattern categories to form the classification. In phase 2 the sensitivity of neoplasia identification was 96.0% with a very good level of agreement among the experts (κ = .83). In phase 3, 15 general endoscopists completed the training module. In phase 4 their pretraining sensitivity (85.3%) improved significantly to 95.7% post-training with a good level of agreement (κ = .67).

CONCLUSIONS

We developed and validated a new classification system (BLINC) for the optical diagnosis of Barrett's neoplasia using BLI. Despite the limitations of this image-based study with a high prevalence of neoplasia, we believe it has the potential to improve the optical diagnosis of Barrett's neoplasia given the high degree of sensitivity (96%) noted. It is also a promising tool for training in Barrett's esophagus optical diagnosis using BLI.

Imaging for Barrett's esophagus: state of the art

PURPOSE OF REVIEW

Barrett's esophagus is the premalignant condition for esophageal cancer and the diagnosis of esophageal adenocarcinoma on index endoscopy is increasing. Many advanced endoscopic techniques are available and aim to identify Barrett's esophagus-associated neoplasia earlier, thereby preventing progression into malignancy.

RECENT FINDINGS

It is well established adherence to Seattle protocol increases dysplasia detection but leaves large portions of mucosa unsampled. Recent attention has been given to wide-area transepithelial sampling as an additional means of biopsy and shows increased dysplasia detection rates. Many endoscopic techniques aim to increase the success of diagnosis of Barrett's esophagus-associated neoplasia, including probe confocal endomicroscopy, volumetric laser endomicroscopy, and virtual chromoendoscopy. Interestingly, volumetric laser endomicroscopy may also be useful in delineating margins during endoscopic mucosal resection, leading to both diagnostic and therapeutic applications.

SUMMARY

Advanced endoscopic techniques are available to increase detection of Barrett's esophagus-associated neoplasia; however, these remain localized to academic centers of excellence. With recent advancements in both sampling techniques and the potential application of imaging to therapeutics, these techniques are becoming more accessible to community endoscopists.

Evolving screening and surveillance techniques for Barrett's esophagus

Barrett’s esophagus (BE) is a change in the esophageal lining and is known to be the major precursor lesion for most cases of esophageal adenocarcinoma (EAC). Despite an understanding of its association with BE for many years and the falling incidence rates of squamous cell carcinoma of the esophagus, the incidence for EAC continues to rise exponentially. In association with this rising incidence, if the delay in diagnosis of EAC occurs after the onset of symptoms, then the mortality at 5 years is greater than 80%. Appropriate diagnosis and surveillance strategies are therefore vital for BE. Multiple novel optical technologies and other advanced approaches are being utilized to assist in making screening and surveillance more cost effective. We review the current guidelines and evolving techniques that are currently being evaluated.

Barrett's esophagus: novel strategies for screening and surveillance

Barrett’s esophagus is the precursor lesion for esophageal adenocarcinoma. Screening and surveillance of Barrett’s esophagus are undertaken with the goal of earlier detection and lowering the mortality from esophageal adenocarcinoma. The widely used technique is standard esophagogastroduodenoscopy with biopsies per the Seattle protocol for screening and surveillance of Barrett’s esophagus. Surveillance intervals vary depending on the degree of dysplasia with endoscopic eradication therapy confined to patients with Barrett’s esophagus and confirmed dysplasia. In this review, we present various novel techniques for screening of Barrett’s esophagus such as unsedated transnasal endoscopy, cytosponge with trefoil factor-3, balloon cytology, esophageal capsule endoscopy, liquid biopsy, electronic nose, and oral microbiome. In addition, advanced imaging techniques such as narrow band imaging, dye-based chromoendoscopy, confocal laser endomicroscopy, volumetric laser endomicroscopy, and wide-area transepithelial sampling with computer-assisted three-dimensional analysis developed for better detection of dysplasia are also reviewed.