Daniel K. Chan

Comparative diagnostic performance of volumetric laser endomicroscopy and confocal laser endomicroscopy in the detection of dysplasia associated with Barrett’s esophagus

BACKGROUND AND AIMS Probe-based confocal laser endomicroscopy (pCLE) and volumetric laser endomicroscopy (VLE) (also known as frequency domain optical coherence tomography) are advanced endoscopic imaging modalities that may be useful in the diagnosis of dysplasia associated with Barretts esophagus (BE). We performed pCLE examination in ex-vivo EMR specimens and compared the diagnostic performance of using the current VLE scoring index (previously established as OCT-SI) and a novel VLE diagnostic algorithm (VLE-DA) for the detection of dysplasia. METHODS A total of 27 patients with BE enrolled in a surveillance program at a tertiary-care center underwent 50 clinically indicated EMRs that were imaged with VLE and pCLE and classified into neoplastic (N = 34; high-grade dysplasia, intramucosal adenocarcinoma) and nonneoplastic (N = 16; low-grade dysplasia, nondysplastic BE), based on histology. Image datasets (VLE, N = 50; pCLE, N = 50) were rated by 3 gastroenterologists trained in the established diagnostic criteria for each imaging modality as well as a new diagnostic algorithm for VLE derived from a training set that demonstrated association of specific VLE features with neoplasia. Sensitivity, specificity, and diagnostic accuracy were assessed for each imaging modality and diagnostic criteria. RESULTS The sensitivity, specificity, and diagnostic accuracy of pCLE for detection of BE dysplasia was 76% (95% confidence interval [CI], 59-88), 79% (95% CI, 53-92), and 77% (95% CI, 72-82), respectively. The optimal diagnostic performance of OCT-SI showed a sensitivity of 70% (95% CI, 52-84), specificity of 60% (95% CI, 36-79), and diagnostic accuracy of 67%; (95% CI, 58-78). The use of the novel VLE-DA showed a sensitivity of 86% (95% CI, 69-96), specificity of 88% (95% CI, 60-99), and diagnostic accuracy of 87% (95% CI, 86-88). The diagnostic accuracy of using the new VLE-DA criteria was significantly superior to the current OCT-SI (P < .01). CONCLUSION The use of a new VLE-DA showed enhanced diagnostic performance for detecting BE dysplasia ex vivo compared with the current OCT-SI. Further validation of this algorithm in vivo is warranted.

Breath Testing for Barrett’s Esophagus Using Exhaled Volatile Organic Compound Profiling With an Electronic Nose Device

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Jacques Bergman and Patrick Yachimski, Section Editors 61 62 63 64 65 Breath Testing for Barrett’s Esophagus Using Exhaled Volatile Organic Compound Profiling With an Electronic Nose Device 66 67 68 69 70 71 Daniel K. Chan, Liam Zakko, Kavel H. Visrodia, Cadman L. Leggett, Lori S. Lutzke, Magdalen A. Clemens, James D. Allen, Marlys A. Anderson, and Kenneth K. Wang

Diagnosing gastrointestinal illnesses using fecal headspace volatile organic compounds.

Volatile organic compounds (VOCs) emitted from stool are the components of the smell of stool representing the end products of microbial activity and metabolism that can be used to diagnose disease. Despite the abundance of hydrogen, carbon dioxide, and methane that have already been identified in human flatus, the small portion of trace gases making up the VOCs emitted from stool include organic acids, alcohols, esters, heterocyclic compounds, aldehydes, ketones, and alkanes, among others. These are the gases that vary among individuals in sickness and in health, in dietary changes, and in gut microbial activity. Electronic nose devices are analytical and pattern recognition platforms that can utilize mass spectrometry or electrochemical sensors to detect these VOCs in gas samples. When paired with machine-learning and pattern recognition algorithms, this can identify patterns of VOCs, and thus patterns of smell, that can be used to identify disease states. In this review, we provide a clinical background of VOC identification, electronic nose development, and review gastroenterology applications toward diagnosing disease by the volatile headspace analysis of stool.

Su1352 Detection of Clostridium difficile-Infected Stool by Electronic-Nose Analysis of Fecal Headspace Volatile Organic Compounds

Introduction Electronic-noses (e-noses) have the ability of converting smells to digital signatures. By interacting with volatile organic compounds (VOCs) emitted by metabolic end-products of disease, e-noses create distinct patterns of aggregate VOCs to generate unique signatures that can be used to identify disease. The detection of Clostridium difficile (C. diff) by VOCs is prototypic as it has been successfully identified by scent using canines. We seek to pilot a novel portable e-nose device to profile fecal headspace to diagnose C. diff infection. Methods We are prospectively enrolling patients undergoing stool testing by C. diff PCR for infectious diarrhea for fecal headspace analysis using the Aetholab e-nose (eNose Company, Zutphen, NL). Stool specimens were obtained from the clinical microbiology lab of our institution within 7 days of ambient collection and aliquots of 10-ml of homogenized stool were transferred to disposable analysis bottles. The e-nose circulates fecal headspace gas within each analysis bottle to allow interaction with its respective sensor array. Each sensor array comprises of three metal-oxide sensors that undergo reversible redox reactions with VOCs at an electrochemical interface. Electrical resistance changes are measured by applying a 32-point thermal cycle to the sensor array generating a digital signature (Figure 1). This process has been shown to interact with a wide range of VOCs. Combined data from the 3 sensors in 7 combinations (A, B, C, AB, AC, AC, ABC) is permuted across 3 scaling factors generating a total of 21 data sets per analysis. These are then compressed through a multi-way analysis to reduce the large amount of data to avoid spurious associations. Finally each samples compressed dataset is introduced into an artificial neural network (ANN) using a supervised approach. The 5 best models generated using a leave-one-out approach are used to obtain the reported results. Results Separation was observed using all 20 C. diff-PCR positive and 53 C. diff-PCR negative stools. The ROC curve for this model is shown in Figure 2 with an AUC = 0.85. This demonstrated 80% sensitivity, 85% specificity with 84% accuracy. The positive predictive value was 0.67 and the negative predictive value 0.92. Matthews correlation coefficient was 0.64. Conclusion Through the use of a pattern-recognition e-nose device it is possible to distinguish C. diffinfected stools. This is the first time that this type of device has been used for this diagnosis, and also the first time this e-nose has been applied for fecal headspace analysis of infectious disease. This indicates that C. diff testing can translate into a point-of-care evaluation.

Shining a new narrow band of light on old problems.

Improvements in narrow band imaging (NBI) may provide an improved view of colonic mucosa for detection of polyps and adenomas. In this issue, Leung et al. report findings to suggest that this next-generation NBI technology is superior to conventional high-definition white light endoscopy in polyp detection. These findings are based on brighter illumination, which has been a problem with older generations of NBI, which did not increase polyp detection but were useful for polyp characterization. Although these findings are very promising for this new role of second-generation NBI in polyp detection, the study must be viewed with consideration of the history of the older NBI system, the analysis of which through multiple positive and negative studies ultimately led to the conclusion that it was not beneficial for detection.

Optical Coherence Tomography: Clinical Applications in Gastrointestinal Endoscopy

Optical coherence tomography (OCT) is a high-resolution imaging modality that uses principles of light interferometry. It has achieved clinical application in several other specialties such as ophthalmology and cardiology where its high resolution and deeper penetration into the surface permits much more detailed examination of the mucosa. In the field of gastroenterology, the technology has evolved through several iterations beginning with a focal magnifying imaging technique and evolving into currently a widefield imaging modality that can scan a relatively large area of mucosa with high resolution. OCT has been used to detect dysplasia in Barrett’s esophagus, differentiate between inflammatory bowel disease subtypes, and define pancreaticobiliary strictures, among other applications. This chapter provides an overview of the principles of OCT and its applications in gastrointestinal imaging with emphasis on recently commercially available OCT technologies.

Sa1890 Effacement of the Mucosal Layer Observed With Volumetric Laser Endomicroscopy Is Not Associated With Mucosal Density or Thickness of Barrett's Esophagus

change was determined as the ratio of the level of gene expression in treated cells to that in untreated control cells grown in parallel. Results: NES-B10T cells treated with A+B for 30 weeks were round and aggregated in clumps (columnar morphological features), whereas untreated cells were spindle-shaped and dispersed (squamous features). Treated NES-B10T cells showed increased expression of CDX2 (11-fold), SOX9 (238-fold), villin (2-fold) and Cox-2 (1,310-fold). Treated NES-B10T cells also showed increased immunofluorescence for mAb DAS-1, (P< 0.04), and also for CK8 (P< 0.02). Immunofluorescence for CK4 is decreased. In contrast to these changes observed in NES-B10T squamous cells (derived from a patient with BE), NES-G2T cells (derived from a patient who had GERD without BE) exhibited no morphological, gene expression or immunofluorescence changes after 30 weeks of A+B treatment. Conclusion: Esophageal squamous cells exposed repeatedly to acid and bile salts in vitro exhibit columnar differentiation typical of Barretts metaplasia. This finding is novel and supports the hypothesis that BE results from reflux-induced transdifferentiation or transcommitment of native esophageal cells. The absence of these changes in similarlytreated squamous cells from a patient who had GERD without BE suggest that certain host genetic factors, in addition to acid and bile reflux, are required for the development of Barretts metaplasia.

423 Can In-Vivo Volumetric Laser Endomicroscopy Detect Barrett's Esophagus Dysplasia Missed on Surveillance Biopsies?

G A A b st ra ct s using VLE for surveillance of dysplasia associated with BE require the interpretation of large volumes of VLE image data by an expert to identify pathologies of interest. The main objective of the current study is to explore the feasibility of developing a diagnostic computer algorithm to assist in the interpretation of VLE image data. METHODS: Retrospective data analysis study. De-identified VLE images from the esophagus obtained with the NvisionVLE radial OCT system (NinePoint Medical, Cambridge, MA), along with their corresponding validated pathology classifications were used in the study. We used the discrete wavelet transform to analyze and characterize the local spatial distribution of gray levels in the VLE images. Three classification problems relevant to the current clinical use of VLE in BE were considered: distinguishing gastric cardia (GC) from BE (analogous to determining the location of the esophagogastric junction), normal squamous (NS) from BE (finding the top of the BE segment), and non-dysplastic BE (NDBE) from BE with dysplasia (BED). Features extracted from the wavelet components that were found to be statistically significant based on a 2sample t-test were used as inputs to a Naive Bayes classifier. Leave-one-out cross-validation was used to obtain performance estimates for each of the classification problems. RESULTS: A total of 60 images (18 from NS, 15 from NDBE, 14 from BED, and 13 from GC) from 38 patients were analyzed. Distinguishing GC from BE (NDBE as well as BED) resulted in per-class accuracies of 77% and 93% respectively. Distinguishing NS from BE resulted in per-class accuracies of 83% for both classes. A sensitivity of 86% and specificity of 93% were obtained when distinguishing NDBE from BED. CONCLUSION: Real-time identification of potential areas of dysplasia by VLE imaging can help to better target biopsies when compared to the standard protocol of random biopsies. Computer-assisted interpretation of VLE images may provide a novel approach to making objective, real-time assessments of pathologies relevant to dysplasia surveillance in BE. Our results offer promise for the feasibility of such an approach, where VLE images could be instantaneously analyzed and interpreted on-the-fly to guide endoscopic diagnosis and treatment.

Sa1070 Has High Grade Dysplasia in Barrett's Esophagus Changed Over the Last Decade?

Background: The overall risk of progression to esophageal adenocarcinoma (EAC) in BE subjects without dysplasia is lower than previously estimated. There is hence lack of consensus on the effectiveness of current surveillance programs. Stratification of risk of progression is appealing, as it may help identify BE patients at higher risk who can be monitored more intensively or offered endoscopic therapy. Though several studies have identified factors predicting progression, evidence on several clinically relevant risk factors influencing progression is not consistent. We aimed to identify the predictors of progression in BE subjects without high grade dysplasia by performing a systematic review and meta-analysis of relevant studies. Methods: A comprehensive search of several databases including PubMed, EMBASE, and Web of Science databases (earliest inception to July 28th, 2014) was performed and studies reporting outcomes of BE cohorts under surveillance were identified. We included studies that reported predictors of progression to HGD/ EAC as an outcome in patients with non-dysplastic BE (NDBE) and BE-low grade dysplasia (LGD). A pooled estimate (odds ratio) of the potential of age, sex, smoking, alcohol use, BMI, baseline LGD (vs NDBE), BE length, and medication use in predicting progression to HGD/EAC in NDBE/ LGD patients was calculated. Results: 23 studies reporting predictors of progression as an outcome were identified from the systematic review. 1231 events in 74943 patients in 204926.2 patient years of follow-up were analyzed. Table 1 shows the pooled odds ratio (OR) of predictors analyzed. Increasing age, male sex, ever smoking (current or past), and increasing BE segment length were predictive of increased risk of progression to HGD/EAC with low heterogeneity (9-13 studies). Patients with LGD had an almost four fold increased risk of progression compared to those with no dysplasia. NSAID and statin use were protective against progression to HGD/EAC without heterogeneity. Alcohol use and obesity as measured by BMI did not influence progression rates. Conclusion: Age, male sex, ever smoking (current or past), and BE length are predictive of increased risk of progression to HGD/ EAC. Subjects with baseline LGD are at 4 times increased risk of progression compared to those without dysplasia. These factors may be used to risk stratify BE subjects as part of a prediction score, to identify those who could potentially benefit from intensive surveillance or endoscopic therapy. Smoking is a modifiable risk factor for cancer prevention in BE subjects. Table 1: Pooled odds ratio (OR) of predictors of progression to HGD / EAC.