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Patients with Barrett's esophagus are at an increased risk to develop esophageal cancer and, therefore, undergo regular endoscopic surveillance. Early detection of neoplasia enables endoscopic treatment, which improves outcomes. However, early Barrett's neoplasia is easily missed during endoscopic surveillance. This study investigates multidiameter single fiber reflectance spectroscopy (MDSFR) to improve Barrett's surveillance. Based on the concept of field cancerization, it may be possible to identify the presence of a neoplastic lesion from measurements elsewhere in the esophagus or even the oral cavity. In this study, MDSFR measurements are performed on non-dysplastic Barrett's mucosa, squamous mucosa, oral mucosa, and the neoplastic lesion (if present). Based on logistic regression analysis on the scattering parameters measured by MDSFR, a classifier is developed that can predict the presence of neoplasia elsewhere in the Barrett's segment from measurements on the non-dysplastic Barrett's mucosa (sensitivity 91%, specificity 71%, AUC = 0.77). Classifiers obtained from logistic regression analysis for the squamous and oral mucosa do not result in an AUC significantly different from 0.5., (© 2021 Wiley-VCH GmbH.)

Volumetric laser endomicroscopy (VLE) is a balloon-based technique, which provides a circumferential near-microscopic scan of the esophageal wall layers, and has potential to improve Barrett's neoplasia detection. Interpretation of VLE imagery in Barrett's esophagus (BE) however is time-consuming and complex, due to a large amount of visual information and numerous subtle gray-shaded VLE images. Computer-aided detection (CAD), analyzing multiple neighboring VLE frames, might improve BE neoplasia detection compared to automated single-frame analyses. This study is to evaluate feasibility of automatic data extraction followed by CAD using a multiframe approach for detection of BE neoplasia. Prospectively collected ex-vivo VLE images from 29 BE-patients with and without early neoplasia were retrospectively analyzed. Sixty histopathology-correlated regions of interest (30 nondysplastic vs. 30 neoplastic) were assessed using different CAD systems. Multiple neighboring VLE frames, corresponding to 1.25 millimeter proximal and distal to each region of interest, were evaluated. In total, 3060 VLE frames were analyzed via the CAD multiframe analysis. Multiframe analysis resulted in a significantly higher median AUC (median level = 0.91) compared to single-frame (median level = 0.83) with a median difference of 0.08 (95% CI, 0.06-0.10), P < 0.001. A maximum AUC of 0.94 was reached when including 22 frames on each side using a multiframe approach. In total, 3060 VLE frames were automatically extracted and analyzed by CAD in 3.9 seconds. Multiframe VLE image analysis shows improved BE neoplasia detection compared to single-frame analysis. CAD with multiframe analysis allows for fast and accurate VLE interpretation, thereby showing feasibility of automatic full scan assessment in a real-time setting during endoscopy., (© The Author(s) 2019. Published by Oxford University Press on behalf of International Society for Diseases of the Esophagus. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background and Aims: Endoscopic features of early neoplasia in Barrett's esophagus (BE) are subtle. Blue-light imaging (BLI) may improve visualization of neoplastic lesions. The aim of this study was to evaluate BLI in visualization of Barrett's neoplasia., Methods: Corresponding white-light endoscopy (WLE) and BLI images of 40 BE lesions were obtained prospectively and assessed by 6 international experts in 3 assessments. Each assessment consisted of overview and magnification images. Assessments were as follows: assessment 1, WLE only; assessment 2, BLI only; and assessment 3, corresponding WLE and BLI images. Outcome parameters were as follows: (1) appreciation of macroscopic appearance and surface relief (visual analog scale scores); (2) ability to delineate lesions (visual analog scale scores); (3) preferred technique for delineation (ordinal scores); and (4) quantitative agreement on delineations (AND/OR scores)., Results: Experts appreciated BLI significantly better than WLE for visualization of macroscopic appearance (median 8.0 vs 7.0, P < .001) and surface relief (8.0 vs 6.0, P < .001). For both overview and magnification images, experts appreciated BLI significantly better than WLE for ability to delineate lesions (8.0 vs 6.0, P < .001 and 8.0 vs 5.0, P < .001). There was no overall significant difference in AND/OR scores of WLE + BLI when compared with WLE, yet agreement increased significantly with WLE + BLI for cases with a low baseline AND/OR score on WLE, both in overview (mean difference, 0.15; P = .015) and magnification (mean difference, 0.10; P = .01)., Conclusions: BLI has additional value for visualization of BE neoplasia. Experts appreciated BLI better than WLE for visualization and delineation of BE neoplasia. Quantitative agreement increased significantly when BLI was offered next to WLE for lesions that were hard to delineate with WLE alone. (ISRCTN registry study ID: ISRCTN15916689.)., (Copyright © 2019 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

The incidence of Barrett cancer is increasing rapidly and current screening protocols often miss the disease at an early, treatable stage. Volumetric Laser Endomicroscopy (VLE) is a promising new tool for finding this type of cancer early, capturing a full circumferential scan of Barrett's Esophagus (BE), up to 3-mm depth. However, the interpretation of these VLE scans can be complicated, due to the large amount of cross-sectional images and the subtle grayscale variations. Therefore, algorithms for automated analysis of VLE data can offer a valuable contribution to its overall interpretation. In this study, we broadly investigate the potential of Computer-Aided Detection (CADe) for the identification of early Barrett's cancer using VLE. We employ a histopathologically validated set of ex-vivo VLE images for evaluating and comparing a considerable set of widely-used image features and machine learning algorithms. In addition, we show that incorporating clinical knowledge in feature design, leads to a superior classification performance and additional benefits, such as low complexity and fast computation time. Furthermore, we identify an optimal tissue depth for classification of 0.5-1.0 mm, and propose an extension to the evaluated features that exploits this phenomenon, improving their predictive properties for cancer detection in VLE data. Finally, we compare the performance of the CADe methods with the classification accuracy of two VLE experts. With a maximum Area Under the Curve (AUC) in the range of 0.90-0.93 for the evaluated features and machine learning methods versus an AUC of 0.81 for the medical experts, our experiments show that computer-aided methods can achieve a considerably better performance than trained human observers in the analysis of VLE data., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Optical coherence tomography (OCT) is an imaging technique optically analogous to ultrasound that can generate depth-resolved images with micrometer-scale resolution. Advances in fiber optics and miniaturized actuation technologies allow OCT imaging of the human body and further expand OCT utilization in applications including but not limited to cardiology and gastroenterology. This review article provides an overview of current OCT development and its clinical utility in the gastrointestinal tract, including disease detection/differentiation and endoscopic therapy guidance, as well as a discussion of its future applications., ((2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).)

Background and Aims: Volumetric laser endomicroscopy (VLE) is an advanced imaging system that provides a near-microscopic resolution scan of the esophageal wall layers up to 3-mm deep. VLE has the potential to improve detection of early neoplasia in Barrett's esophagus (BE). However, interpretation of VLE images is complex because of the large amount of data that need to be interpreted in real time. The aim of this study was to investigate the feasibility of a computer algorithm to identify early BE neoplasia on ex vivo VLE images., Methods: We used 60 VLE images from a database of high-quality ex vivo VLE-histology correlations, obtained from BE patients ± neoplasia (30 nondysplastic BE [NDBE] and 30 high-grade dysplasia/early adenocarcinoma images). VLE features from a recently developed clinical VLE prediction score for BE neoplasia served as input for the algorithm: (1) higher VLE surface than subsurface signal and (2) lack of layering. With this input, novel clinically inspired algorithm features were developed, based on signal intensity statistics and grayscale correlations. For comparison, generic image analysis methods were examined for their performance to detect neoplasia. For classification of the images in the NDBE or neoplastic group, several machine learning methods were evaluated. Leave-1-out cross-validation was used for algorithm validation., Results: Three novel clinically inspired algorithm features were developed. The feature "layering and signal decay statistics" showed the optimal performance compared with the other clinically features ("layering" and "signal intensity distribution") and generic image analyses methods, with an area under the receiver operating characteristic curve (AUC) of .95. Corresponding sensitivity and specificity were 90% and 93%, respectively. In addition, the algorithm showed a better performance than the clinical VLE prediction score (AUC .81)., Conclusions: This is the first study in which a computer algorithm for BE neoplasia was developed based on VLE images with direct histologic correlates. The algorithm showed good performance to detect BE neoplasia in ex vivo VLE images compared with the performance of a recently developed clinical VLE prediction score. This study suggests that an automatic detection algorithm has the potential to assist endoscopists in detecting early neoplasia on VLE. Future studies on in vivo VLE scans are needed to further validate the algorithm., (Copyright © 2017 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

Background and Aim: Volumetric laser endomicroscopy (VLE) provides a circumferential scan of the esophageal wall layers and has potential to improve detection of neoplasia in Barrett's esophagus (BE). The novel VLE laser marking system enables direct in vivo marking of suspicious areas as identified on VLE. These laser marked areas can subsequently be targeted for biopsies. The aim was to evaluate the visibility and positional accuracy of laser marks (LMs) in different esophageal tissue types on white light endoscopy (WLE) and VLE., Methods: Patients with BE with or without neoplasia underwent imaging with VLE. Protocol refinements were practiced in a learning phase. In the second phase, visibility of LMs was assessed by random marking in squamous, BE, and gastric tissue. In phase 3, positional accuracy of the LMs was tested by identifying and laser marking surrogate targets (endoscopically placed cautery marks). In the final phase, the most suspicious areas for neoplasia were identified in each patient using VLE, targeted by LMs, and biopsy samples subsequently obtained., Results: Sixteen patients with BE were included (14 men; median age, 68 years), 1 of whom was included twice in different study phases. Worst histologic diagnoses were 9 non-dysplastic Barrett's esophagus (NDBE), 3 low-grade dysplasia (LGD), 4 high-grade dysplasia (HGD), and 1 early adenocarcinoma (EAC). In total, 222 LMs were placed, of which 97% was visible on WLE. All LMs were visible on VLE directly after marking, and 86% could be confirmed during post hoc analysis. LM targeting was successful with positional accuracy in 85% of cautery marks. Inaccurate targeting was caused by system errors or difficult cautery mark visualization on VLE. In the final phase (5 patients), 18 areas suspicious on VLE were identified, which were all successfully targeted by LMs (3 EAC, 3 HGD, 1 LGD, and 11 NDBE). Mean VLE procedure time was 22 minutes (±6 minutes standard deviation); mean endoscopy time was 56 minutes (±17 minutes). No adverse events were reported., Conclusions: This first-in-human study of VLE-guided laser marking was found to be feasible and safe in 17 procedures. Most LMs were visible on WLE and VLE. Targeting VLE areas of interest proved to be highly successful. VLE-guided laser marking may improve the detection and delineation of Barrett's neoplasia in the future., (Copyright © 2017 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

Early neoplasia in Barrett’s esophagus (BE) is difficult to detect. Volumetric laser endomicroscopy (VLE) incorporates optical coherence tomography, providing a circumferential scan of the esophageal wall layers. The attenuation coefficient (μVLE) quantifies decay of detected backscattered light versus depth, and could potentially improve BE neoplasia detection. The aim is to investigate feasibility of μVLE for identification of early BE neoplasia. In vivo and ex vivo VLE scans with histological correlation from BE patients ± neoplasia were used. Quantification by μVLE was performed manually on areas of interest (AoIs) to differentiate neoplasia from nondysplastic (ND)BE. From ex vivo VLE scans from 16 patients (13 with neoplasia), 68 AoIs were analyzed. Median μVLE values (mm−1) were 3.7 [2.1 to 4.4 interquartile range (IQR)] for NDBE and 4.0 (2.5 to 4.9 IQR) for neoplasia, not statistically different (p=0.82). Fourteen in vivo scans were used: nine from neoplastic and five from NDBE patients. Median μVLE values were 1.8 (1.5 to 2.6 IQR) for NDBE and 2.1 (1.9 to 2.6 IQR) for neoplasia, with no statistically significant difference (p=0.37). In conclusion, there was no significant difference in μVLE values in VLE scans from early neoplasia versus NDBE. Future studies with a larger sample size should explore other quantitative methods for detection of neoplasia during BE surveillance.

Background and Aims: Volumetric laser endomicroscopy (VLE) provides a circumferential scan that enables visualization of the subsurface layers of the esophageal wall at 7 μm resolution. The aims of this study were to identify VLE features of Barrett's esophagus (BE) neoplasia and to develop a VLE prediction score., Methods: A database of VLE images from endoscopic resection specimens, precisely correlated with histology, from patients with BE with and without neoplasia was used. Features potentially predictive for early BE neoplasia were identified by unblinded evaluation of 25 VLE-histology images. In a learning phase, 20 VLE images with or without BE neoplasia were scored by 2 VLE experts, blinded to histology. A prediction score was created by using multivariable logistic regression analyses and validated by scoring 40 VLE images (50% neoplastic) by using area under receiver operating characteristic (ROC) curve (AUC) analysis., Results: Three VLE features independently predictive for BE neoplasia were identified: (1) lack of layering; (2) higher surface than subsurface signal; (3) presence of irregular, dilated glands/ducts. A VLE neoplasia prediction score was developed with the following: (1) 6 points; (2) 6 or 8 points for equal or higher surface signal; and (3) 5 points. The ROC curve of this prediction score showed an AUC of 0.81 (95% confidence interval, 0.71-0.90). A cut-off value of ≥8 was associated with sensitivity and specificity of 83% and 71%, respectively., Conclusions: When high-quality ex vivo VLE-histology correlation was used, the VLE features of layering, surface signal, and irregular glands/ducts were independently and significantly associated with BE neoplasia. A VLE prediction score for BE neoplasia was developed and validated, with promising accuracy. (Clinical trial registration number: NCT01862666.)., (Copyright © 2017. Published by Elsevier Inc.)

Optical coherence tomography (OCT) is an optical diagnostic modality that can acquire cross-sectional images of the microscopic structure of the esophagus, including Barrett's esophagus (BE) and associated dysplasia. We developed a swallowable tethered capsule OCT endomicroscopy (TCE) device that acquires high-resolution images of entire gastrointestinal (GI) tract luminal organs. This device has a potential to become a screening method that identifies patients with an abnormal esophagus that should be further referred for upper endoscopy. Currently, the characterization of the OCT-TCE esophageal wall data set is performed manually, which is time-consuming and inefficient. Additionally, since the capsule optics optimally focus light approximately 500 µm outside the capsule wall and the best quality images are obtained when the tissue is in full contact with the capsule, it is crucial to provide feedback for the operator about tissue contact during the imaging procedure. In this study, we developed a fully automated algorithm for the segmentation of in vivo OCT-TCE data sets and characterization of the esophageal wall. The algorithm provides a two-dimensional representation of both the contact map from the data collected in human clinical studies as well as a tissue map depicting areas of BE with or without dysplasia. Results suggest that these techniques can potentially improve the current TCE data acquisition procedure and provide an efficient characterization of the diseased esophageal wall.

Background and Aims: The prevalence and clinical relevance of buried Barrett's glands (BB) after radiofrequency ablation (RFA) in Barrett's esophagus (BE) are debated. Recent optical coherence tomography studies demonstrated a high prevalence of BBs. Direct histological correlation, however, has been lacking. Volumetric laser endomicroscopy (VLE) is a second-generation optical coherence tomography system capable of scanning a large surface of the esophageal wall layers with low-power microscopy resolution. The aim was to evaluate whether post-RFA subsquamous glandular structures (SGSs), detected with VLE, actually correspond to BBs by pursuing direct histological correlation with VLE images., Methods: In vivo VLE was performed to detect SGSs in patients with endoscopic regression of BE post-RFA. A second in vivo VLE scan was performed to confirm correct delineation of the SGSs. After endoscopic resection, the specimens were imaged ex vivo with VLE. Extensive histological sectioning of SGS areas was performed, and all histology slides were evaluated by an expert BE pathologist., Results: Seventeen patients underwent successful in vivo VLE (histological diagnosis before endoscopic treatment: early adenocarcinoma in 8 patients and high-grade dysplasia in 9). In 4 of 17 patients, no SGSs were identified during VLE, and a random resection was performed. In the remaining 13 patients (76%), VLE detected SGS areas, which were all confirmed on a second in vivo VLE scan and subsequently resected. Most SGSs identified by VLE corresponded to normal histological structures (eg, dilated glands and blood vessels). However, 1 area containing BBs was found on histology. No specific VLE features to distinguish between BBs and normal SGSs were identified., Conclusions: VLE is able to detect subsquamous esophageal structures. One area showed BBs beneath endoscopically normal-appearing neosquamous epithelium; however, most post-RFA SGSs identified by VLE correspond to normal histological structures. (, Clinical Trial Registration Number: NTR4056.)., (Copyright © 2016 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

Evaluation of patients with Barrett's esophagus (BE) using dye-based chromoendoscopy, optical chromoendoscopy, autofluorescence imaging, or confocal laser endomicroscopy does not significantly increase the number of patients with a diagnosis of early neoplasia compared with high-definition white light endoscopy (HD-WLE) with random biopsy analysis. These newer imaging techniques are not more effective in standard surveillance of patients with BE because the prevalence of early neoplasia is low and HD-WLE with random biopsy analysis detects most cases of neoplasia. The evaluation and treatment of patients with BE and early stage neoplasia should be centralized in tertiary referral centers, where procedures are performed under optimal conditions, by expert endoscopists. Lesions that require resection are almost always detected by HD-WLE, although advanced imaging techniques can detect additional flat lesions. However, these are of limited clinical significance because they are effectively eradicated by ablation therapy. No endoscopic imaging technique can reliably assess submucosal or lymphangio invasion. Endoscopic resection of early stage neoplasia in patients with BE is important for staging and management. Optical chromoendoscopy can also be used to evaluate lesions before endoscopic resection and in follow-up after successful ablation therapy.