Volumetric laser endomicroscopy interpretation and feature analysis in dysplastic Barrett's esophagus

Barrett's Epithelial Thickness, Assessed by Volumetric Laser Endomicroscopy, Is Associated With Response to Radiofrequency Ablation

BACKGROUND & AIMS

Radiofrequency ablation (RFA) is the most common treatment for flat Barrett's esophagus (BE), but reasons for varying outcomes are poorly understood. A recently developed contrast-enhancement algorithm allows reliable measurement of Barrett's epithelial thickness (BET) from volumetric laser endomicroscopy (VLE) images and correlation with response to RFA. Using this algorithm, we investigated whether patients with thicker Barrett's mucosa are less likely to respond to RFA. In the future, this algorithm may guide choice of RFA dosing or endoscopic resection.

METHODS

We performed a retrospective analysis on all patients with BE who received a baseline VLE scan between May 2015 and October 2016, followed by RFA and 1 follow-up exam, from 14 institutions participating in the United States VLE registry. We measured BET on equidistant locations by estimating the distance between the esophageal surface and the superficial edge of the deepest lamina propria. The primary outcome variable was the percentage reduction in Prague length; secondary outcome variables were complete remission of intestinal metaplasia (CRIM) and presence of strictures after 12 months.

RESULTS

Images from 61 patients were included in our final analysis. Mean BET per patient ranged from 224 μm to 705 μm. A 100 μm thicker mean BET per patient resulted in a 12% lower response to treatment, measured by a reduction of Prague length (P = .03), after adjustment for confounders. We found an association between mean BET and CRIM, but not with stricture formation.

CONCLUSIONS

Based on measurements on contrast-enhanced VLE images, we found that BET correlates with response to RFA. For clinical implementation, larger studies with a standardized follow-up and development of computer-aided image analysis systems are needed.

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.

Improved Barrett's neoplasia detection using computer-assisted multiframe analysis of volumetric laser endomicroscopy

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.

Interpretation of volumetric laser endomicroscopy in Barrett's esophagus using image enhancement software

Image interpretation of Barrett's esophagus (BE) with volumetric laser endomicroscopy (VLE) can be enhanced by image processing software that highlights established features using a color-graded scale (intelligent real-time image segmentation, IRIS). This study aims to provide a description of IRIS features of various gastroesophageal tissue types using histologic correlation. A database of 80 VLE laser-marked targets with histologic correlation was reviewed for various tissue types. IRIS was applied off-line to the VLE scans, laser-marked targets were identified, and feature review was performed. Squamous epithelium targets (N = 7) showed IRIS layered architecture with lack of surface hyper-reflectivity and epithelial glands. Gastric cardia targets (N = 10) showed absent layering (100%) and surface hyper-reflectivity with epithelial glands (40%). Nondysplastic BE targets (N = 39) showed surface hyper-reflectivity (64%), epithelial glands (51%), and lack of layering (74%). Targets of BE with early neoplasia (N = 24), showed surface hyper-reflectivity (96%), epithelial glands (67%), and lack of layering (96%). IRIS features that characterize each tissue type appear to mirror the nonenhanced VLE counterparts that define them.

Volumetric laser endomicroscopy and optical coherence tomography in Barrett's esophagus: a systematic review and meta-analysis

Background and study aims  Endoscopic imaging of Barrett's esophagus (BE) with advanced technologies, such as optical coherence tomography (OCT) and volumetric laser endomicroscopy (VLE), allows targeted biopsies and may reduce the number of random biopsies to detect esophageal neoplasia in the early stages during endoscopic BE surveillance. The aim of this study was to evaluate the accuracy of OCT and VLE in diagnosis of intestinal metaplasia, dysplasia, and high-grade dysplasia (HGD), and intramucosal carcinoma (IMC) in BE. Patients and methods  In this systematic review and meta-analysis, the primary outcome measure was diagnostic accuracy of OCT and VLE, in comparison with the gold standard. In the meta-analysis, we calculated sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), and diagnostic odds ratio (DOR) for both methods. We performed analyses by patient and by lesion. Results  We evaluated 14 studies involving a collective total of 721 patients and 1565 lesions. In the analysis by lesion, VLE showed a pooled sensitivity, specificity, LR+, LR-, DOR, and SROC AUC of 85 %, 73 %, 3.2, 0.21, 15.0, and 0.87, respectively, for detection of HGD/IMC. In the analysis by lesion for detection of HGD/EAC, OCT showed a pooled sensitivity, specificity, LR+, LR-, DOR, and summary receiver operating characteristic area under the curve of 89 %, 91 %, 9.6, 0.12, 81.0, and 0.95, respectively. The accuracy of OCT in identifying intestinal metaplasia showed a pooled sensitivity, specificity, LR+, LR-, and DOR of 92 %, 81 %, 5.06, 0.091, and 55.58, respectively. Conclusion  OCT- and VLE-guided targeted biopsies could improve detection of dysplasia and neoplasia. Further studies could determine whether the use of such biopsies might replace the current protocol.

Outcome of endoscopic mucosal resection in Barrett's esophagus determined by systematic quantification of epithelial glands using volumetric laser endomicroscopy

BACKGROUND

Dysplastic Barrett's esophagus (BE) lesions ≤2 cm in size can be targeted for en-bloc endoscopic mucosal resection (EMR). White-light endoscopy can underestimate the size of a lesion, limiting complete resection. Volumetric laser endomicroscopy (VLE) provides high-resolution cross-sectional imaging of BE. Epithelial glands are a VLE feature associated with BE dysplasia. We study the association between VLE gland quantification and outcome of resection.

METHODS

EMR specimens of BE lesions targeted for en-bloc resection were imaged with VLE using an established protocol. Manual and automated quantification of epithelial glands was performed blinded to resection outcome. The presence of epithelial glands at the resection margins was recorded. Histologic en-bloc (R0) resection of the targeted lesion was defined by the absence and incomplete (R1) resection by the presence of dysplasia/neoplasia at specimen margins.

RESULTS

Thirty-seven EMRs with a mean (standard deviation) size of 1.04 (0.37) cm were imaged with VLE. The highest grade of dysplasia found was low-grade dysplasia (n = 12), high-grade dysplasia (n = 19), and intramucosal cancer (n = 6). The en-bloc resection rate was 37.8% (R0, n = 14; R1, n = 23). The mean (standard deviation) number of epithelial glands quantified with VLE was 13.0 (6.7) and 28.8 (23.9) for R0 and R1 specimens, respectively, with a significant mean difference of 15.8 glands (95% confidence interval, 2-29; P = .02). The presence of glands at the specimen margin was associated with incomplete resection (P < .001).

CONCLUSION

Systematic quantification of BE epithelial glands using VLE can determine the outcome of endoscopic resection. VLE may have a potential role in assessment of lesion margins.