Abstract
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.
Original language | English (US) |
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Journal | Diseases of the Esophagus |
Volume | 32 |
Issue number | 11 |
DOIs | |
State | Published - Nov 1 2019 |
Keywords
- Barrett's esophagus
- Intelligent real-time image segmentation
- Volumetric laser endomicroscopy
ASJC Scopus subject areas
- Gastroenterology