A Pilot Study on Automatic Three-Dimensional Quantification of Barrett's Esophagus for Risk Stratification and Therapy Monitoring.
Journal:
Gastroenterology
Published Date:
Sep 1, 2021
Abstract
BACKGROUND & AIMS: Barrett's epithelium measurement using widely accepted Prague C&M classification is highly operator dependent. We propose a novel methodology for measuring this risk score automatically. The method also enables quantification of the area of Barrett's epithelium (BEA) and islands, which was not possible before. Furthermore, it allows 3-dimensional (3D) reconstruction of the esophageal surface, enabling interactive 3D visualization. We aimed to assess the accuracy of the proposed artificial intelligence system on both phantom and endoscopic patient data.
Authors
Keywords
Aged
Automation
Barrett Esophagus
Deep Learning
Disease Progression
Esophageal Mucosa
Esophagogastric Junction
Esophagoscopy
Female
Humans
Image Interpretation, Computer-Assisted
Imaging, Three-Dimensional
Male
Pilot Projects
Predictive Value of Tests
Reproducibility of Results
Risk Assessment
Risk Factors
Severity of Illness Index
Treatment Outcome