Masterclass: Advanced GI Endoscopic Imaging (On-Demand) | December 2025-Chromoendoscopy and AI in IBD

Video Transcription

Video Summary

Nassim's lecture addresses challenges in inflammatory bowel disease (IBD) care, highlighting increased incidence, subjective and inconsistent endoscopic scoring (like the Mayo score), and plateaued treatment efficacy. Current assessment tools suffer from inter-observer variability and fail to capture nuanced improvements. Advanced imaging and AI offer solutions: deep neural networks can objectively and accurately assess endoscopic and histologic remission, outperforming subjective human scoring. Innovations like Red Density Algorithm provide continuous, granular scoring, improving sensitivity to disease changes. Real-time AI-assisted endocytoscopy predicts histological healing and relapse risk. AI-enabled tools speed up and standardize scoring, reducing reading time and improving lesion detection. Additionally, intestinal ultrasound (IUS) is a promising non-invasive alternative with high accuracy but limited by operator training and variability. AI can democratize IUS, providing real-time guidance and measurements, enabling broader and more accurate use. Ultimately, Nassim concludes that AI enhances precision and accessibility in IBD care, emphasizing that future clinical success hinges on integrating AI with physician expertise.

Asset Subtitle

Nasim Parsa

Meta Tag

Concept Mayo Score

Concept Ulcerative Colitis Endoscopic Index of Severity

Concept Artificial Intelligence

Concept Intestinal Ultrasound

Concept Interobserver Variability

Keywords

Inflammatory Bowel Disease

AI in Endoscopy

Red Density Algorithm

Intestinal Ultrasound

Deep Neural Networks

Mayo Score

Ulcerative Colitis Endoscopic Index of Severity

Artificial Intelligence

Intestinal Ultrasound

Interobserver Variability