Real-Time Diagnosis of an Early Barrett's Carcinoma using Artificial Intelligence (AI) - Video Case Demonstration
- Introduction We present a clinical case showing the real-time detection, characterization and delineation of an early Barrett’s cancer using AI. Patients and methods A 70-year old patient with a long-segment Barrett’s esophagus (C5M7) was assessed with an AI algorithm. Results The AI system detected a 10 mm focal lesion and AI characterization predicted cancer with a probability of >90%. After ESD resection, histopathology showed mucosal adenocarcinoma (T1a (m), R0) confirming AI diagnosis. Conclusion We demonstrate the real-time AI detection, characterization and delineation of a small and early mucosal Barrett’s cancer.
| Author: | Alanna EbigboORCiD, Robert MendelORCiD, Georgios Tziatzios, Andreas Probst, Christoph PalmORCiDGND, Helmut Messmann |
|---|---|
| DOI: | https://doi.org/10.1055/s-0040-1704075 |
| Parent Title (English): | Endoscopy |
| Publisher: | Thieme |
| Document Type: | conference proceeding (presentation, abstract) |
| Language: | English |
| Year of first Publication: | 2020 |
| Release Date: | 2022/05/30 |
| Tag: | Artificial Intelligence; Barrett's Carcinoma |
| GND Keyword: | Speiseröhrenkrebs; Künstliche Intelligenz; Diagnose |
| Volume: | 52 |
| Issue: | S 01 |
| Pagenumber: | S23 |
| Konferenzangabe: | ESGE Days 2020 |
| Institutes: | Fakultät Informatik und Mathematik |
| Fakultät Informatik und Mathematik / Regensburg Medical Image Computing (ReMIC) | |
| Begutachtungsstatus: | peer-reviewed |
| research focus: | Lebenswissenschaften und Ethik |
| Licence (German): |
