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Forrest Classification for Bleeding Peptic Ulcer: A New Look at the Old Endoscopic Classification.

Hsu-Heng YenPing-Yu WuTung-Lung WuSiou-Ping HuangYang-Yuan ChenMei-Fen ChenWen-Chen LinCheng-Lun TsaiKang-Ping Lin
Published in: Diagnostics (Basel, Switzerland) (2022)
The management of peptic ulcer bleeding is clinically challenging. For decades, the Forrest classification has been used for risk stratification for nonvariceal ulcer bleeding. The perception and interpretation of the Forrest classification vary among different endoscopists. The relationship between the bleeder and ulcer images and the different stages of the Forrest classification has not been studied yet. Endoscopic still images of 276 patients with peptic ulcer bleeding for the past 3 years were retrieved and reviewed. The intra-rater agreement and inter-rater agreement were compared. The obtained endoscopic images were manually drawn to delineate the extent of the ulcer and bleeding area. The areas of the region of interest were compared between the different stages of the Forrest classification. A total of 276 images were first classified by two experienced tutor endoscopists. The images were reviewed by six other endoscopists. A good intra-rater correlation was observed (0.92-0.98). A good inter-rater correlation was observed among the different levels of experience (0.639-0.859). The correlation was higher among tutor and junior endoscopists than among experienced endoscopists. Low-risk Forrest IIC and III lesions show distinct patterns compared to high-risk Forrest I, IIA, or IIB lesions. We found good agreement of the Forrest classification among different endoscopists in a single institution. This is the first study to quantitively analyze the obtained and explain the distinct patterns of bleeding ulcers from endoscopy images.
Keyphrases
  • deep learning
  • convolutional neural network
  • machine learning
  • atrial fibrillation
  • optical coherence tomography
  • ultrasound guided
  • endoscopic submucosal dissection