O30 Deep neural network for the detection of early neoplasia in Barrett’s oesophagus

Abstract

data adds further evidence to the long term benefit of eradication of dysplastic BE in reducing invasive OAC. Achieving and maintaining CRD in dysplastic BE patients reduces OAC risk to a level similar to patients with nondysplastic BE.

Diagnostic Accuracy of Artificial Intelligence (AI) to Detect Early Neoplasia in Barrett's Esophagus: A Non-comparative Systematic Review and Meta-Analysis

“…Fourteen studies were further excluded as they did not meet the eligibility criteria. Finally, twelve studies that met all the inclusion criteria were included for this meta-analysis (16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27). The search strategy and study selection are shown in Figure 1.…”

“…A total of 1,361 patients were included in these studies, with 532,328 images acquired to train the various AI models that were developed. Seven studies were retrospective (16,17,19,22,24,26,27), four studies were prospective (18,21,23,25), and one study had both retrospective and prospective components in their methods (20). In terms of endoscopic imaging modality evaluated, eleven studies included WLE (16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26), three studies included NBI (17,22,27), and three studies included virtual chromoendoscopy images (i-Scan) (24)(25)(26).…”

“…Hashimoto ( 22) Samarasena ( 23 the basis of their AI model (17,(19)(20)(21)(22)(23)(24)(25)(26)(27). Three studies had used a proprietary pre-training dataset of images from various parts of the gastrointestinal tracts known as "GastroNet" (20,21,27).…”

“…Only two studies demonstrated the real-time capabilities of their AI models (21,22). Eleven studies documented that endoscopic images included were confirmed on histopathological reports (16)(17)(18)(19)(20)(21)(22)(24)(25)(26)(27). Among all included studies, there were slight differences in the definitions of dysplastic lesions, including endoscopic images of BE with high-grade dysplasia, T1/intramucosal adenocarcinoma, esophageal adenocarcinoma, or a combination of the above.…”

“…All twelve studies reported the sensitivity and specificity of their AI model at detecting early BE neoplasia. Eleven studies (16,(18)(19)(20)(21)(22)(25)(26)(27), including two studies which are sub-studies of de Groof et al (20), of 191,278 endoscopic images or frames (for video-based studies) demonstrated that AI is very accurate at detecting early BE neoplasia with the respective pooled sensitivity, specificity and diagnostic odds ratio (DOR): 90.3% [95% CI: 87.1%−92.7%] (Figure 2), 84.4% [95% CI: 80.2-87.9%] (Figure 3) and 48.1 [95% CI: 28.4-81.5] (Figure 4). However, all the primary outcome analyses had significant heterogeneity (I 2 of >50%, Tau 2 of >0.1 and p < 0.05).…”