Diagnostic accuracy of artificial intelligence-aided capsule endoscopy (TOP100) in overt small bowel bleeding

Background Capsule endoscopy (CE) is the first-choice exploration in case of overt small bowel bleeding (SBB). An early CE is known to increase diagnostic yield, but long reading times may delay therapeutics. The study evaluates the diagnostic performance of the artificial intelligence tool TOP100 in patients with overt SBB undergoing early CE with Pillcam SB3. Methods Patients who underwent early CE (up to 14 days from the bleeding episode) for suspected overt SBB were included. One experienced endoscopist prospectively performed standard reading (SR) and a second blind experienced endoscopist performed a TOP100-based reading (TR). The primary endpoint was TR diagnostic accuracy for lesions with high bleeding potential (P2). Results A total of 111 patients were analyzed. The most common clinical presentation was melena (64%). CE showed angiodysplasias in 40.5% of patients (45/111). In per-patient analysis, TR showed a sensitivity of 90.48% (95% CI 82.09–95.80), specificity of 100% (95% CI 87.23–100) with a PPV of 100% (95% CI 94.01–100), NPV of 77.14% (95% CI 63.58–86.71) and diagnostic accuracy of 92.79 (86.29–96.84). At multivariate analysis, adequate intestinal cleansing was the only independent predictor of concordance between TR and SR (OR 2.909, p = 0.019). The median reading time for SR and TR was 23 min (18.0–26.8) and 1.9 min (range 1.7–2.1), respectively ( p < 0.001). Conclusions TOP100 provides a fast-reading mode for early CE in case of overt small bowel bleeding. It identifies most patients with active bleeding and angiodysplasias, aiding in the prioritization of therapeutic procedures. However, its accuracy in detecting ulcers, varices and P1 lesions seems insufficient. Graphical abstract